☆ 4.7 Review

A review in guided-ultrasonic-wave-based structural health monitoring: From fundamental theory to machine learning techniques

ULTRASONICS (2023)

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Article Engineering, Mechanical

Structural Health Monitoring for impact localisation via machine learning

F. Dipietrangelo et al.

Summary: This manuscript focuses on the application of machine learning in structural health monitoring. Two algorithms, polynomial regression and shallow neural network, were used to detect impacts on an aluminum plate. The performance of both algorithms was optimized and compared in terms of accuracy. The study confirmed the effectiveness of machine learning in impact detection.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2023)

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Article Materials Science, Characterization & Testing

Uncertainty quantification in super-resolution guided wave array imaging using a variational Bayesian deep learning approach

Homin Song et al.

Summary: A Bayesian deep learning approach is proposed to quantify and interpret uncertainties in super-resolution guided wave array imaging. The approach successfully quantifies two types of uncertainties: aleatoric uncertainty inherent in the data and epistemic uncertainty associated with the Bayesian deep learning model.

NDT & E INTERNATIONAL (2023)

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Article Engineering, Industrial

Probabilistic physics-informed machine learning for dynamic systems

Abhinav Subramanian et al.

Summary: This paper proposes a physics-informed machine learning approach for response prediction in dynamic systems. The approach combines a physics-based model and a probabilistic machine learning model to account for model error. The model error is quantified using Bayesian state estimation, and the machine learning model is trained to predict the output discrepancy. Different computational options are developed for different types of inputs and computational requirements. The proposed approach is demonstrated with numerical examples of a deep beam and hypersonic flow over an aircraft panel.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2023)

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Article Acoustics

Ultrasonic image denoising using machine learning in point contact excitation and detection method

Himanshu Singh et al.

Summary: A point contact/Coulomb coupling technique is used to visualize ultrasonic waves in PZT ceramics. Different types of noise, including speckle, Gaussian, Poisson, and salt and pepper noise, corrupt the ultrasonic signal and degrade the quality of images. This study implements deep learning-based convolutional autoencoders for noise modeling and denoising of ultrasonic images. Quantitative analysis using PSNR and SSIM metrics shows that speckle noise model performs better than other noise models.

ULTRASONICS (2023)

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Article Acoustics

Numerical and experimental investigation of guided ultrasonic wave propagation in non-uniform plates with structural phase variations

Beata Zima et al.

Summary: The article presents the results of numerical and experimental investigations into guided wave propagation in aluminum plates with variable thickness. Specially designed plate surfaces and statistical description were used to analyze the wave propagation characteristics caused by non-uniform thickness. The study proved that the signal time course and wave modes in specimens with variable thickness can be accurately predicted.

ULTRASONICS (2023)

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Article Engineering, Mechanical

Non-contact microcrack detection via nonlinear Lamb wave mixing and laser line arrays

Santhakumar Sampath et al.

Summary: In this study, a non-contact nonlinear Lamb wave mixing technique based on laser line-array excitation is developed for microcrack detection in plate-like structures. The developed system allows the user to selectively implement the Lamb wave mode at the desired input frequency by adjusting the optical lens. Experimental validation shows that the proposed system can locate and detect microcracks in plate-like structures.

INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES (2023)

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Article Engineering, Mechanical

Laser ultrasonic imaging of submillimeter defect in a thick waveguide using entropy-polarized bilateral filtering and minimum variance beamforming

Yi He et al.

Summary: A laser-ultrasonics imaging approach is developed to accurately characterize submillimeter defects in thick waveguides using denoising and defect imaging techniques.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2023)

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Article Engineering, Mechanical

A two-step localization method using wavelet packet energy characteristics for low-velocity impacts on composite plate structures

Qi Liu et al.

Summary: A two-step impact localization method is proposed in this paper, which uses wavelet packet energy characteristics to address the issue of low localization accuracy in previous studies due to the low sampling frequency of FBG sensing system. The method involves the collection of impact samples, feature extraction, and two-step localization. The effectiveness and satisfactory performance of the proposed method are proved through experiments on CFRP plate.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2023)

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Article Engineering, Multidisciplinary

Guidelines for effective unsupervised guided wave compression and denoising in long-term guided wave structural health monitoring

Kang Yang et al.

Summary: This paper investigates the effectiveness of joint compression and denoising strategies using realistic, long-term guided wave structural health monitoring data. It explores how to optimize data collection and algorithms to utilize guided wave data for compression, denoising, and damage detection.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2023)

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Article Automation & Control Systems

Deep learning approach for delamination identification using animation of Lamb waves

Saeed Ullah et al.

Summary: The complex design of composite structures makes it difficult for conventional visual inspection techniques to detect defects. In this study, the feasibility of implementing deep learning methods for delamination identification in composite laminates was investigated, and two end-to-end deep learning-based models were developed for pixel-wise image segmentation. The models showed good performance on both numerically generated test data and real-world experimental data, enabling the automation of delamination identification without user intervention.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2023)

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Article Acoustics

Damage localization in pressure vessel using guided wave-based techniques: Optimizing the sensor array configuration to mitigate nozzle effects

Chaojie Hu et al.

Summary: Ultrasonic guided waves are suitable for damage monitoring in large structures, but the complex scattering poses a challenge in extracting damage information from pressure vessels equipped with accessories. Signal processing and damage localization analysis methods, along with sensor array configuration optimization and Particle Swarm Optimization algorithm, are employed for accurate damage localization in pressure vessels.

APPLIED ACOUSTICS (2022)

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Article Engineering, Multidisciplinary

Acoustic emission data based deep learning approach for classification and detection of damage-sources in a composite panel

Shirsendu Sikdar et al.

Summary: This paper investigates structural health monitoring for lightweight complex composite structures using a data-driven deep learning approach, demonstrating effective classification of damage source regions on composite panels. The proposed deep learning method shows high accuracy in damage monitoring and classification.

COMPOSITES PART B-ENGINEERING (2022)

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Editorial Material Computer Science, Interdisciplinary Applications

An editorial perspective: new team, aims and scope and advances of EWCO

Jessica Zhang et al.

ENGINEERING WITH COMPUTERS (2022)

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Article Engineering, Multidisciplinary

A GAN noise modeling based blind denoising method for guided waves

Xiushi Cui et al.

Summary: This paper proposes a new denoising method that improves the denoising effect in guided wave detection by combining GAN and AE. The method can effectively reduce noise level and accurately recover peak time of wave packet, especially in low signal-to-noise conditions.

MEASUREMENT (2022)

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Article Engineering, Mechanical

Automated fatigue damage detection and classification technique for composite structures using Lamb waves and deep autoencoder

Hyunseong Lee et al.

Summary: This paper introduces a robust automatic damage diagnosis technique that uses ultrasonic Lamb waves and a deep autoencoder (DAE) to detect and classify fatigue damage in composite structures. The technique accurately detects and classifies fatigue damage in composite structures, while eliminating the need for manual or signal processing-based damage sensitive feature extraction.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2022)

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Article Materials Science, Characterization & Testing

A Bayesian approach for damage assessment in welded structures using Lamb-wave surrogate models and minimal sensing

Mohammad Ali Fakih et al.

Summary: This study proposes a novel structural health monitoring approach using a minimal LW sensor-actuator set-up for damage detection, localization, and assessment. The results show that damage of different sizes and locations can be successfully identified with a high level of resolution and with quantified uncertainty.

NDT & E INTERNATIONAL (2022)

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Article Instruments & Instrumentation

Life-cycle health monitoring of composite structures using piezoelectric sensor network

Yinghong Yu et al.

Summary: This paper proposes a real-time active smart diagnostic system (SDS) based on piezoelectric sensor network to monitor the whole life-cycle of composite structures. Experimental results demonstrate that the system can effectively monitor the curing process and health status of composite structures, and has the potential to identify different stages.

SMART MATERIALS AND STRUCTURES (2022)

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Article Acoustics

Imaging damage in plate waveguides using frequency-domain multiple signal classification (F-MUSIC)

Xiongbin Yang et al.

Summary: The frequency domain MUSIC (F-MUSIC) algorithm is developed to improve imaging precision in in situ health monitoring with a sparse sensor network. By modeling in the frequency domain, F-MUSIC can fuse rich information scattered in a broad band and is not limited by the quantity of damage.

ULTRASONICS (2022)

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Article Chemistry, Multidisciplinary

An Artificial Intelligence Approach to Fatigue Crack Length Estimation from Acoustic Emission Waves in Thin Metallic Plates

Joseph Chandler Garrett et al.

Summary: The study investigates the correlation between fatigue crack length and acoustic emission (AE) signal signatures and develops a novel AE signal analysis technique using artificial intelligence (AI). By combining finite element modeling and fatigue experiments, the research builds an AI-enabled system capable of accurately predicting the length of a fatigue crack from AE signals. This novel AI system proves to be effective with an accuracy of 98.4%.

APPLIED SCIENCES-BASEL (2022)

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Article Mechanics

Impact identification of composite cylinder based on improved deep metric learning model and weighted fusion Tikhonov regularized total least squares

Sijue Li et al.

Summary: The proposed two-stage method for random impact force localization and reconstruction utilizes deep networks for feature extraction and weighted fusion for reconstruction.

COMPOSITE STRUCTURES (2022)

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Article Automation & Control Systems

Microcrack Defect Quantification Using a Focusing High-Order SH Guided Wave EMAT: The Physics-Informed Deep Neural Network GuwNet

Hongyu Sun et al.

Summary: This study proposes a physics-informed deep neural network called GuwNet for accurate quantification of microcrack defects using a high-frequency, high-order shear horizontal guided wave electromagnetic acoustic transducer (EMAT). By introducing the concept of NDT physics, the poor predictive abilities of the deep neural network trained on small datasets are compensated.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2022)

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Article Engineering, Aerospace

Guided Wave Excitation and Sensing in Constant Irregular Cross Section Structures with the Semianalytical Finite-Element Method

Zhengyan Yang et al.

Summary: This paper introduces a semi-analytical finite-element method for guided wave excitation and sensing in irregular cross sections, and proposes a modal control method using optimal transducer design. The experimental investigation validates the feasibility of the proposed method, and a feasible optimal and economical transducer design method is presented.

JOURNAL OF AEROSPACE ENGINEERING (2022)

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Article Materials Science, Multidisciplinary

Localization of low velocity impacts on CFRP laminates based on FBG sensors and BP neural networks

Xianglong Wen et al.

Summary: A low velocity impact supervisory and testing system based on FBG sensors was built for CFRP laminates to obtain a strain sensitivity model. The use of genetic algorithm optimized the FBG sensing network configuration, while FFT, PCA, and BP neural network were employed for feature extraction and model training. The impact localization for CFRP laminates was successfully achieved with an average localization error of 2.1 cm.

MECHANICS OF ADVANCED MATERIALS AND STRUCTURES (2022)

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Article Materials Science, Multidisciplinary

Early Fatigue Crack Damage Identification by Multi-classification Support-Vector Machine Based on Lamb Wave and Temperature Compensation

Gaozheng Zhao et al.

Summary: This study proposes a temperature compensation method based on the extraction of Lamb wave characteristic parameters for damage identification. By establishing a compensation model, the influence of temperature on characteristic parameters can be eliminated, thus improving the accuracy of damage identification.

JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE (2022)

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Article Materials Science, Characterization & Testing

Locating Low Velocity Impacts on a Composite Plate Using Multi-Frequency Image Fusion and Artificial Neural Network

Bo Feng et al.

Summary: This paper analyzes the multi-frequency characteristics of impact-induced guided waves and proposes two fusion methods to combine the features. The results show that the localization errors of the two fusion methods are 4.39 mm and 3.61 mm on average, and 3.56 mm and 3.13 mm for the median errors.

JOURNAL OF NONDESTRUCTIVE EVALUATION (2022)

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Article Engineering, Mechanical

TwIST sparse regularization method using cubic B-spline dual scaling functions for impact force identification

Chun Huang et al.

Summary: The study utilizes sparse regularization to solve impact force identification problems, combining the TwIST algorithm and B-spline scaling functions to improve accuracy and computational efficiency.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2022)

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Article Engineering, Mechanical

Effective combination of modeling and experimental data with deep metric learning for guided wave-based damage localization in plates

Shengyuan Zhang et al.

Summary: This study proposes a data-driven method for damage localization using both modeling and experimental training data. By utilizing deep metric learning and kernel regression, this method overcomes the shortage of training data and improves localization accuracy.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2022)

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Article Engineering, Mechanical

Ultrasonic guided wave imaging with deep learning: Applications in corrosion mapping

Xiaocen Wang et al.

Summary: In this paper, a rapid guided wave imaging method based on convolutional neural network (CNN) is proposed for quantitative evaluation of corrosion damage. The method involves offline training and online imaging, and has shown excellent imaging performance and high success rate in numerical experiments.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2022)

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Article Engineering, Multidisciplinary

Distribution adaptation deep transfer learning method for cross-structure health monitoring using guided waves

Bin Zhang et al.

Summary: This article proposes a cross-structure ultrasonic guided wave structural health monitoring method based on distribution adaptation deep transfer learning to solve the feature generalization problem in different monitoring structures. The experimental results show that the method can utilize single-sensor monitoring data in one structure to achieve multi-sensor damage monitoring in another structure and achieve damage imaging visualization, with significantly superior imaging performance compared to existing methods.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2022)

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Article Engineering, Multidisciplinary

Fatigue damage detection from imbalanced inspection data of Lamb wave

Jingjing He et al.

Summary: This study proposed a method for damage detection using imbalanced inspection data collected through Lamb wave detection, which achieved crack identification and detection through improved minority class over-sampling technique and classification methods.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2022)

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Article Engineering, Multidisciplinary

Damage imaging in skin-stringer composite aircraft panel by ultrasonic-guided waves using deep learning with convolutional neural network

Ranting Cui et al.

Summary: This article presents a method for structural damage detection using deep learning and convolutional neural networks, which automatically select the most sensitive wave features and have generalization capabilities. With a specific 1D-CNN algorithm, successful imaging of damage in key regions of composite aircraft structures has been achieved.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2022)

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Article Engineering, Multidisciplinary

A feature learning-based method for impact load reconstruction and localization of the plate-rib assembled structure

Tao Chen et al.

Summary: The proposed method utilizes deep learning to reconstruct and localize impact loads, consisting of a convolutional-recurrent encoder-decoder neural network and a deep convolutional-recurrent neural network. The effectiveness of the method was validated through numerical studies and experiments, showing its ability to accurately and quickly handle complex structures. The performance of deep convolutional-recurrent neural network is influenced by sensor numbers and network architecture, with a proposed strategy to reduce training locations.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2022)

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Article Acoustics

Damage characterization using CNN and SAE of broadband Lamb waves

Fei Gao et al.

Summary: The method based on Lamb wave demonstrates great potential in structural health monitoring and nondestructive testing, with a proposed broadband Lamb wave deep learning algorithm for damage localization and quantification. By applying different mode selections, signal processing methods, and deep learning algorithms, the method shows effectiveness and high accuracy in utilizing rich broadband information.

ULTRASONICS (2022)

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Article Instruments & Instrumentation

A multi-level damage classification technique of aircraft plate structures using Lamb wave-based deep transfer learning network

Weihan Shao et al.

Summary: This paper presents a deep transfer learning network based on Lamb waves for multi-level damage classification of plate-type structures. The study demonstrates the effectiveness and reliability of the proposed technique through experimental results, showing improved efficiency in model calculation by adopting the concept of fine-tune transfer learning.

SMART MATERIALS AND STRUCTURES (2022)

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Article Acoustics

Guided waves-based damage identification in plates through an inverse Bayesian process

W. Wu et al.

Summary: The use of guided waves to identify damage has become a popular method due to its robustness and fast execution, as well as the advantage of being able to inspect large areas and detect minor structural defects. By analyzing the scattered field, one can characterize the type and size of the plate damage.

ULTRASONICS (2022)

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Article Acoustics

Deep learning inversion with supervision: A rapid and cascaded imaging technique

Junkai Tong et al.

Summary: In this article, a new deep learning inversion method called DLIS is proposed and applied for corrosion mapping. The results show that DLIS can effectively reduce the scale of training set and provide reliable reconstruction accuracy when dealing with multiple defects of complex shape.

ULTRASONICS (2022)

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Article Materials Science, Multidisciplinary

Machine Learning Based Quantitative Damage Monitoring of Composite Structure

Xinlin Qing et al.

Summary: Composite materials are widely used in various industries due to their excellent mechanical properties. However, analyzing the integrity and durability of composite structures is challenging due to their complex characteristics and the variability of load and environmental conditions. Structural health monitoring (SHM), based on built-in sensor networks, has been recognized as a method to enhance the safety and reliability of composite structures and reduce operational costs.

INTERNATIONAL JOURNAL OF SMART AND NANO MATERIALS (2022)

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Review Engineering, Multidisciplinary

Emergence of Machine Learning Techniques in Ultrasonic Guided Wave-based Structural Health Monitoring: A Narrative Review

Afshin Sattarifar et al.

Summary: This review study focuses on the application of machine learning approaches in Ultrasonic Guided Wave-based structural health monitoring. By extracting features and processing patterns, machine learning algorithms have the potential to improve traditional damage detection algorithms and enhance the accuracy and efficiency of damage detection.

INTERNATIONAL JOURNAL OF PROGNOSTICS AND HEALTH MANAGEMENT (2022)

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Article Mechanics

Delamination prediction in composite panels using unsupervised-feature methods with wavelet-enhanced wave

Mahindra Rautela et al.

Summary: The demand for reliable and robust structural health monitoring (SHM) procedures for aerospace composite structures is increasing rapidly. In this paper, two different unsupervised feature learning approaches are proposed to predict delamination in aerospace structures. The approaches utilize dimensionality reduction techniques and deep learning-based deep convolutional autoencoders. Experimental results show that the deep convolutional autoencoder approach generates better reconstructions with higher accuracy.

COMPOSITE STRUCTURES (2022)

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Article Acoustics

Theoretical and experimental investigation of circumferential guided waves in orthotropic annuli

Jinyun Lin et al.

Summary: This study aims to provide accurate dispersion results in an arbitrarily thick orthotropic homogeneous cylindrical shell by combining the Floquet BC method and SFFEM method. The combination of these two methods has clear advantages in extracting circumferential guided wave dispersion characteristics through simulation and experimental measurements.

ULTRASONICS (2022)

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Article Acoustics

One-way Lamb and SH mixing method in thin plates with quadratic nonlinearity: Numerical and experimental studies

Yuzi Liu et al.

Summary: This study demonstrates that the one-way Lamb and SH mixing method can quantitatively evaluate and locate the damage region of quadratic nonlinearity in thin plates. Resonant behavior is observed when the primary S-0-mode Lamb waves and SH0 waves mix in the region with quadratic nonlinearity, with the acoustic nonlinear parameter increasing monotonously with material nonlinearity, damage region length, and resonant wave frequency. The study also shows that the damage region can be located using the time-domain signal of the resonant wave based on the one-way S0-SH0 mixing method.

ULTRASONICS (2022)

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Article Acoustics

Spectral element modeling of ultrasonic guided wave propagation in optical fibers

Piotr Fiborek et al.

Summary: This paper introduces a new modeling approach and parallelized computing method to improve the efficiency of fiber optic guided wave sensing simulation. The study demonstrates that the spectral element method-based simulation accurately captures the directional sensitivity of fiber optic sensors and the reflection phenomena from damage.

ULTRASONICS (2022)

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Article Acoustics

Characterization of interfacial property of a two-layered plate using a nonlinear low-frequency Lamb wave approach

Han Chen et al.

Summary: This work investigates the feasibility of using a nonlinear low-frequency Lamb wave approach for characterizing the interfacial property of a two-layered plate. The approximate phase-velocity matching in the low-frequency region can still guarantee the cumulative second harmonic generation of primary Lamb wave propagation. Numerical analysis and experimental measurement show the potential of using the SHG effect of low-frequency Lamb wave propagation to characterize minor changes in the interfacial properties.

ULTRASONICS (2022)

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Article Acoustics

Damage identification using wave damage interaction coefficients predicted by deep neural networks

Christoph Humer et al.

Summary: This paper presents a damage identification method for plate-like structures based on a database of wave damage interaction coefficients (WDICs), which is substantially enhanced by using deep neural networks (DNNs). The method accurately replicates and interpolates complex WDIC patterns and allows for high-confidence identification of damage characteristics.

ULTRASONICS (2022)

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Article Computer Science, Information Systems

Semi-Supervised Learning for Automatic Atrial Fibrillation Detection in 24-Hour Holter Monitoring

Peng Zhang et al.

Summary: This study developed a novel semi-supervised learning method for automatic detection of paroxysmal atrial fibrillation (AF). The method utilized a small amount of labeled data and a large amount of unlabeled data to train a deep learning model. The results showed that the method achieved comparable accuracy to supervised learning methods while significantly reducing the workload of data annotation.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2022)

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Article Computer Science, Information Systems

Data-Adaptive Censoring for Short-Term Wind Speed Predictors Based on MLP, RNN, and SVM

Ali Ogun Sarp et al.

Summary: This study introduces novel short-term wind speed predictors based on MLP, RNN, and SVM with the DAC strategy. The DAC strategy, based on the LMS algorithm, iteratively selects informative wind data for training and reduces the training costs without significantly affecting the prediction performances. Simulation results on real-life large-scale data confirm the attractive features of the proposed predictors.

IEEE SYSTEMS JOURNAL (2022)

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Article Engineering, Mechanical

Sparse ultrasonic guided wave imaging with compressive sensing and deep learning

Xiaocen Wang et al.

Summary: A sparse UGW imaging algorithm based on compressive sensing and deep learning models is proposed to address the limitation of imaging quality due to the number of transducers in service. By using CS and deep learning models, the method can effectively reconstruct sparse detection signals acquired by a small number of transducers. Experimental and simulation results demonstrate the effectiveness of the proposed method in achieving high-quality imaging with limited transducers.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2022)

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Article Acoustics

Machine learning-enabled resolution-lossless tomography for composite structures with a restricted sensing capability

Jianwei Yang et al.

Summary: This article introduces a tomographic imaging approach based on machine learning and algebraic reconstruction technique for in-situ ultrasound imaging and structural health monitoring of composite materials. By segmenting and extracting features of blurry ART images, it accurately images artificial anomalies and delaminations, while minimizing false alarms.

ULTRASONICS (2022)

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Article Acoustics

Broadband torsional guided wave magnetostrictive patch transducer with circumferential alternating permanent magnet array for structural health monitoring

Shujuan Wang et al.

Summary: This paper proposes a broadband torsional guided wave MPT based on T(0,1) guided waves and verifies its bandwidth and wavelength characteristics through experiments. By using frequency sweeping detection, through-hole defects of different sizes can be quantitatively analyzed, and the remaining service life of the test specimen can be predicted more accurately.

ULTRASONICS (2022)

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Article Computer Science, Information Systems

A Composite Approach of Intrusion Detection Systems: Hybrid RNN and Correlation-Based Feature Optimization

Sunil Gautam et al.

Summary: This study presents a hybrid model based on deep learning called Bidirectional Recurrent Neural Network using Long Short-Term Memory and Gated Recurrent Unit for intrusion detection. Through simulations on a public dataset, the model demonstrates high performance in accurately predicting network attacks.

ELECTRONICS (2022)

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Review Computer Science, Information Systems

A Review on Machine Learning Styles in Computer Vision-Techniques and Future Directions

Supriya Mahadevkar et al.

Summary: Computer applications have shifted from single data processing to machine learning due to the accessibility and availability of massive volumes of data obtained through the internet and various sources. This paper discusses the different machine learning techniques used in computer vision, deep learning, neural networks, and machine learning. The applications of machine learning in computer vision include object identification, object classification, and extracting usable information from images, graphic documents, and videos.

IEEE ACCESS (2022)

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Article Computer Science, Artificial Intelligence

Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-Based Beam Search

Xiao Wang et al.

Summary: This paper proposes a novel multi-agent reinforcement learning based beam search tracking strategy, called BeamTracking, to tackle the limitations of traditional visual trackers in challenging scenarios. By maintaining multiple tracking trajectories and applying beam search, accumulated errors can be reduced and tracking accuracy and reliability can be improved.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2022)

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Article Engineering, Multidisciplinary

Noncontact super-resolution guided wave array imaging of subwavelength defects using a multiscale deep learning approach

Homin Song et al.

Summary: This article introduces a noncontact super-resolution guided wave array imaging approach based on deep learning, which can visualize subwavelength defects in plate-like structures. By utilizing two fully convolutional networks to globally detect defects and locally resolve fine structural details, the proposed method achieves the localization and visualization of subwavelength defects.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2021)

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Review Engineering, Multidisciplinary

Impact diagnosis in stiffened structural panels using a deep learning approach

Sakib Ashraf Zargar et al.

Summary: This article presents an approach for autonomous analysis of wavefields for impact diagnosis, utilizing deep neural networks and a unified CNN-RNN architecture. The incorporation of the physics-based concept of time-reversal in the network's recurrent part enhances network performance and demonstrates the model's generalization capabilities. The potential extension of the proposed methodology to an end-to-end vision-based impact monitoring system is also discussed.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2021)

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Article Materials Science, Composites

Vibration Parameters for Impact Detection of Composite Panel: A Neural Network Based Approach

Maurizio Arena et al.

Summary: The study focuses on the utilization of neural algorithms to locate impact positions on composite structures, and validates the approach through finite element simulations and experimental modal parameters identification.

JOURNAL OF COMPOSITES SCIENCE (2021)

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Article Acoustics

Guided waves propagation in multi-layered porous materials by the global matrix method and Biot theory

Gao Jie et al.

Summary: This research presents a numerical approach for analyzing the analytical solution of guided wave propagation characteristics in multilayer two-phased porous media. By establishing global dispersion equations and considering complex boundary conditions, the feasibility and accuracy of the method are confirmed. The method is further applied to lithium ion batteries to study the influence of porosity on guided wave characteristics.

APPLIED ACOUSTICS (2021)

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Article Mechanics

Derivation of circumferential guided waves equations for a multilayered laminate composite hollow cylinder by state-vector and Legendre polynomial hybrid formalism

Mingfang Zheng et al.

Summary: This study presents a new spectral method based on the hybrid formula system for deriving explicit expressions of circumferential guided waves in anisotropic multilayer composite cylinders with arbitrary lay-ups. Numerical verification shows that the proposed method overcomes the complexity of traditional methods and exhibits exponential convergence.

COMPOSITE STRUCTURES (2021)

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Article Engineering, Mechanical

Damage localization in plate-like structures using time-varying feature and one-dimensional convolutional neural network

Shengyuan Zhang et al.

Summary: This study presents a novel Lamb wave-based damage detection and localization method, achieved accurate damage localization through time-varying damage index feature and one-dimensional convolutional neural network. The proposed method performs well in various scenarios without the need for a large-scale actuator-sensor network.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2021)

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Article Engineering, Electrical & Electronic

3-D Source Location by Neural Network for FBG Acoustic Emission Sensors

Tao Fu et al.

Summary: The paper utilizes fiber Bragg grating acoustic emission sensors for an experiment to locate the acoustic emission source, using a neural network method instead of the traditional time-difference location method. The experimental results demonstrate that the neural network location method is suitable for fiber Bragg grating acoustic emission sensors.

IEEE SENSORS JOURNAL (2021)

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Article Acoustics

Guided Wave Tomography Based on Supervised Descent Method for Quantitative Corrosion Imaging

Min Lin et al.

Summary: This article introduces an ultrasonic quantitative tomography method called fast inversion tomography (FIT) for corrosion mapping on plate-like structures. FIT demonstrates great performance in quantitative corrosion imaging through offline training and online inversion stages.

IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL (2021)

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Article Engineering, Mechanical

A probabilistic fatigue life prediction for adhesively bonded joints via ANNs-based hybrid model

Karthik Reddy Lyathakula et al.

Summary: The paper presents an efficient and robust probabilistic fatigue life prediction framework for adhesively bonded joints, calibrating the fatigue life model with experimental data and utilizing probabilistic assessment and neural networks for prediction. This framework allows rapid simulation of fatigue degradation and quantification of uncertainties for probabilistic fatigue life prediction in various joint configurations.

INTERNATIONAL JOURNAL OF FATIGUE (2021)

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Article Computer Science, Information Systems

ESR-GAN: Environmental Signal Reconstruction Learning With Generative Adversarial Network

Xu Kang et al.

Summary: The study introduces a new framework for reconstructing urban environmental signals utilizing a generative adversarial network based on sensory data. Experimental results demonstrate its superior performance in signal recovery accuracy.

IEEE INTERNET OF THINGS JOURNAL (2021)

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Article Automation & Control Systems

Data-Driven Approaches for Characterization of Delamination Damage in Composite Materials

Huan Liu et al.

Summary: Composite materials are crucial in the aerospace industry, but delamination poses a threat to their structural integrity. This article proposes data-driven methods to accurately quantify delamination area and address the problem of insufficient inspection data. Experimental results show that the proposed ensemble learning-based model outperforms other methods in terms of prediction accuracy and efficiency.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2021)

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Article Automation & Control Systems

Detection and Quantization of Fatigue Damage in Laminated Composites With Cross Recursive Quantitative Analysis

Xiaofeng Liu et al.

Summary: The article presents a method for detecting and quantifying fatigue damage in composite laminates using cross recurrence plots and support vector data description models. The proposed method integrates data from diagnostic paths to establish a unified damage index for quantifying fatigue damage under cyclic loading conditions. The feasibility of the method is validated using simulation data and fatigue damage progression data from NASA prognostics data repository.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)

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Article Engineering, Multidisciplinary

Detection of impact on aircraft composite structure using machine learning techniques

Li Ai et al.

Summary: This study utilized acoustic emission (AE) technology to monitor impact damage on aircraft structures, training source location models using random forest and deep learning approaches, resulting in better event localization performance. The analysis showed that by removing unimportant features, the random forest model can significantly reduce storage requirements and computing time while maintaining acceptable localization performance.

MEASUREMENT SCIENCE AND TECHNOLOGY (2021)

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Article Instruments & Instrumentation

Lamb wave damage severity estimation using ensemble-based machine learning method with separate model network

Syed Haider M. Rizvi et al.

Summary: The study developed a general crack quantification model for thin metallic plates using ensemble-based machine learning algorithms, studying Lamb wave signal scattering due to different crack severities and proposing three time-frequency-based damage sensitive indices.

SMART MATERIALS AND STRUCTURES (2021)

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Article Acoustics

Experimental observation of static component generation by Lamb wave propagation in an elastic plate

Guangjian Gao et al.

Summary: The study reported the experimental observation of static component (SC) generation by acoustic radiation induced through Lamb wave propagation in an elastic plate. An experimental approach to directly detect the generated SC has been proposed, demonstrating that the SC does exhibit a cumulative growth effect with propagation distance. Through quantitative measurements of the relative nonlinear acoustic parameter with propagation distance, it was confirmed that the proposed approach is effective in detecting the generated SC of Lamb wave propagation.

ULTRASONICS (2021)

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Article Chemistry, Physical

Damage Detection in Flat Panels by Guided Waves Based Artificial Neural Network Trained through Finite Element Method

Donato Perfetto et al.

Summary: The article introduces a guided wave-based artificial neural network developed through the Finite Element Method for accurately locating damages under various scenarios, demonstrating high accuracy through comparison with experimental and analytical data.

MATERIALS (2021)

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Article Optics

Low energy impact damage identification method of CFRP structure based on wavelet transform and probabilistic neural network

Shizeng Lu et al.

Summary: This paper investigated a method for low energy impact damage identification of CFRP structure using FBG sensors, continuous wavelet transform, and PNN. The experimental results confirmed the feasibility and effectiveness of the proposed method in accurately identifying damage in CFRP structures.

OPTIK (2021)

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Article Acoustics

Supervised learning strategy for classification and regression tasks applied to aeronautical structural health monitoring problems

Roberto Miorelli et al.

Summary: This paper utilizes a kernel-based machine learning strategy for automatic flaw detection, localization, and characterization, using piezoelectric sensors to monitor flaws of various positions and dimensions on aluminum panels. Guided wave signals processed with an imaging algorithm are used to build classification and regression models.

ULTRASONICS (2021)

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Article Acoustics

Modeling and simulation of backward combined harmonic generation induced by one-way mixing of longitudinal ultrasonic guided waves in a circular pipe

Weibin Li et al.

Summary: This paper investigates the modeling of the backward combined harmonic induced by one-way mixing of two primary co-directional guided waves in a circular pipe. The successfully observed backward combined harmonic in the given pipe demonstrates its effectiveness for localized material degradation characterization and location. This study provides a promising means for characterization of localized degradations in pipes.

ULTRASONICS (2021)

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Article Acoustics

Cure monitoring and damage identification of CFRP using embedded piezoelectric sensors network

Xiao Liu et al.

Summary: The study employed the SAFE method and micromechanical model to analyze the Lamb wave propagation characteristics in CFRP, and monitored the vacuum bag moulding process using FBG and piezoelectric sensors.

ULTRASONICS (2021)

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Article Engineering, Multidisciplinary

Fatigue damage characterization for composite laminates using deep learning and laser ultrasonic

Chongcong Tao et al.

Summary: In this work, a novel deep learning approach is proposed to process and characterize guided wave information measured in fatigue tests on FRP laminates. The DL model combines various neural network structures and is trained using unsupervised strategy, incorporating domain knowledge to improve interpretability. Experimental results demonstrate that the DL model successfully characterizes fatigue damage through learned latent wave features.

COMPOSITES PART B-ENGINEERING (2021)

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Article Automation & Control Systems

Bayesian Estimation of Instantaneous Speed for Rotating Machinery Fault Diagnosis

Yue Hu et al.

Summary: The proposed method in this article utilizes Bayesian estimation to accurately estimate the fast time-varying instantaneous speed in a computationally efficient manner. By modeling a linear chirp signal in the Bayesian framework, the method improves robustness against noise or other interferences, and enhances computational efficiency.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2021)

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Article Engineering, Mechanical

Physics-Informed Deep Learning for Computational Elastodynamics without Labeled Data

Chengping Rao et al.

Summary: In this paper, a new method called Physics-Informed Neural Network (PINN) is introduced to model PDE solutions without using labeled data for computational mechanics problems. By taking displacement and stress components as DNN outputs inspired by hybrid finite element analysis, the accuracy and trainability of the network are significantly improved. A composite scheme based on multiple single DNNs is established to forcibly satisfy the initial/boundary conditions, overcoming issues related to weakly imposed conditions in traditional PINN frameworks.

JOURNAL OF ENGINEERING MECHANICS (2021)

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Article Engineering, Mechanical

Probability based impact localization in plate structures using an error index

Rahim Gorgin et al.

Summary: This study introduces a Probability based Impact Localization method for plate structures, which does not require signal interpretation, is effective even in the presence of noise, and can accurately predict Time of Arrivals through a novel method.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2021)

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Article Engineering, Mechanical

A hybrid support vector regression with multi-domain features for low-velocity impact localization on composite plate structure

Qi Liu et al.

Summary: This study proposes a hybrid support vector regression method with multi-domain features to increase the accuracy of low-velocity impact localization on composite plate structures of ships. By incorporating signal preprocessing, feature extraction, and impact localization, the method effectively improves the localization performance. Experimental results demonstrate the satisfactory effectiveness of the proposed method in handling low-velocity impact localization issues on CFRP plates.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2021)

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Article Materials Science, Characterization & Testing

Defect sizing in guided wave imaging structural health monitoring using convolutional neural networks

Roberto Miorelli et al.

Summary: This paper presents an automatic defect localization and sizing procedure for Structural Health Monitoring using guided waves imaging, applied to an aluminum plate with active piezoelectric sensors. The strategy utilizes a convolutional neural network trained on numerical simulations of guided wave signals and processed by the delay and sum imaging algorithm, showing effectiveness in inverting both synthetic and experimental data.

NDT & E INTERNATIONAL (2021)

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Article Computer Science, Artificial Intelligence

Identification of acoustic emission sources for structural health monitoring applications based on convolutional neural networks and deep transfer learning

Daniel Frank Hesser et al.

Summary: Different types of acoustic emission sources were identified using computational intelligence to differentiate between internal damage and external load sources. Machine learning architectures were utilized for training, demonstrating the accurate identification of AE source types through computational intelligence.

NEUROCOMPUTING (2021)

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Article Acoustics

Multi-frequency localized wave energy for delamination identification using laser ultrasonic guided wave

Tianfang Gao et al.

Summary: Delamination is a common failure mode for multilayered structures. Different shapes and sizes of delamination defects have varying sensitivity to guided wave frequencies. In this study, the use of multi-frequency localized wave energy for delamination identification is explored using laser ultrasonic guided waves. Experimental results show lower noises and more discernible profiles of delamination regions in both medial and non-medial delamination cases.

ULTRASONICS (2021)

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Article Acoustics

Combined two-level damage identification strategy using ultrasonic guided waves and physical knowledge assisted machine learning

Mahindra Rautela et al.

Summary: The paper proposes a novel structural health monitoring method for composite structures, combining ultrasonic guided waves and machine learning technology, which utilizes physical knowledge to improve network performance. Two neural networks were trained on an experimental dataset for damage detection and localization, and a combined damage identification strategy for real-time application was proposed.

ULTRASONICS (2021)

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Proceedings Paper Engineering, Biomedical

Temperature compensation for guided waves using convolutional denoising autoencoders

Mahindra Rautela et al.

Summary: In this paper, a deep learning-based temperature compensation method is proposed to mitigate the impact of temperature on guided waves in structural health monitoring. By training a convolutional denoising autoencoder, temperature-affected signals can be transformed into signals at the reference temperature with low mean squared loss and high coefficient of determination, demonstrating successful temperature compensation.

HEALTH MONITORING OF STRUCTURAL AND BIOLOGICAL SYSTEMS XV (2021)

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Article Engineering, Electrical & Electronic

Fault Diagnosis for Electro-Mechanical Actuators Based on STL-HSTA-GRU and SM

Xiaoyu Zhang et al.

Summary: In this study, a novel algorithm combining HSTA-GRU and STL is proposed to predict multiple time-series data for enhanced fault diagnosis of EMAs. By extracting seasonal factors and capturing spatio-temporal relationships among multivariate EMA sensors, the algorithm improves time series prediction and fault classification efficiency.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2021)

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Review Physics, Applied

Physics-informed machine learning

George Em Karniadakis et al.

Summary: Physics-informed learning seamlessly integrates data and mathematical models through neural networks or kernel-based regression networks for accurate inference of realistic and high-dimensional multiphysics problems. Challenges remain in incorporating noisy data seamlessly, complex mesh generation, and addressing high-dimensional problems.

NATURE REVIEWS PHYSICS (2021)

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Article Instruments & Instrumentation

Impact Localization of CFRP Structure Based on FBG Sensor Network

Yaozhang Sai et al.

PHOTONIC SENSORS (2020)

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Article Mechanics

Digital twin approach for damage-tolerant mission planning under uncertainty

Pranav M. Karve et al.

ENGINEERING FRACTURE MECHANICS (2020)

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Article Materials Science, Multidisciplinary

Online Stress Monitoring Technique Based on Lamb-wave Measurements and a Convolutional Neural Network Under Static and Dynamic Loadings

H. J. Lim et al.

EXPERIMENTAL MECHANICS (2020)

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Article Materials Science, Multidisciplinary

Acoustic Emission Source Localization with Generalized Regression Neural Network Based on Time Difference Mapping Method

Z. H. Liu et al.

EXPERIMENTAL MECHANICS (2020)

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Article Mechanics

Global-Local model for guided wave scattering problems with application to defect characterization in built-up composite structures

Antonino Spada et al.

INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES (2020)

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Article Acoustics

Air coupled ultrasonic inspection with Lamb waves in plates showing mode conversion

Arno Roemmeler et al.

ULTRASONICS (2020)

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Review Acoustics

Environmental and operational conditions effects on Lamb wave based structural health monitoring systems: A review

Rahim Gorgin et al.

ULTRASONICS (2020)

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Article Acoustics

Hidden corrosion detection using laser ultrasonic guided waves with multi-frequency local wavenumber estimation

Tianfang Gao et al.

ULTRASONICS (2020)

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Article Engineering, Mechanical

Damage Localization in Pressure Vessel by Guided Waves Based on Convolution Neural Network Approach

Chaojie Hu et al.

JOURNAL OF PRESSURE VESSEL TECHNOLOGY-TRANSACTIONS OF THE ASME (2020)

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Article Mechanics

Detection and classification of matrix cracking in laminated composites using guided wave propagation and artificial neural networks

A. Mardanshahi et al.

COMPOSITE STRUCTURES (2020)

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Article Acoustics

Investigation of thermo-acoustoelastic guided waves by semi -analytical finite element method

Zhengyan Yang et al.

ULTRASONICS (2020)

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Article Acoustics

Active source localization in wave guides based on machine learning

Daniel Frank Hesser et al.

ULTRASONICS (2020)

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Article Instruments & Instrumentation

Deep learning for impact detection in composite plates with sparsely integrated sensors

Andreas M. Damm et al.

SMART MATERIALS AND STRUCTURES (2020)

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Article Computer Science, Information Systems

Automatic Classifying of Patients With Non-Traumatic Fractures Based on Ultrasonic Guided Wave Spectrum Image Using a Dynamic Support Vector Machine

Jean-Gabriel Minonzio et al.

IEEE ACCESS (2020)

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Article Computer Science, Information Systems

A Novel Acoustic Emission Sources Localization and Identification Method in Metallic Plates Based on Stacked Denoising Autoencoders

Li Yang et al.

IEEE ACCESS (2020)

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Article Engineering, Multidisciplinary

Guided wave excitation and propagation in damped composite plates

Hanfei Mei et al.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2019)

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Article Mechanics

Impact localization of composite stiffened panel with triangulation method using normalized magnitudes of fiber optic sensor signals

Byeong-Wook Jang et al.

COMPOSITE STRUCTURES (2019)

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Article Engineering, Electrical & Electronic

Locating Defects in Anisotropic CFRP Plates Using ToF-Based Probability Matrix and Neural Networks

Bo Feng et al.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2019)

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Article Engineering, Electrical & Electronic

Impact Localization and Severity Estimation on Composite Structure Using Fiber Bragg Grating Sensors by Least Square Support Vector Regression

Amitabha Datta et al.

IEEE SENSORS JOURNAL (2019)

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Article Chemistry, Analytical

Guided Wave-Convolutional Neural Network Based Fatigue Crack Diagnosis of Aircraft Structures

Liang Xu et al.

SENSORS (2019)

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Article Instruments & Instrumentation

Determination of Lamb wave phase velocity dispersion using time-frequency analysis

Liang Zeng et al.

SMART MATERIALS AND STRUCTURES (2019)

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Article Engineering, Electrical & Electronic

Damage Identification in Composites Based on Hilbert Energy Spectrum and Lamb Wave Tomography Algorithm

Chenhui Su et al.

IEEE SENSORS JOURNAL (2019)

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Article Engineering, Mechanical

Impact load identification of nonlinear structures using deep Recurrent Neural Network

J. M. Zhou et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2019)

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Article Optics

Ultrasensitive ultrasound detection using an intracavity phase-shifted fiber Bragg grating in a self-injection-locked diode laser

Yupeng Zhu et al.

OPTICS LETTERS (2019)

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Article Chemistry, Analytical

A Convolutional Neural Network for Impact Detection and Characterization of Complex Composite Structures

Iuliana Tabian et al.

SENSORS (2019)

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Article Instruments & Instrumentation

Impact identification using nonlinear dimensionality reduction and supervised learning

V. Meruane et al.

SMART MATERIALS AND STRUCTURES (2019)

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Article Instruments & Instrumentation

Axisymmetric and non-axisymmetric Lamb wave excitation using rectangular actuators

Kai Zhou et al.

SMART MATERIALS AND STRUCTURES (2019)

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Article Construction & Building Technology

Frequency domain decomposition-based multisensor data fusion for assessment of progressive damage in structures

Mehrisadat Makki Alamdari et al.

STRUCTURAL CONTROL & HEALTH MONITORING (2019)

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Article Computer Science, Information Systems

Dualattn-GAN: Text to Image Synthesis With Dual Attentional Generative Adversarial Network

Yali Cai et al.

IEEE ACCESS (2019)

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Article Engineering, Multidisciplinary

Inverse identification of impact locations using multilayer perceptron with effective time-domain feature

Md Sazzad Hossain et al.

INVERSE PROBLEMS IN SCIENCE AND ENGINEERING (2018)

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Article Engineering, Electrical & Electronic

Fault Detection in Wireless Sensor Networks Through SVM Classifier

Salah Zidi et al.

IEEE SENSORS JOURNAL (2018)

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Article Engineering, Electrical & Electronic

Generative Adversarial Networks An overview

Antonia Creswell et al.

IEEE SIGNAL PROCESSING MAGAZINE (2018)

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Article Acoustics

State-vector formalism and the Legendre polynomial solution for modelling guided waves in anisotropic plates

Mingfang Zheng et al.

JOURNAL OF SOUND AND VIBRATION (2018)

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Article Materials Science, Characterization & Testing

Quantitative characterization of disbonds in multilayered bonded composites using laser ultrasonic guided waves

Kuanshuang Zhang et al.

NDT & E INTERNATIONAL (2018)

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Article Chemistry, Analytical

Electromagnetic Acoustic Transducers for Robotic Nondestructive Inspection in Harsh Environments

Sungho Choi et al.

SENSORS (2018)

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Article Materials Science, Composites

Multi-functional interface sensor with targeted IFSS enhancing, interface monitoring and self-healing of GF/EVA thermoplastic composites

Bin Yang et al.

COMPOSITES SCIENCE AND TECHNOLOGY (2018)

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Article Engineering, Aerospace

Artificial Neural Networks for Impact Force Reconstruction on Composite Plates and Relevant Uncertainty Propagation

Giulia Sarego et al.

IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE (2018)

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Article Materials Science, Characterization & Testing

A new method to detect delamination in composites using chirp-excited Lamb wave and wavelet analysis

Bo Feng et al.

NDT & E INTERNATIONAL (2018)

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Article Multidisciplinary Sciences

Deep learning for universal linear embeddings of nonlinear dynamics

Bethany Lusch et al.

NATURE COMMUNICATIONS (2018)

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Article Construction & Building Technology

Optimization of an artificial neural network for fatigue damage identification using analysis of variance

Claudio Sbarufatti

STRUCTURAL CONTROL & HEALTH MONITORING (2017)

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Article Computer Science, Artificial Intelligence

A comparative study of vibrational response based impact force localization and quantification using radial basis function network and multilayer perceptron

Md Sazzad Hossain et al.

EXPERT SYSTEMS WITH APPLICATIONS (2017)

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Article Engineering, Electrical & Electronic

Deep Reinforcement Learning A brief survey

Kai Arulkumaran et al.

IEEE SIGNAL PROCESSING MAGAZINE (2017)

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Article Computer Science, Hardware & Architecture

MACHINE LEARNING PARADIGMS FOR NEXT-GENERATION WIRELESS NETWORKS

Chunxiao Jiang et al.

IEEE WIRELESS COMMUNICATIONS (2017)

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Article Acoustics

SAFE-PML approach for modal study of waveguides with arbitrary cross sections immersed in inviscid fluid

Peng Zuo et al.

JOURNAL OF SOUND AND VIBRATION (2017)

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Article Engineering, Civil

Data-Driven Support Vector Machine with Optimization Techniques for Structural Health Monitoring and Damage Detection

Guoqing Gui et al.

KSCE JOURNAL OF CIVIL ENGINEERING (2017)

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Article Materials Science, Characterization & Testing

Feature guided wave inspection of bond line defects between a stiffener and a composite plate

Xudong Yu et al.

NDT & E INTERNATIONAL (2017)

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Article Materials Science, Characterization & Testing

Numerical modeling of embedded solid waveguides using SAFE-PML approach using a commercially available finite element package

Peng Zuo et al.

NDT & E INTERNATIONAL (2017)

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Article Engineering, Multidisciplinary

An adaptive guided wave-Gaussian mixture model for damage monitoring under time-varying conditions: Validation in a full-scale aircraft fatigue test

Lei Qiu et al.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2017)

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Article Acoustics

Applications of a nanocomposite-inspired in-situ broadband ultrasonic sensor to acousto-ultrasonics-based passive and active structural health monitoring

Menglong Liu et al.

ULTRASONICS (2017)

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Article Acoustics

A new omnidirectional shear horizontal wave transducer using face-shear (d24) piezoelectric ring array

Hongchen Miao et al.

ULTRASONICS (2017)

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Article Mechanics

Simplified elastic wave modeling in seven-wire prestressed parallel strands

C. L. Li et al.

ACTA MECHANICA (2017)

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Article Chemistry, Physical

Lamb Wave Damage Quantification Using GA-Based LS-SVM

Fuqiang Sun et al.

MATERIALS (2017)

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Article Mechanics

Experimental investigation on buckling and free vibration behavior of woven natural fiber fabric composite under axial compression

M. Rajesh et al.

COMPOSITE STRUCTURES (2017)

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Article Construction & Building Technology

Impact energy level assessment of composite structures using MUSIC-ANN approach

Yongteng Zhong et al.

STRUCTURAL CONTROL & HEALTH MONITORING (2016)

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Article Mechanics

Thermoelastic wave characteristics in a hollow cylinder using the modified wave finite element method

C. L. Li et al.

ACTA MECHANICA (2016)

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Article Acoustics

PVDF Multielement Lamb Wave Sensor for Structural Health Monitoring

Baiyang Ren et al.

IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL (2016)

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Article Physics, Applied

Second harmonic generation in composites: Theoretical and numerical analyses

Jinling Zhao et al.

JOURNAL OF APPLIED PHYSICS (2016)

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Article Chemistry, Analytical

Baseline Signal Reconstruction for Temperature Compensation in Lamb Wave-Based Damage Detection

Guoqiang Liu et al.

SENSORS (2016)

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Article Instruments & Instrumentation

Guide waves-based multi-damage identification using a local probability-based diagnostic imaging method

Dongyue Gao et al.

SMART MATERIALS AND STRUCTURES (2016)

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Article Instruments & Instrumentation

A coatable, light-weight, fast-response nanocomposite sensor for the in situ acquisition of dynamic elastic disturbance: from structural vibration to ultrasonic waves

Zhihui Zeng et al.

SMART MATERIALS AND STRUCTURES (2016)

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Article Instruments & Instrumentation

A sparse sensor network topologized for cylindrical wave-based identification of damage in pipeline structures

Qiang Wang et al.

SMART MATERIALS AND STRUCTURES (2016)

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Article Instruments & Instrumentation

Hybrid local FEM/global LISA modeling of damped guided wave propagation in complex composite structures

Yanfeng Shen et al.

SMART MATERIALS AND STRUCTURES (2016)

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Review Instruments & Instrumentation

Guided wave based structural health monitoring: A review

Mira Mitra et al.

SMART MATERIALS AND STRUCTURES (2016)

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Article Acoustics

Guided wave phased array beamforming and imaging in composite plates

Lingyu Yu et al.

ULTRASONICS (2016)

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Article Acoustics

Guided waves based diagnostic imaging of circumferential cracks in small-diameter pipe

Kehai Liu et al.

ULTRASONICS (2016)

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Article Acoustics

Ultrasonic guided wave tomography for ice detection

Xiang Zhao et al.

ULTRASONICS (2016)

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Article Acoustics

Impact imaging of aircraft composite structure based on a model-independent spatial-wavenumber filter

Lei Qiu et al.

ULTRASONICS (2016)

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Article Computer Science, Information Systems

Privacy-Preserving Patient-Centric Clinical Decision Support System on Naive Bayesian Classification

Ximeng Liu et al.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2016)

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Article Computer Science, Artificial Intelligence

Fast detection of impact location using kernel extreme learning machine

Heming Fu et al.

NEURAL COMPUTING & APPLICATIONS (2016)

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Article Engineering, Electrical & Electronic

Low Velocity Impact Localization on CFRP Based on FBG Sensors and ELM Algorithm

Mingshun Jiang et al.

IEEE SENSORS JOURNAL (2015)

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Article Acoustics

Reconstruction of multiple impact forces by wavelet relevance vector machine approach

Souleymane Samagassi et al.

JOURNAL OF SOUND AND VIBRATION (2015)

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Article Acoustics

Investigation of wave propagation in double cylindrical rods considering the effect of prestress

Chunlei Li et al.

JOURNAL OF SOUND AND VIBRATION (2015)

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Article Engineering, Mechanical

Identification of thin elastic isotropic plate parameters applying Guided Wave Measurement and Artificial Neural Networks

Ewa Pabisek et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2015)

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Article Engineering, Electrical & Electronic

Low velocity impact localization system of CFRP using fiber Bragg grating sensors

Shizeng Lu et al.

OPTICAL FIBER TECHNOLOGY (2015)

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Article Instruments & Instrumentation

Impact energy identification on a composite plate using basis vectors

Zhanjun Wu et al.

SMART MATERIALS AND STRUCTURES (2015)

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Article Instruments & Instrumentation

Baseline-free delamination inspection in composite plates by synthesizing non-contact air-coupled Lamb wave scan method and virtual time reversal algorithm

Zenghua Liu et al.

SMART MATERIALS AND STRUCTURES (2015)

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Article Engineering, Multidisciplinary

Development of an artificial neural network for source localization using a fiber optic acoustic emission sensor array

Tao Fu et al.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2015)

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Article Materials Science, Multidisciplinary

Prediction of attenuated guided waves propagation in carbon fiber composites using Rayleigh damping model

Matthieu Gresil et al.

JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES (2015)

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Article Materials Science, Multidisciplinary

Reinforcement corrosion assessment capability of surface bonded and embedded piezo sensors for reinforced concrete structures

Visalakshi Talakokula et al.

JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES (2015)

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Article Materials Science, Multidisciplinary

Validation and evaluation of damage identification using probability-based diagnostic imaging on a stiffened composite panel

Zhanjun Wu et al.

JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES (2015)

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Article Instruments & Instrumentation

Application of a novel optical fiber sensor to detection of acoustic emissions by various damages in CFRP laminates

Qi Wu et al.

SMART MATERIALS AND STRUCTURES (2015)

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Proceedings Paper Physics, Applied

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Acoustic emission source localization in plate-like structures using least-squares support vector machines with delta t feature

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A numerically-enhanced machine learning approach to damage diagnosis using a Lamb wave sensing network

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A Comparison Study of Extreme Learning Machine and Least Squares Support Vector Machine for Structural Impact Localization

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Noncontact detection of fatigue cracks by laser nonlinear wave modulation spectroscopy (LNWMS)

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High temperature thickness measurements of stainless steel and low carbon steel using electromagnetic acoustic transducers

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NDT & E INTERNATIONAL (2014)

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Acousto-ultrasonics-based fatigue damage characterization: Linear versus nonlinear signal features

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Guided wave generation, sensing and damage detection using in-plane shear piezoelectric wafers

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Lamb wave based automatic damage detection using matching pursuit and machine learning

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Damage size characterization algorithm for active structural health monitoring using the A0 mode of Lamb waves

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Review of air-coupled ultrasonic materials characterization

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A novel acoustic emission beamforming method with two uniform linear arrays on plate-like structures

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Wavelet packet energy characterization of low velocity impacts and load localization by optical fiber Bragg grating sensor technique

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Identification of impact force for smart composite stiffened panels

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Characterization of impact damage in composite laminates using guided wavefield imaging and local wavenumber domain analysis

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Comparison of different higher order finite element schemes for the simulation of Lamb waves

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A Hybrid Particle Swarm Optimization (PSO)-Simplex Algorithm for Damage Identification of Delaminated Beams

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Modelling of attenuation of Lamb waves using Rayleigh damping: Numerical and experimental studies

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Acoustic Emission Source Location in Unidirectional Carbon-Fiber-Reinforced Plastic Plates with Virtually Trained Artificial Neural Networks

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Frequency-wavenumber domain analysis of guided wavefields

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Characterization of a large-area PVDF thin film for electro-mechanical and ultrasonic sensing applications

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Modeling of wave propagation in plate structures using three-dimensional spectral element method for damage detection

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Time-domain spectral element method for built-in piezoelectric-actuator-induced lamb wave propagation analysis

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A Survey of Techniques for Internet Traffic Classification using Machine Learning

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Investigations of propagating wave types in railway tracks at high frequencies

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Macro-fiber composite piezoelectric rosettes for acoustic source location in complex structures

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Investigation of fatigue crack in stainless steel using a mobile fiber Brago, grating ultrasonic sensor

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OPTICAL FIBER TECHNOLOGY (2007)

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Impact detection in an aircraft composite panel - A neural-network approach

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Group velocity and characteristic wave curves of Lamb waves in composites: Modeling and experiments

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Air-coupled ultrasonic investigation of multi-layered composite materials

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Fatigue crack propagation monitoring of stainless steel using fiber Bragg grating ultrasound sensors

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Multi-functional fibre Bragg grating sensors for fatigue crack detection in metallic structures

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Some aspects of numerical simulation for Lamb wave propagation in composite laminates

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Modeling wave propagation in damped waveguides of arbitrary cross-section

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Review Acoustics

Guided Lamb waves for identification of damage in composite structures: A review

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Modeling and testing of PZT and PVDF piezoelectric wafer active sensors

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The excitation and detection of lamb waves with planar coil electromagnetic acoustic transducers

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IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL (2005)

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Guided wave propagation mechanics across a pipe elbow

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Finite element prediction of wave motion in structural waveguides

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Advanced signal processing for enhanced damage detection with piezoelectric wafer active sensors

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Determination of ultrasonic wave velocities and phase velocity dispersion curves of an Inconel 600 plate using resonant ultrasound spectroscopy and leaky Lamb waves

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ULTRASONICS (2004)

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Article Mechanics

Lamb wave-based quantitative identification of delamination in CF/EP composite structures using artificial neural algorithm

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Force reconstruction: analysis and regularization of a deconvolution problem

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Response of a fiber Bragg grating ultrasonic sensor

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Impact Location and Quantification on a Composite Panel using Neural Networks and a Genetic Algorithm

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STRAIN (2000)

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Impact monitoring of smart composite laminates using neural network and wavelet analysis

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