相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。In-situ fatigue life analysis by modal acoustic emission, direct current potential drop and digital image correlation for steel
Sulochana Shrestha et al.
INTERNATIONAL JOURNAL OF FATIGUE (2021)
Crack Length Measurement Using Convolutional Neural Networks and Image Processing
Yingtao Yuan et al.
SENSORS (2021)
Machine learning approach to predict fatigue crack growth
Rohit G. Kamble et al.
MATERIALS TODAY-PROCEEDINGS (2021)
Review of Structural Health Monitoring Methods Regarding a Multi-Sensor Approach for Damage Assessment of Metal and Composite Structures
Christoph Kralovec et al.
SENSORS (2020)
Detection and size estimation of crack in plate based on guided wave propagation
Beata Zima et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2020)
Fatigue crack growth of a hot mix asphalt using digital image correlation
Calvin M. Stewart et al.
INTERNATIONAL JOURNAL OF FATIGUE (2019)
Analysis for post-impact tensile-tensile fatigue damage of 2024-T3 sheets based on tests, digital image correlation (DIC) technique and finite element simulation
Yajun Chen et al.
INTERNATIONAL JOURNAL OF FATIGUE (2019)
High-Sensitivity Dielectric Resonator-Based Waveguide Sensor for Crack Detection on Metallic Surfaces
Qingmin Wang et al.
IEEE SENSORS JOURNAL (2019)
A digital image correlation analysis on a sheet AA6061-T6 bi-failure specimen to predict static failure
Behzad V. Farahani et al.
ENGINEERING FAILURE ANALYSIS (2018)
Study of anisotropic crack growth behavior for aluminum alloy 7050-T7451
Jun Cao et al.
ENGINEERING FRACTURE MECHANICS (2018)
A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method
Long Wen et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2018)
NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naive Bayes Data Fusion
Fu-Chen Chen et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2018)
Fatigue crack detection using dual laser induced nonlinear ultrasonic modulation
Peipei Liu et al.
OPTICS AND LASERS IN ENGINEERING (2018)
Pattern Deep Region Learning for Crack Detection in Thermography Diagnosis System
Jue Hu et al.
METALS (2018)
Crack detection using image processing: A critical review and analysis
Arun Mohan et al.
ALEXANDRIA ENGINEERING JOURNAL (2018)
Microwaves-Based High Sensitivity Sensors for Crack Detection in Metallic Materials
Ali M. Albishi et al.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES (2017)
Passive RFID sensor systems for crack detection & characterization
Jun Zhang et al.
NDT & E INTERNATIONAL (2017)
The Detection and Recognition of Bridges'Cracks Based on Deep Belief Network
Wang Xuejun et al.
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING (CSE) AND IEEE/IFIP INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (EUC), VOL 1 (2017)
A texture-Based Video Processing Methodology Using Bayesian Data Fusion for Autonomous Crack Detection on Metallic Surfaces
Fu-Chen Chen et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2017)
A Novel Breaking Strategy for Electrical Endurance Extension of Electromagnetic Alternating Current Contactors
Ziran Wu et al.
IEEE TRANSACTIONS ON COMPONENTS PACKAGING AND MANUFACTURING TECHNOLOGY (2016)
A Survey of Fault Diagnosis and Fault-Tolerant Techniques-Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches
Zhiwei Gao et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2015)
Board-Level Functional Fault Diagnosis Using Multikernel Support Vector Machines and Incremental Learning
Fangming Ye et al.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS (2014)
3D Convolutional Neural Networks for Human Action Recognition
Shuiwang Ji et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2013)
Surface crack detection in welds using thermography
Patrik Broberg
NDT & E INTERNATIONAL (2013)
Complementary Split-Ring Resonator for Crack Detection in Metallic Surfaces
Ali M. Albishi et al.
IEEE MICROWAVE AND WIRELESS COMPONENTS LETTERS (2012)
Electromagnetic Stimulation of the Acoustic Emission for Fatigue Crack Detection of the Sheet Metal
Liang Jin et al.
IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY (2010)
Instantaneous reference-free crack detection based on polarization characteristics of piezoelectric materials
Seung Bum Kim et al.
SMART MATERIALS AND STRUCTURES (2007)