4.7 Article

A Health state-related ensemble deep learning method for aircraft engine remaining useful life prediction

Related references

Note: Only part of the references are listed.
Article Chemistry, Analytical

A Fuzzy Similarity-Based Approach to Classify Numerically Simulated and Experimentally Detected Carbon Fiber-Reinforced Polymer Plate Defects

Mario Versaci et al.

Summary: This paper presents an eddy current approach for testing, estimating, and classifying CFRP plate sub-surface defects, mainly due to delamination, through specific 2D magnetic induction field amplitude maps. The authors propose a method based on innovative fuzzy similarity formulations to efficiently classify the maps, and a low-cost analysis system has been implemented. The developed tool can detect and evaluate the extent of surface defects with the same performance as a hardware tool of higher specifications.

SENSORS (2022)

Article Computer Science, Artificial Intelligence

Multitask learning for health condition identification and remaining useful life prediction: deep convolutional neural network approach

Tae San Kim et al.

Summary: The research proposes a multi-task learning method based on convolution neural networks to better reflect the relationship between remaining useful life estimation and health status detection process, and it shows superior performance to existing baseline models in experiments using the C-MAPSS dataset for aero-engine unit prognostics.

JOURNAL OF INTELLIGENT MANUFACTURING (2021)

Article Computer Science, Artificial Intelligence

Evolutionary neural architecture search for remaining useful life prediction

Hyunho Mo et al.

Summary: This paper proposes a Neural Architecture Search technique based on an Evolutionary Algorithm to optimize the architecture of Deep Neural Networks for accurate predictions of the remaining useful life. Experimental results demonstrate the reliability and effectiveness of this method in industrial applications.

APPLIED SOFT COMPUTING (2021)

Article Computer Science, Interdisciplinary Applications

An ensemble framework based on convolutional bi-directional LSTM with multiple time windows for remaining useful life estimation

Tangbin Xia et al.

COMPUTERS IN INDUSTRY (2020)

Article Computer Science, Artificial Intelligence

Data-driven prognosis method using hybrid deep recurrent neural network

Min Xia et al.

APPLIED SOFT COMPUTING (2020)

Article Engineering, Multidisciplinary

Similarity-based deep learning approach for remaining useful life prediction

Mengru Hou et al.

MEASUREMENT (2020)

Article Computer Science, Information Systems

A novel soft computing method for engine RUL prediction

Sandip Kumar Singh et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2019)

Article Engineering, Industrial

An ensemble learning-based prognostic approach with degradation-dependent weights for remaining useful life prediction

Zhixiong Li et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2019)

Article Engineering, Industrial

Gated recurrent unit based recurrent neural network for remaining useful life prediction of nonlinear deterioration process

Chen Jinglong et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2019)

Article Automation & Control Systems

Ridge Fuzzy Regression Model

Seung Hoe Choi et al.

INTERNATIONAL JOURNAL OF FUZZY SYSTEMS (2019)

Article Mathematics, Applied

A hybrid ARIMA-SVM model for the study of the remaining useful life of aircraft engines

Celestino Ordonez et al.

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS (2019)

Article Engineering, Mechanical

Degradation Modeling and Remaining Useful Life Prediction of Aircraft Engines Using Ensemble Learning

Zhixiong Li et al.

JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME (2019)

Article Computer Science, Information Systems

A Directed Acyclic Graph Network Combined With CNN and LSTM for Remaining Useful Life Prediction

Jialin Li et al.

IEEE ACCESS (2019)

Review Engineering, Mechanical

Machinery health prognostics: A systematic review from data acquisition to RUL prediction

Yaguo Lei et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)

Article Computer Science, Artificial Intelligence

Remaining useful life estimation of engineered systems using vanilla LSTM neural networks

Yuting Wu et al.

NEUROCOMPUTING (2018)

Article Engineering, Industrial

Remaining useful life estimation in prognostics using deep convolution neural networks

Xiang Li et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2018)

Article Chemistry, Multidisciplinary

Transfer Learning with Deep Recurrent Neural Networks for Remaining Useful Life Estimation

Ansi Zhang et al.

APPLIED SCIENCES-BASEL (2018)

Article Engineering, Industrial

Remaining useful life prediction of aircraft engine based on degradation pattern learning

Zeqi Zhao et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2017)

Article Computer Science, Artificial Intelligence

Multiobjective Deep Belief Networks Ensemble for Remaining Useful Life Estimation in Prognostics

Chong Zhang et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2017)

Article Computer Science, Hardware & Architecture

Online Performance Assessment Method for a Model-Based Prognostic Approach

Yang Hu et al.

IEEE TRANSACTIONS ON RELIABILITY (2016)

Review Thermodynamics

A review of physics-based models in prognostics: Application to gears and bearings of rotating machinery

Adrian Cubillo et al.

ADVANCES IN MECHANICAL ENGINEERING (2016)

Article Computer Science, Hardware & Architecture

A Kalman Filter-Based Ensemble Approach With Application to Turbine Creep Prognostics

Piero Baraldi et al.

IEEE TRANSACTIONS ON RELIABILITY (2012)

Review Management

Remaining useful life estimation - A review on the statistical data driven approaches

Xiao-Sheng Si et al.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2011)

Article Multidisciplinary Sciences

Reducing the dimensionality of data with neural networks

G. E. Hinton et al.

SCIENCE (2006)