Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification C Lu, ZY Wang, WL Qin, J Ma Signal Processing 130, 377-388, 2017 | 825 | 2017 |
Intelligent fault diagnosis of rolling bearing using hierarchical convolutional network based health state classification C Lu, Z Wang, B Zhou Advanced Engineering Informatics 32, 139-151, 2017 | 423 | 2017 |
Study on prediction of surface quality in machining process C Lu Journal of materials processing technology 205 (1-3), 439-450, 2008 | 280 | 2008 |
Rolling bearing fault diagnosis under variable conditions using LMD-SVD and extreme learning machine Y Tian, J Ma, C Lu, Z Wang Mechanism and Machine Theory 90, 175-186, 2015 | 243 | 2015 |
Intelligent fault diagnosis for rotating machinery using deep Q-network based health state classification: A deep reinforcement learning approach Y Ding, L Ma, J Ma, M Suo, L Tao, Y Cheng, C Lu Advanced Engineering Informatics 42, 100977, 2019 | 135 | 2019 |
A hybrid remaining useful life prognostic method for proton exchange membrane fuel cell Y Cheng, N Zerhouni, C Lu International Journal of Hydrogen Energy 43 (27), 12314-12327, 2018 | 135 | 2018 |
Fault diagnosis for rotating machinery: A method based on image processing C Lu, Y Wang, M Ragulskis, Y Cheng PloS one 11 (10), e0164111, 2016 | 121 | 2016 |
A review of stochastic battery models and health management L Tao, J Ma, Y Cheng, A Noktehdan, J Chong, C Lu Renewable and Sustainable Energy Reviews 80, 716-732, 2017 | 111 | 2017 |
Fault diagnosis for rotary machinery with selective ensemble neural networks ZY Wang, C Lu, B Zhou Mechanical Systems and Signal Processing 113, 112-130, 2018 | 102 | 2018 |
Self-adaptive bearing fault diagnosis based on permutation entropy and manifold-based dynamic time warping Y Tian, Z Wang, C Lu Mechanical Systems and Signal Processing 114, 658-673, 2019 | 97 | 2019 |
Li-ion battery capacity estimation: A geometrical approach C Lu, L Tao, H Fan Journal of power sources 261, 141-147, 2014 | 91 | 2014 |
Rolling bearing fault diagnosis based on LCD–TEO and multifractal detrended fluctuation analysis H Liu, X Wang, C Lu Mechanical Systems and Signal Processing 60, 273-288, 2015 | 88 | 2015 |
A novel health indicator for PEMFC state of health estimation and remaining useful life prediction J Chen, D Zhou, C Lyu, C Lu International Journal of Hydrogen Energy 42 (31), 20230-20238, 2017 | 78 | 2017 |
A generative adversarial network-based intelligent fault diagnosis method for rotating machinery under small sample size conditions Y Ding, L Ma, J Ma, C Wang, C Lu IEEE Access 7, 149736-149749, 2019 | 77 | 2019 |
Fault diagnosis of gearbox using empirical mode decomposition and multi-fractal detrended cross-correlation analysis H Liu, J Zhang, Y Cheng, C Lu Journal of Sound and Vibration 385, 350-371, 2016 | 72 | 2016 |
A hybrid transfer learning scheme for remaining useful life prediction and cycle life test optimization of different formulation Li-ion power batteries J Ma, P Shang, X Zou, N Ma, Y Ding, J Sun, Y Cheng, L Tao, C Lu, Y Su, ... Applied Energy 282, 116167, 2021 | 70 | 2021 |
Residual lifetime prediction for lithium-ion battery based on functional principal component analysis and Bayesian approach Y Cheng, C Lu, T Li, L Tao Energy 90, 1983-1993, 2015 | 68 | 2015 |
An end-to-end framework for remaining useful life prediction of rolling bearing based on feature pre-extraction mechanism and deep adaptive transformer model X Su, H Liu, L Tao, C Lu, M Suo Computers & Industrial Engineering 161, 107531, 2021 | 67 | 2021 |
An integrated method based on CEEMD-SampEn and the correlation analysis algorithm for the fault diagnosis of a gearbox under different working conditions J Chen, D Zhou, C Lyu, C Lu Mechanical Systems and Signal Processing 113, 102-111, 2018 | 63 | 2018 |
Rolling Bearing Fault Diagnosis under Variable Conditions Using Hilbert‐Huang Transform and Singular Value Decomposition H Liu, X Wang, C Lu Mathematical Problems in Engineering 2014 (1), 765621, 2014 | 63 | 2014 |