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Zhongxiao Peng
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Cited by
Year
An integrated approach to fault diagnosis of machinery using wear debris and vibration analysis
Z Peng, N Kessissoglou
Wear 255 (7-12), 1221-1232, 2003
2522003
Machine-learning assisted laser powder bed fusion process optimization for AlSi10Mg: New microstructure description indices and fracture mechanisms
Q Liu, H Wu, MJ Paul, P He, Z Peng, B Gludovatz, JJ Kruzic, CH Wang, ...
Acta Materialia 201, 316-328, 2020
2162020
Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks
J Shi, D Peng, Z Peng, Z Zhang, K Goebel, D Wu
Mechanical Systems and Signal Processing 162, 107996, 2022
1952022
A study of the effect of contaminant particles in lubricants using wear debris and vibration condition monitoring techniques
Z Peng, NJ Kessissoglou, M Cox
Wear 258 (11-12), 1651-1662, 2005
1932005
Blind vibration component separation and nonlinear feature extraction applied to the nonstationary vibration signals for the gearbox multi-fault diagnosis
Z Li, X Yan, Z Tian, C Yuan, Z Peng, L Li
Measurement 46 (1), 259-271, 2013
1832013
Expert system development for vibration analysis in machine condition monitoring
S Ebersbach, Z Peng
Expert systems with applications 34 (1), 291-299, 2008
1802008
The investigation of the condition and faults of a spur gearbox using vibration and wear debris analysis techniques
S Ebersbach, Z Peng, NJ Kessissoglou
Wear 260 (1-2), 16-24, 2006
1802006
Virtual prototype and experimental research on gear multi-fault diagnosis using wavelet-autoregressive model and principal component analysis method
Z Li, X Yan, C Yuan, Z Peng, L Li
Mechanical Systems and Signal Processing 25 (7), 2589-2607, 2011
1762011
The use of the fractal description to characterize engineering surfaces and wear particles
CQ Yuan, J Li, XP Yan, Z Peng
Wear 255 (1-6), 315-326, 2003
1762003
Wear performance of UHMWPE and reinforced UHMWPE composites in arthroplasty applications: a review
JC Baena, J Wu, Z Peng
Lubricants 3 (2), 413-436, 2015
1722015
Multi-dimensional variational mode decomposition for bearing-crack detection in wind turbines with large driving-speed variations
Z Li, Y Jiang, Q Guo, C Hu, Z Peng
Renewable Energy 116, 55-73, 2018
1632018
Vibration-based anomaly detection using LSTM/SVM approaches
K Vos, Z Peng, C Jenkins, MR Shahriar, P Borghesani, W Wang
Mechanical Systems and Signal Processing 169, 108752, 2022
1562022
Development of a gear vibration indicator and its application in gear wear monitoring
C Hu, WA Smith, RB Randall, Z Peng
Mechanical Systems and Signal Processing 76, 319-336, 2016
1552016
Recent progress on decoupling diagnosis of hybrid failures in gear transmission systems using vibration sensor signal: A review
Z Li, Y Jiang, C Hu, Z Peng
Measurement 90, 4-19, 2016
1532016
Vibration-based updating of wear prediction for spur gears
K Feng, P Borghesani, WA Smith, RB Randall, ZY Chin, J Ren, Z Peng
Wear 426, 1410-1415, 2019
1462019
Optimal demodulation-band selection for envelope-based diagnostics: A comparative study of traditional and novel tools
WA Smith, P Borghesani, Q Ni, K Wang, Z Peng
Mechanical Systems and Signal Processing 134, 106303, 2019
1372019
An RFID-based remote monitoring system for enterprise internal production management
S Zhou, W Ling, Z Peng
The International Journal of Advanced Manufacturing Technology 33, 837-844, 2007
1372007
Use of cyclostationary properties of vibration signals to identify gear wear mechanisms and track wear evolution
K Feng, WA Smith, P Borghesani, RB Randall, Z Peng
Mechanical Systems and Signal Processing 150, 107258, 2021
1282021
Progress and trend of sensor technology for on-line oil monitoring
TH Wu, HK Wu, Y Du, ZX Peng
Science China Technological Sciences 56, 2914-2926, 2013
1272013
Wear particle classification in a fuzzy grey system
Z Peng, TB Kirk
Wear 225, 1238-1247, 1999
1231999
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