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Zhe Li
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Intelligent predictive maintenance for fault diagnosis and prognosis in machine centers: Industry 4.0 scenario
Z Li, Y Wang, KS Wang
Advances in Manufacturing 5, 377-387, 2017
1992017
A deep learning approach for anomaly detection based on SAE and LSTM in mechanical equipment
Z Li, J Li, Y Wang, K Wang
The International Journal of Advanced Manufacturing Technology 103, 499-510, 2019
812019
Industry 4.0-potentials for predictive maintenance
Z Li, K Wang, Y He
6th International Workshop of Advanced Manufacturing and Automation, 42-46, 2016
632016
A deep learning driven method for fault classification and degradation assessment in mechanical equipment
Z Li, Y Wang, K Wang
Computers in industry 104, 1-10, 2019
522019
A data-driven method based on deep belief networks for backlash error prediction in machining centers
Z Li, Y Wang, K Wang
Journal of Intelligent Manufacturing 31, 1693-1705, 2020
502020
Interpretation and compensation of backlash error data in machine centers for intelligent predictive maintenance using ANNs
KS Wang, Z Li, J Braaten, Q Yu
Advances in Manufacturing 3, 97-104, 2015
382015
Smart Maintenance in Asset Management–Application with Deep Learning
H Rødseth, RJ Eleftheriadis, Z Li, J Li
Advanced Manufacturing and Automation IX 9th, 608-615, 2020
62020
A review on data-driven predictive maintenance approach for hydro turbines/generators
S Wang, K Wang, Z Li
6th International Workshop of Advanced Manufacturing and Automation, 30-35, 2016
42016
Knowledge discovery and anomaly identification for low correlation industry data
Z Li, J Li
Advanced Manufacturing and Automation IX 9th, 195-202, 2020
12020
Fault classification and degradation assessment based on wavelet packet decomposition for rotary machinery
Z Li, VGB Pedersen, K Wang, Y He
Advanced Manufacturing and Automation VII 7, 509-516, 2018
12018
Deep learning driven approaches for predictive maintenance: A framework of intelligent fault diagnosis and prognosis in the industry 4.0 era
Z Li
NTNU, 2018
12018
HDPS-BPSO based predictive maintenance scheduling for backlash error compensation in a machining center
Z Li, Y Wang, K Wang, J Li
Advanced Manufacturing and Automation VIII 8, 71-77, 2019
2019
Applying Radial Basis Function Networks to Fault Diagnosis of Motorized Spindle
Z Li, K Wang, J Yang, Y Stefanov
6th International Workshop of Advanced Manufacturing and Automation, 237-240, 2016
2016
Comparing different methods of fault classification in centrifugal pumps
Z Li, K Wang
WIT Transactions on Engineering Sciences 113, 217-224, 2016
2016
Research on fault diagnosis and prognosis for machine centers
Z Li, K Wang
WIT Transactions on Engineering Sciences 113, 225-232, 2016
2016
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Artikler 1–15