Fault Detection for Motor Drive Control System of Industrial Robots Using CNN-LSTM-based Observers-Reference-Cited by-同舟云学术

Fault Detection for Motor Drive Control System of Industrial Robots Using CNN-LSTM-based Observers

Published:2023-06 Issue:2 Volume:7 Page:144-152
ISSN:2096-3564
Container-title:CES Transactions on Electrical Machines and Systems
language:
Short-container-title:Trans. Electr. Mach. Syst.

Author:

Wang Tao¹,Zhang Le¹,Wang Xuefei²

Affiliation:

1. School of Intelligent Equipment Engineering, Wuxi Taihu University,Jiangsu International Cooperation Laboratory of 6G Network and Big Data Intelligent Application,Wuxi,China,214064

2. School of Intelligent Equipment Engineering, Wuxi Taihu University,Wuxi,China,214064

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7873789/10172142/10032059.pdf?arnumber=10032059

Reference25 articles.

1. A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method

2. Deep learning and its applications to machine health monitoring

3. Rolling Bearing Initial Fault Detection Using Long Short-Term Memory Recurrent Network

4. Hybrid CNN-LSTM Model for Short-Term Individual Household Load Forecasting

5. A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load

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