Fault Diagnosis for Industrial Robots Based on Informer
Author:
Affiliation:
1. Guangdong University of Technology,Guangdong Provincial Key Laboratory of Cyber-Physical System,Guangzhou,China
2. School of Aerospace, Transport and Manufacturing, Cranfield University,Welding and additive manufacturing Centre,Cranfield,UK
Funder
Natural Science Foundation of Guangdong Province
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10275139/10275143/10275280.pdf?arnumber=10275280
Reference15 articles.
1. Bearing fault diagnosis based on vibro-acoustic data fusion and 1D-CNN network
2. Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
3. Sequential Fault Diagnosis Based on LSTM Neural Network
4. An Intelligent Fault Diagnosis Method Using GRU Neural Network towards Sequential Data in Dynamic Processes
5. Study on Model-Based Fault Detection and Diagnosis for Mobile Robot: Fault diagnosis of internal sensor and robot-localization;hashimoto;The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2003,2003
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