Harmonic reducer in-situ fault diagnosis for industrial robots based on deep learning-Reference-Cited by-同舟云学术

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Harmonic reducer in-situ fault diagnosis for industrial robots based on deep learning

Published:2022-08-04 Issue:9 Volume:65 Page:2116-2126
ISSN:1674-7321
Container-title:Science China Technological Sciences
language:en
Short-container-title:Sci. China Technol. Sci.

Author:

Zhou Xing,Zhou HuiCheng,He YiMing,Huang ShiFeng,Zhu ZhiHong,Chen JiHong

Publisher

Springer Science and Business Media LLC

Subject

General Engineering,General Materials Science

Link

https://link.springer.com/content/pdf/10.1007/s11431-022-2129-9.pdf

Reference39 articles.

1. Hwang I, Kim S, Kim Y, et al. A survey of fault detection, isolation, and reconfiguration methods. IEEE Trans Contr Syst Technol, 2009, 18: 636–653

2. Abid A, Khan M T, Iqbal J. A review on fault detection and diagnosis techniques: Basics and beyond. Artif Intell Rev, 2021, 54: 3639–3664

3. Khalastchi E, Kalech M. On fault detection and diagnosis in robotic systems. ACM Comput Surv, 2018, 51: 1–24

4. McIntyre M L, Dixon W E, Dawson D M, et al. Fault identification for robot manipulators. IEEE Trans Robot, 2005, 21: 1028–1034

5. Xiao B, Yin S. An intelligent actuator fault reconstruction scheme for robotic manipulators. IEEE Trans Cybern, 2017, 48: 639–647

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