A Sensor Fault Identification Method Based on Adaptive Particle Swarm Optimization Support Vector Machine-Reference-Cited by-同舟云学术

A Sensor Fault Identification Method Based on Adaptive Particle Swarm Optimization Support Vector Machine

Published:2022-09-18 Issue: Volume: Page:749-759
ISSN:2211-0984
Container-title:Proceedings of IncoME-VI and TEPEN 2021
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Author:

Cheng Xuezhen,Wang Dafei,Xu Chuannuo,Li Jiming

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-99075-6_60

Reference10 articles.

1. Liu, X.L., Zhao, Y., Wang, W.J., Ma, S.X., Zhuang, J.: Photovoltaic self-powered gas sensing: a review. IEEE Sens. J. 21(5), 5628–5644 (2021)

2. Zhou, D.H., Zhao, Y.H., Wang, Z.D., He, X., Gao, M.: Review on diagnosis techniques for intermittent faults in dynamic systems. IEEE Trans. Industr. Electron. 67(3), 2337–2347 (2020)

3. Lu, N.N., Xiao, H.H., Sun, Y.J., Han, M., Wang, Y.F.: A new method for intelligent fault diagnosis of machines based on unsupervised domain adaptation. Neurocomputing 427, 96–109 (2021)

4. Qian, J.G.: Diagnosis of machinery fault by time-domain parameters. Coal Mine Mach. 27(09), 192–193 (2006)

5. Cheng, Z, Zhang, J., Lv, Y.L., Xu, H.W.: Wafer yield improvement based on enhanced particle swarm optimization. Comput. Integrat. Manuf. Syst. 1–17 (2021)

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