Fault diagnosis algorithm of medium and low-voltage switches based on improved immune learning algorithm

Min Zhang; Jian Fang; Hongbin Wang; Xiang Lin; Yan Tian

doi:10.1117/12.3005060

25 September 2023 Fault diagnosis algorithm of medium and low-voltage switches based on improved immune learning algorithm

Min Zhang, Jian Fang, Hongbin Wang, Xiang Lin, Yan Tian

Author Affiliations +

Proceedings Volume 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023); 127885O (2023) https://doi.org/10.1117/12.3005060
Event: Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 2023, Kuala Lumpur, Malaysia

Abstract

An improved immune learning algorithm (IILA) is proposed. The algorithm uses the input data as the antigen and the center of the hidden layer in the network as the antibody. A diverse set of antibody memories obtained through the immune algorithm equals the center for the purpose of shunning the difficult problem of discovering the center. Afterward, the weight is determined via gradient descent, and fault diagnosis of the medium and low-pressure switches is conducted through the trained network. The simulation results demonstrate that such a method is conducive to the analysis of mechanical vibration signals of medium and low-voltage switches.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Min Zhang, Jian Fang, Hongbin Wang, Xiang Lin, and Yan Tian "Fault diagnosis algorithm of medium and low-voltage switches based on improved immune learning algorithm", Proc. SPIE 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 127885O (25 September 2023); https://doi.org/10.1117/12.3005060

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