Paper
9 January 2024 Design of automatic identification algorithm for double-feature fault signal waveform of power equipment
Huidong Tang, Duo Li, Wendong Lei, Jinpeng Meng
Author Affiliations +
Proceedings Volume 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023); 1296903 (2024) https://doi.org/10.1117/12.3014372
Event: International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023), 2023, Qingdao, China
Abstract
The conventional automatic identification algorithm of double-feature fault signal waveform of power equipment mainly uses ART (Adaptive Resonnance Theory) network for classification and discrimination, which is easily influenced by the identification mapping relationship, resulting in low correct identification rate of fault signal waveform. Therefore, it is necessary to design a brand-new automatic identification algorithm of double-feature fault signal waveform of power equipment. That is to say, the waveform characteristics of dual-feature fault signal of power equipment are extracted, and the optimization algorithm for automatic identification of dual-feature fault signal waveform of power equipment is generated, so that the automatic identification of fault signal waveform is realized. The experimental results show that the designed double-feature fault signal waveform automatic identification algorithm for power equipment has a high correct fault identification rate, which proves that the designed double-feature fault signal waveform automatic identification algorithm for power equipment has good identification effect, reliability and certain application value, and has made certain contributions to improving the operation safety of power equipment.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Huidong Tang, Duo Li, Wendong Lei, and Jinpeng Meng "Design of automatic identification algorithm for double-feature fault signal waveform of power equipment", Proc. SPIE 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023), 1296903 (9 January 2024); https://doi.org/10.1117/12.3014372
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KEYWORDS
Power supplies

Signal processing

Design and modelling

Detection and tracking algorithms

Sampling rates

Mathematical optimization

Reliability

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