Design of automatic identification algorithm for double-feature fault signal waveform of power equipment

• Main Authors: Tang, Huidong, Li, Duo, Lei, Wendong, Meng, Jinpeng
• Format: Conference Proceeding
• Language: English
• Published: SPIE 09.01.2024
• ISBN: 9781510672444; 1510672443
• ISSN: 0277-786X
• DOI: 10.1117/12.3014372

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.