Research on voice print feature extraction technology of GIS equipment based on speech signal processing

Xiaoliang Zhuang; Qiankun Li; Yanhui Shi; Xueming Huang; Chenjiarui Gong; Xiangdong Qi

doi:10.1117/12.3006984

10 October 2023 Research on voice print feature extraction technology of GIS equipment based on speech signal processing

Xiaoliang Zhuang, Qiankun Li, Yanhui Shi, Xueming Huang, Chenjiarui Gong, Xiangdong Qi

Author Affiliations +

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127990M (2023) https://doi.org/10.1117/12.3006984
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

The normal and stable operation of GIS equipment is related to the safety and reliable operation of the power system. The mechanical sound signal generated during the operation of GIS equipment contains a very rich information on the operation status of GIS equipment. Therefore, in order to accurately monitor the operation status of GIS equipment, based on the artificial intelligence voice print recognition technology, the sound signal feature extraction method under different operating status of GIS equipment is studied, so as to support the fault monitoring and judgment of GIS equipment. This paper proposes the voice print feature extraction method of GIS equipment based on wavelet packet decomposition. The experiment shows that the method can accurately extract the voice print features of GIS equipment and provide support for the next step of fault identification of GIS equipment.

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

Citation Download Citation

Xiaoliang Zhuang, Qiankun Li, Yanhui Shi, Xueming Huang, Chenjiarui Gong, and Xiangdong Qi "Research on voice print feature extraction technology of GIS equipment based on speech signal processing", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127990M (10 October 2023); https://doi.org/10.1117/12.3006984

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