Optical Characteristics and Fault Diagnosis of Partial Discharge in C4F7N/CO2 Gas Mixture and SF6 Based on Novel Multispectral Microarray Detection

• Published in: IEEE transactions on dielectrics and electrical insulation Vol. 29; no. 3; pp. 1079 - 1086
• Main Authors: Zang, Yiming, Qian, Yong, Zhou, Xiaoli, Niasar, Mohamad Ghaffarian, Sheng, Gehao, Jiang, Xiuchen
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Carbon dioxide; C₄F₇N/CO₂ gas mixture; Defects; Discharge; Fault diagnosis; Feature extraction; Gas mixtures; Gases; Insulation; Integrated optics; multispectral microarray detection; Optical attenuators; Optical buffering; optical characteristic; Optical filters; Optical properties; Optical sensors; partial discharge (PD); Partial discharges
• ISSN: 1070-9878; 1558-4135
• DOI: 10.1109/TDEI.2022.3168332

Optical partial discharge (PD) detection is an efficient means of diagnosing the insulation status of power equipment. C 4 F 7 N/CO 2 gas mixture is a very potential environmentally-friendly SF 6 substitute gas, and its PD optical characteristics need to be studied to guide the PD diagnosis of novel C 4 F 7 N/CO 2 equipment. Therefore, this article proposes a multispectral microarray detection technology, which can achieve high-sensitivity detection and PD diagnosis by simultaneously collecting the spectral characteristics of multiple bands. By setting up an experimental platform, the PD experiments of four typical defects in the C 4 F 7 N/CO 2 gas mixture with five different proportions and pure SF 6 are carried out. Based on the analysis of PD multispectral features, the correlation between different gases and the difference between different defects are obtained. Finally, by combining multispectral detection with a <inline-formula> <tex-math notation="LaTeX">{t} </tex-math></inline-formula>-distributed stochastic neighbor embedding (T-SNE) feature extraction algorithm, a PD diagnosis method that can adapt to both C 4 F 7 N/CO 2 gas mixture and SF 6 is proposed, which provides a reference for the PD detection of novel C 4 F 7 N/CO 2 equipment application.