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

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 ${t}$ -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.