TY - JOUR
T1 - Optical Characteristics and Fault Diagnosis of Partial Discharge in C4F7N/CO2 Gas mixture and SF6 Based on Novel Multispectral Microarray Detection
AU - Zang, Yiming
AU - Qian, Yong
AU - Zhou, Xiaoli
AU - Niasar, Mohamad Ghaffarian
AU - Sheng, Gehao
AU - Jiang, Xiuchen
PY - 2022
Y1 - 2022
N2 - Optical partial discharge (PD) detection is an efficient means of diagnosing the insulation status of power equipment. C4F7N/CO2 gas mixture is a very potential environmentally-friendly SF6 substitute gas, and its PD optical characteristics need to be studied to guide the PD diagnosis of novel C4F7N/CO2 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 C4F7N/CO2 gas mixture with five different proportions and pure SF6 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 C4F7N/CO2 gas mixture and SF6 is proposed, which provides a reference for the PD detection of novel C4F7N/CO2 equipment application.
AB - Optical partial discharge (PD) detection is an efficient means of diagnosing the insulation status of power equipment. C4F7N/CO2 gas mixture is a very potential environmentally-friendly SF6 substitute gas, and its PD optical characteristics need to be studied to guide the PD diagnosis of novel C4F7N/CO2 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 C4F7N/CO2 gas mixture with five different proportions and pure SF6 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 C4F7N/CO2 gas mixture and SF6 is proposed, which provides a reference for the PD detection of novel C4F7N/CO2 equipment application.
KW - C4F7N/CO2 gas mixture
KW - multispectral microarray detection
KW - optical characteristic
KW - Optical sensors
KW - partial discharge
KW - Partial discharges
UR - http://www.scopus.com/inward/record.url?scp=85128607665&partnerID=8YFLogxK
U2 - 10.1109/TDEI.2022.3168332
DO - 10.1109/TDEI.2022.3168332
M3 - Article
AN - SCOPUS:85128607665
SN - 1070-9878
VL - 29
SP - 1079
EP - 1086
JO - IEEE Transactions on Dielectrics and Electrical Insulation
JF - IEEE Transactions on Dielectrics and Electrical Insulation
IS - 3
M1 - 9760393
ER -