TY - GEN
T1 - Remote Fault Diagnosis and Intelligent Decision-making System for Condenser Based on Pattern Recognition and Reliability Evaluation
AU - Li, Chenlong
AU - Xia, Chao
AU - Ma, Xiaoguang
AU - Mei, Rui
AU - Li, Zhiqiang
AU - Sun, Chuan
AU - Gao, Lei
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - Paper presented a common fault diagnosis method based on pattern recognition and reliability evaluation, and made intelligent decision according to the diagnosis results. Firstly, the fault model library of the phase modulator was established, and the instantaneous value and the change rate of the sampled signal were calculated by using the time domain and frequency domain signal analysis methods to determine the type and reliability of the fault. Then, through the comparative analysis of historical data and relevant standards, the severity of the fault was determined, and the severity and trend of the fault of the condenser were obtained. Finally, according to the fault and severity of the unit, visual display and intelligent decision-making were carried out and timely pushed. The intelligent decision-making system established in this paper could help operators make scientific operation and maintenance decisions, reduce the probability of equipment failure, improve the service life of the condenser, and provide the strongest technical support for improving power transmission and security and stability of the power grid.
AB - Paper presented a common fault diagnosis method based on pattern recognition and reliability evaluation, and made intelligent decision according to the diagnosis results. Firstly, the fault model library of the phase modulator was established, and the instantaneous value and the change rate of the sampled signal were calculated by using the time domain and frequency domain signal analysis methods to determine the type and reliability of the fault. Then, through the comparative analysis of historical data and relevant standards, the severity of the fault was determined, and the severity and trend of the fault of the condenser were obtained. Finally, according to the fault and severity of the unit, visual display and intelligent decision-making were carried out and timely pushed. The intelligent decision-making system established in this paper could help operators make scientific operation and maintenance decisions, reduce the probability of equipment failure, improve the service life of the condenser, and provide the strongest technical support for improving power transmission and security and stability of the power grid.
KW - Condenser
KW - fault diagnosis
KW - intelligent decision
KW - pattern recognition
KW - reliability evaluation
UR - https://www.scopus.com/pages/publications/85084050853
U2 - 10.1109/EI247390.2019.9061863
DO - 10.1109/EI247390.2019.9061863
M3 - 会议稿件
AN - SCOPUS:85084050853
T3 - 2019 3rd IEEE Conference on Energy Internet and Energy System Integration: Ubiquitous Energy Network Connecting Everything, EI2 2019
SP - 2212
EP - 2217
BT - 2019 3rd IEEE Conference on Energy Internet and Energy System Integration
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE Conference on Energy Internet and Energy System Integration, EI2 2019
Y2 - 8 November 2019 through 10 November 2019
ER -