摘要
为有效提升输变电设备一体化智能检测系统的效率和准确性,提出一种基于人工智能(Artificial Intelligence,AI)技术Markov分析法和贝叶斯网络(Bayesian Network,BN)模型的Markov-BN一体化智能故障预测系统。利用BN模型,训练学习一体化智能故障预测系统中采集的实时信号,并且将该故障预测系统得出的故障诊断权值与输变电设备故障性能做对比,以此确定输变电设备的运行状态,实现智能运维系统快速诊断效果。以输变电设备绝缘子故障预测诊断为例,验证了该系统的有效性。
In order to effectively improve the efficiency and accuracy of the integrated intelligent detection system for transmission and substation equipment,a Markov-BN integrated intelligent fault prediction system based on the Artificial Intelligence(AI)technology Markov analysis and Bayesian Network(BN)model is proposed.Using the BN model,the real-time signals collected in the integrated intelligent fault prediction system are trained and learned,and the fault diagnostic weights derived from this fault prediction system are compared with the fault performance of transmission and substation equipment,so as to determine the operational status of transmission and substation equipment and realize the rapid diagnostic effect of intelligent operation and maintenance system.Taking the insulator fault prediction diagnosis of transmission and substation equipment as an example,the effectiveness of the system is verified.
作者
张蔚元
ZHANG Weiyuan(State Grid Shandong Electric Extrahigh Voltage Company,Jinan 250000,China)
出处
《通信电源技术》
2023年第21期275-277,共3页
Telecom Power Technology
