摘要
传统变电设备故障在线检测方法检测过程比较单一,无法实现多故障点并行检测,为此提出基于人工智能的变电设备故障在线检测方法。采用人工智能方法中神经网络与模糊推理相结合方式对数据进行融合,生成变电设备故障在线检测器。将故障点数据进行去重处理,选择文本对去重后的数据实施补充,放入变电设备故障在线检测器中进行识别,识别数据与正常运行数据进行比对处理,确定故障点信息,传输至显示模块完成故障在线显示,实现变电设备故障在线检测。通过实验结果表明,提出的变电设备故障在线检测方法,能够对多点故障进行同时段故障检测,成功解决传统方法出现的问题。
The traditional online fault detection method for substation equipment has a single detection process,which cannot realize parallel detection of multiple fault points.Therefore,an online fault detection method for substation equipment based on artificial intelligence is proposed.combining neural network and fuzzy reasoning in artificial intelligence,data fusion is achieved,and on-line detectors for substation equipment faults are generated the fault point data is reprocessed.Selecting text to supplement,the data after de duplication,and putting it into on-line detector for identification,comparing identification data with the normal operation of the data processing,the fault point information is determined.Transfering it to the display module to complete the online fault,the online fault detection substation equipment is realized.The experimental results show that the proposed on-line fault detection method can detect multi-point fault at the same time and solve the problems of traditional methods successfully.
作者
佟忠正
孙旸子
TONG Zhongzheng;SUN Yangzi(Information Science&Technology of Guangdong Power Grid Co.,Ltd.,Yuexiu Guangzhou 510080,China;Guangdong Diankeyuan Energy Technology Co.,Ltd,,Yuexiu Guangzhou 510080,China)
出处
《自动化与仪器仪表》
2020年第6期172-175,共4页
Automation & Instrumentation
基金
基于物联网+的智能助手协同运维的信息机房创新技术研究与应用(No.GDKJXM20183896)。
关键词
人工智能
变电设备
在线检测
故障检测器
artificial intelligence
substation equipment
online detection
fault detector