摘要
超临界机组发电系统结构复杂且安全性能要求极高,故障诊断非常困难。结合模糊算法与DS证据理论,提出了一种新的故障诊断方法,从隶属度函数确定、模糊化处理、神经网络诊断,到运用DS证据理论进行数据融合,最终得出故障诊断结果。以某超临界机组发电系统的风机设备为例,应用该方法进行故障诊断,可快速、准确地找出故障概率较高的设备,针对故障及时给出建议并进行处理。
Since the supercritical generating system has complex structure and high requirements on safety performance,fault diagnosis is very difficult. Combining fuzzy theory and DS evidential theory,a new fault diagnosis method is proposed,whose process includes membership function determination,fuzzy processing,neural network diagnosis,data fusion with DS evidence theory and obtaining the final result. Taking the fan of a supercritical generating system as an example,this method can be used for fault diagnosis,finding the equipment with higher fault probability quickly and accurately and providing countermeasure according to the fault in time.
出处
《华电技术》
CAS
2018年第7期5-9,共5页
HUADIAN TECHNOLOGY
关键词
超临界机组
故障诊断
模糊算法
DS证据理论
数据融合
supercritical unit
fault diagnosis
fuzzy algorithm
DS evidential theory
data fusion
