模糊Petri网在风电机组故障诊断中的应用  

Fault diagnosis of wind power generator set based on fuzzy Petri net

作　　者：黄敏[1] 张芳[1] 

机构地区：[1]长沙理工大学计算机与通信工程学院,长沙410014

出　　处：《计算机工程与应用》2012年第27期206-210,共5页Computer Engineering and Applications

基　　金：湖南省科技厅计划基金项目(No.2011GK3113)

摘　　要：针对风力发电机组故障诊断建模中动态行为较难描述的问题,结合模糊Petri网的图形描述能力及模糊推理性,提出故障诊断的模糊Petri网模型及其相应的故障诊断方法,根据故障发生的实际情况给出正反两种推理算法。用齿轮箱故障的实例加以验证,证明了该方法的正确性及在风电机组故障诊断中应用的可行性。In wind power generator set it is hard to show dynamic behaviors in fault diagnosis. Associating with fuzzy Petri net graphics describing ability and Fuzzy inferential, the FPN models of fault diagnosis and the corre- sponding algorithm are proposed, according to the actual situation of failure by both forward and backward reason- ing algorithm. The instance of gear box＇ s breakdown is used to verify the algorithm. Practice has proved that this method reduces the failure diagnosis rate and missed diagnosis rate. And the difficult problem of fault diagnosis and prediction for wind power generator set under complex environment is solved.

关 键 词：风力发电机组 故障诊断 模糊PETRI网模型 正反推理 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]