摘要
根据Bently实验台所采集的不平衡、不对中、碰摩、松动4种典型汽轮机转子振动故障信号,运用小波包分析方法对其进行分析并提取故障特征。将提取的故障特征作为D-S证据理论的识别框架,利用信息融合技术对汽轮机转子振动故障进行诊断。诊断结果表明:基于小波包分析和信息融合技术的故障诊断方法,能提高故障诊断的准确性。
According to the four typical fault signals of turbine vibration including ： mass unbalance, misalignment, rubbing and loosing from the Bently experiment table, analysis and symptom extraction are carried out by wavelet packet analysis. The fault symptom parameters extracted by wavelet packet compose the framework of the D-S evidence theory; get turbine rotor vibration faults types by the information fusion technology. The results of diagnosis indicate that the faults diagnosis method based on wavelet analysis and information fusion technology can improve the accuracy of fault diagnosis.
出处
《汽轮机技术》
北大核心
2010年第4期300-302,共3页
Turbine Technology
