摘要
为准确诊断离心泵的振动故障,提出了基于提升小波包和相关向量机的离心泵振动故障诊断方法。首先通过提升小波包方法快速提取各状态振动信号的分解系数能量、时域统计参数作为特征量。针对支持向量机稀疏性不高而导致诊断速度慢的问题,利用相关向量机实现分类诊断。研究结果表明,该方法能够有效地诊断离心泵的振动故障,诊断率达95.5%;与其它算法相比,测试时间短,只有0.022 s,更适合在线诊断。
To accurately diagnose the vibration fault of a centrifugal pump,presented was a method for diagnosing the vibration fault of a centrifugal pump based on a lifting wavelet package and a relevant vector mahine.Firstly,the lifting wavelet method was used to quickly extract the decomposition coefficient energy and time-domain statistical parameters of vibration signals in various states to serve as the characteristic variables.In the light of the problem of a low speed in diagnosis due to a low sparsity of the supporting vector machine,a relevant vector machine can be utilized to accomplish the classification diagnosis.The research results show that the method in question can effectively diagnose any vibration fault of a centrifugal pump with its diagnostic rate being as high as 95.5%.Compared with other algorithms,the method under discussion takes a short time for testing and needs only 0.022 seconds,thus more suitable for on-line diagnosis.
出处
《热能动力工程》
CAS
CSCD
北大核心
2011年第6期738-742,777-778,共5页
Journal of Engineering for Thermal Energy and Power
基金
吉林省教育厅基金资助项目(2007047)
关键词
离心泵
故障诊断
提升小波包
相关向量机
centrifugal pump,fault diagnosis,lifting wavelet package,relevant vector machine