摘要
往复泵的正常工作是确保煤矿生产顺利进行的关键,由于工作环境恶劣,往复泵的故障诊断是非常重要的,因此,深入地研究了小波包分析和概率神经网络在往复泵故障诊断中的应用。分析了基于小波包的往复泵故障提取机理,设计了基于小波包分析的往复泵故障特征提取流程;构建了基于概率神经网络的往复泵的故障诊断模型,设计了概率神经网络的基本结构。对往复泵进行了故障诊断分析,仿真结果表明小波包和概率神经网络能够准确地获得故障诊断的类型。
The proper working of the reciprocating pump can ensure the coal mine produce smoothly, the fault diagnosis of reciprocating pump is very important because the working environment is poor, therefore the application of wavelet package analysis and probability neutral network on it is studied in depth. The extracting mechanism of faults based on wavelet package is analyzed, and the corresponding extracting program is designed. The fault diagnosis model of reciprocating pump based on probability neutral network is constructed, and basic frame of it is designed. The fault diagnosis of reciprocating pump is carried out, and results show that the wavelet package analysis and probability neutral network can obtain the fault type correctly.
出处
《煤矿机械》
北大核心
2013年第12期256-258,共3页
Coal Mine Machinery
关键词
小波包分析
概率神经网络
往复泵
wavelet package analysis
probability neutral network
reciprocating pump
