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基于聲強(qiáng)信號分析和組合神經(jīng)網(wǎng)絡(luò)的發(fā)動(dòng)機(jī)故障診斷
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    摘要:

    建立了一個(gè)基于聲強(qiáng)信號分析和組合神經(jīng)網(wǎng)絡(luò)的發(fā)動(dòng)機(jī)故障診斷模型。該模型首先運(yùn)用小波理論分析各類故障下發(fā)動(dòng)機(jī)產(chǎn)生的聲強(qiáng)信號，獲取反映發(fā)動(dòng)機(jī)工作狀態(tài)的頻帶特征向量，然后將特征向量用于組合神經(jīng)網(wǎng)絡(luò)訓(xùn)練，進(jìn)行故障模式識別。通過對3Y豐田2.0發(fā)動(dòng)機(jī)的試驗(yàn)數(shù)據(jù)分析表明，這種模型可有效提高故障診斷的效率和準(zhǔn)確率。

    Abstract:

    A new engine fault diagnosis model based on sound intensity signal and BP neural network integration was proposed. Firstly, the sound intensity signals were decomposed and recomposed by using wavelet packets. Afterwards, the signal energy values were extracted from each frequency band, and were used as input features into the BP neural network integration for fault pattern recognition. It has been testified by the experimentation of the 3Y Toyota 2.0 engine and the results showed that it could increase the efficiency and accuracy of the system.

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李增芳,何勇,徐高歡.基于聲強(qiáng)信號分析和組合神經(jīng)網(wǎng)絡(luò)的發(fā)動(dòng)機(jī)故障診斷[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2008,39(12):170-173.[J]. Transactions of the Chinese Society for Agricultural Machinery,2008,39(12):170-173.

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