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形態(tài)小波降噪方法在齒輪故障特征提取中的應(yīng)
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of Morphological Wavelet De-noising in Extracting Gear Fault Feature
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    摘要:

    針對齒輪故障特征往往被強背景噪聲淹沒的問題，采用形態(tài)小波降噪方法來提取故障特征,。形態(tài)小波降噪方法適合于對具有一定形態(tài)特征的齒輪故障信號進行特征提取,。首先采用形態(tài)小波對信號進行分解,，然后對各層的細(xì)節(jié)系數(shù)進行軟閾值降噪處理,，最后根據(jù)處理得到的小波系數(shù)重構(gòu)信號以提取故障特征,。仿真與實例證明,，該方法可有效地提取隱含在噪聲中的齒輪故障特征,。形態(tài)小波降噪算法只涉及加減和極大,、極小運算,，運算簡單且執(zhí)行高效，適合于齒輪故障的在線監(jiān)測與診斷,。

    Abstract:

    Fault feature is always hidden by strong noise background in gear fault signal. Based on morphological wavelet de-noising, a novel method was proposed to extract gear fault feature. Morphological wavelet de-noising has a good performance in extracting morphological feature in signal. Firstly, the signal was decomposed by morphological wavelet. Secondly, detail coefficient in each level was processed using soft threshold de-noising. Finally, fault feature was extracted by reconstructing original signal. Simulation and experiment results showed that this method is effective in gear feature extraction. Morphological wavelet de-noising algorithm includes addition, subtraction, maximum and minimum operations, and does not involve multiplication and division. It is suitable for on-line monitor and gear fault diagnosis.

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沈路,周曉軍,劉莉,楊富春.形態(tài)小波降噪方法在齒輪故障特征提取中的應(yīng)[J].農(nóng)業(yè)機械學(xué)報,2010,41(4):217-221. of Morphological Wavelet De-noising in Extracting Gear Fault Feature[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(4):217-221.

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