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【正文】 第 2 部分中介紹了關(guān)于 瞬變模型和參數(shù)辨識的基本理論背景。然而，在旋轉(zhuǎn)的構(gòu)件局部故障會導(dǎo)致周期性復(fù)雜瞬變，這可能與拉普拉斯小波不吻合，因此 LWCF不適合所有在局部故障場合的瞬變模型。 小波變換在機械故障診斷中的應(yīng)用已經(jīng)有十年歷史。雖然 ICA 在模擬信號的盲分離中是有 效的，但是，由于復(fù)雜的原信號，并且信號在機械系統(tǒng)中的傳輸路徑是復(fù)雜多變的再加上噪聲污染，使得 ICA在機械故障診斷中的有效應(yīng)用仍處于發(fā)展初期。 為了提取或分析振動信號的特征，尤其是瞬時的，在旋轉(zhuǎn)機器診斷文獻中不同的 技術(shù)已經(jīng)提出，如經(jīng)驗?zāi)Ｊ椒纸? (EMD)、 獨立成分分析 (ICA)、 時間頻率表示（ TFR) 、小波變換、匹配追蹤 (MP) 等。這項研究 提出對于旋轉(zhuǎn)機械故障診斷的局部故障檢測通過瞬態(tài)建模和參數(shù)檢測是一種 有效的方法。 however, the excessive putational cost limits its engineering applications. Correlation filtering, enlightened from matching pursuit, was introduced based on Laplace wavelet and applied to identify the parameters of transient by calculating the maximal correlation value, including the modal parameters identification of a flutter for aerodynamic and structural testing , the natural frequency identification of a hydro generator shaft and the wear fault diagnosis of the intake valve of an internal bustion engine , detection the position and the depth for rotor crack .Correlation filtering, enlightened from matching pursuit, was introduced based on Laplace wavelet and applied to identify the parameters of transient by calculating the maximal correlation value, including the modal parameters identification of a flutter for aerodynamic and structural testing , the natural frequency identification of a hydro generator shaft and the wear fault 4 diagnosis of the intake valve of an internal bustion engine , detection the position and the depth for rotor crack . Laplace wavelet correlation filtering (LWCF), which in essence used only Laplace wavelet as the transient model and identified the parameters by correlation filtering, is effective in detecting single transient. However, localized faults in rotating ponents tend to result in periodic multiple transients, which may not be similar with Laplace wavelet, LWCF is thus not suitable for all transient models in any localized fault occasions. In this paper, considering periodic multiple transients, we propose a new technique, as an extension of LWCF but not limited to Laplace wavelet, incorporating transient modeling and parameter identification for rotating machine fault diagnosis. Firstly, transient model is built to simulate a single transient and the parameters of model are identified. Then the identified transient model and its parameters are used to construct periodic multitransient
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