本文關(guān)鍵詞：基于改進奇異譜分解的形態(tài)學(xué)解調(diào)方法及其在滾動軸承故障診斷中的應(yīng)用　出處：《機械工程學(xué)報》2017年07期 　論文類型：期刊論文

  更多相關(guān)文章： 奇異譜分解 端點效應(yīng) 形態(tài)學(xué)解調(diào) 滾動軸承 故障診斷

【摘要】：針對強背景噪聲及干擾源信號影響下滾動軸承故障特征難以檢測的問題,提出一種基于改進奇異譜分解的形態(tài)學(xué)解調(diào)方法用于軸承故障診斷。首先,為了克服奇異譜分析按經(jīng)驗性選取嵌入維數(shù)長度的缺陷,采用一種新的自適應(yīng)信號處理方法——奇異譜分解(Singular spectrum decomposition,SSD)進行振動信號分析,該方法通過構(gòu)建一個軌跡矩陣與自適應(yīng)選擇嵌入維數(shù)長度,將非平穩(wěn)信號從高頻至低頻依次劃分為若干個單分量信號。針對奇異譜分解在分量序列重構(gòu)過程中兩端數(shù)據(jù)會偏離實際數(shù)據(jù)值進而引起端點效應(yīng)現(xiàn)象的問題,提出運用特征波形匹配延拓法對奇異譜分解進行改進,提高其對振動信號的分解質(zhì)量,獲得一系列更接近實際曲線的單分量序列。為準確提取單分量中蘊含的有用故障特征信息,提出一種基于特征能量比自適應(yīng)確定結(jié)構(gòu)元素最佳尺度的自互補頂帽變換對單分量信號進行形態(tài)學(xué)解調(diào)。最后,分析解調(diào)結(jié)果的頻譜特征并提取突出頻率成分,實現(xiàn)軸承故障類型的準確判別。仿真和實測信號分析驗證了方法的有效性。
[Abstract]:In order to solve the problem that the fault characteristics of rolling bearing are difficult to detect under the influence of strong background noise and interference source signal, a morphological demodulation method based on improved singular spectrum decomposition is proposed for bearing fault diagnosis. In order to overcome the defect of selecting embedding dimension length by experience in singular spectrum analysis. A new adaptive signal processing method, singular spectrum decomposition (SSD), is used for vibration signal analysis. This method constructs a trajectory matrix and adaptively selects the embedding dimension length. The non-stationary signal is divided into several single-component signals from high frequency to low frequency. In order to solve the problem that the data at both ends of the singular spectrum decomposition will deviate from the actual data value in the process of component sequence reconstruction, the phenomenon of endpoint effect will be caused. The characteristic waveform matching continuation method is proposed to improve the decomposition quality of the vibration signal. A series of single component sequences, which are closer to the actual curve, are obtained to extract the useful fault feature information contained in the single component accurately. A self-complementary top-cap transform based on the adaptive determination of the optimal scale of structural elements is proposed to demodulate the single component signal. Finally, the spectrum features of the demodulation results are analyzed and the outburst frequency components are extracted. The validity of the method is verified by simulation and actual signal analysis.
【作者單位】： 東南大學(xué)機械工程學(xué)院;
【基金】：國家自然科學(xué)基金(51675098) 高等學(xué)校博士學(xué)科點專項科研基金(20130092110003)資助項目
【分類號】：TH133.33
【正文快照】： 0前言*滾動軸承是機械設(shè)備中的核心組件,在長期高速運轉(zhuǎn)、交變載荷等惡劣工況下,極易產(chǎn)生局部損傷并演化成晚期故障,影響著整個機械傳遞系統(tǒng)的工作性能。因此,針對軸承早期損傷階段進行有效檢測備受關(guān)注。而在實際工程中,軸承振動信號往往表現(xiàn)為周期非平穩(wěn)特性,其受到部件間多，

本文編號：1408541