發(fā)布時(shí)間：2018-01-11 07:03

  本文關(guān)鍵詞：基于改進(jìn)奇異譜分解的形態(tài)學(xué)解調(diào)方法及其在滾動(dòng)軸承故障診斷中的應(yīng)用　出處：《機(jī)械工程學(xué)報(bào)》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(diǎn)效應(yīng) 形態(tài)學(xué)解調(diào) 滾動(dòng)軸承 故障診斷

【摘要】：針對(duì)強(qiáng)背景噪聲及干擾源信號(hào)影響下滾動(dòng)軸承故障特征難以檢測(cè)的問題,提出一種基于改進(jìn)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(yàn)性選取嵌入維數(shù)長(zhǎng)度的缺陷,采用一種新的自適應(yīng)信號(hào)處理方法——奇異譜分解(Singular spectrum decomposition,SSD)進(jìn)行振動(dòng)信號(hào)分析,該方法通過構(gòu)建一個(gè)軌跡矩陣與自適應(yīng)選擇嵌入維數(shù)長(zhǎng)度,將非平穩(wěn)信號(hào)從高頻至低頻依次劃分為若干個(gè)單分量信號(hào)。針對(duì)奇異譜分解在分量序列重構(gòu)過程中兩端數(shù)據(jù)會(huì)偏離實(shí)際數(shù)據(jù)值進(jìn)而引起端點(diǎn)效應(yīng)現(xiàn)象的問題,提出運(yùn)用特征波形匹配延拓法對(duì)奇異譜分解進(jìn)行改進(jìn),提高其對(duì)振動(dòng)信號(hào)的分解質(zhì)量,獲得一系列更接近實(shí)際曲線的單分量序列。為準(zhǔn)確提取單分量中蘊(yùn)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(bǔ)頂帽變換對(duì)單分量信號(hào)進(jìn)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(shí)現(xiàn)軸承故障類型的準(zhǔn)確判別。仿真和實(shí)測(cè)信號(hào)分析驗(yàn)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(jī)械工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金(51675098) 高等學(xué)校博士學(xué)科點(diǎn)專項(xiàng)科研基金(20130092110003)資助項(xiàng)目
【分類號(hào)】：TH133.33
【正文快照】： 0前言*滾動(dòng)軸承是機(jī)械設(shè)備中的核心組件,在長(zhǎng)期高速運(yùn)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(gè)機(jī)械傳遞系統(tǒng)的工作性能。因此,針對(duì)軸承早期損傷階段進(jìn)行有效檢測(cè)備受關(guān)注。而在實(shí)際工程中,軸承振動(dòng)信號(hào)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(hào)：1408541