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基于JADE-EMD的滾動(dòng)軸承故障檢測(cè)
2021年電子技術(shù)應(yīng)用第6期
馮平興1,張洪波2
1.成都工業(yè)學(xué)院 網(wǎng)絡(luò)與通信工程學(xué)院,四川 成都611731;2.成都信息工程大學(xué) 通信工程學(xué)院,四川 成都610225
摘要: 軸承故障分析在滾動(dòng)傳動(dòng)系統(tǒng)中一直是研究的熱點(diǎn),傳統(tǒng)的軸承故障診斷方法往往建立在苛刻的約束條件之上,如檢測(cè)信號(hào)為單一的故障信號(hào)成分、既定的混合系統(tǒng)保持不變或者模型建立在無噪聲的環(huán)境等。針對(duì)這些局限,結(jié)合了獨(dú)立成分分析(Independent Component Analysis,ICA)方法,提出了一種基于特征矩陣聯(lián)合相似對(duì)角化及經(jīng)驗(yàn)?zāi)B(tài)分解(Joint Approximative Diagonalization of Eigen matrix-Empirical Mode Decomposition,JADE-EMD)的多故障動(dòng)態(tài)盲分析技術(shù)。該方法的基本思想是基于多輸入多輸出的動(dòng)態(tài)混合模型,利用四階統(tǒng)計(jì)量對(duì)隨機(jī)噪聲的盲辨識(shí)特性,將滾動(dòng)軸承正常工作時(shí)的平穩(wěn)隨機(jī)噪聲看成一類常規(guī)的信號(hào)輸入。
中圖分類號(hào): TN91
文獻(xiàn)標(biāo)識(shí)碼: A
DOI:10.16157/j.issn.0258-7998.201019
中文引用格式: 馮平興,張洪波. 基于JADE-EMD的滾動(dòng)軸承故障檢測(cè)[J].電子技術(shù)應(yīng)用,2021,47(6):71-76.
英文引用格式: Feng Pingxing,Zhang Hongbo. Fault test of rolling bearing based on JADE-EMD[J]. Application of Electronic Technique,2021,47(6):71-76.
Fault test of rolling bearing based on JADE-EMD
Feng Pingxing1,Zhang Hongbo2
1.School of Network and Communication Engineering,Chengdu Technological University,Chengdu 611731,China; 2.School of Communication and Information Engineering,Chengdu University of Information Technology,Chengdu 610225,China
Abstract: Bearing fault analysis has been a research focus in rolling transmission system. However, the traditional bearing fault diagnosis technology is usually based on strict constraints, such as the detection signal is a single fault signal component, the established hybrid system remains unchanged, and the model is established in noise free situation. Aiming at the limitation of this problem, combined with the independent component analysis(ICA) method, this study proposes a multi fault dynamic blind analysis method based on joint approximate diagonalization of eigenmatrix empirical mode decision(JADE-EMD). The basic idea of this method is based on the dynamic transmission system with multi input and multi output. Because of the blind identification characteristics for random noise with fourth-order statistics, the stationary random noise of rolling bearing in normal operation works as a kind of conventional signal input. Then, the mixed signals received by the sensor are decomposed into independent components by dynamic blind source separation technology. Finally, the separated fault signals are decomposed by EMD, and the distribution results of several basic mode component functions(IMF) are obtained. Simulation results show that the method can effectively diagnose the rolling bearing with faults. Especially in the multi bearing drive system, it can effectively avoid the mutual interference between various fault signals. Compared with the traditional single direct detection method, it can further improve the accuracy of fault bearing analysis.
Key words : JADE-EMD;dynamic blind analysis;rolling bearing;fault diagnosis

0 引言

    滾動(dòng)軸承是轉(zhuǎn)動(dòng)傳輸系統(tǒng)中的關(guān)鍵機(jī)械零件之一,由于其表面光滑、滾道的尺寸精密,因而早期故障的振動(dòng)信號(hào)往往相對(duì)微弱[1-4],常常淹沒在軸與齒輪的振動(dòng)信號(hào)中,而軸承的工作狀態(tài)直接關(guān)系到整個(gè)機(jī)械傳輸系統(tǒng)的正常運(yùn)行。為了保障機(jī)械系統(tǒng)的正常且安全可靠的運(yùn)行,避免因軸承故障而對(duì)系統(tǒng)引起的次生損害[5-9],需要一種能動(dòng)態(tài)監(jiān)測(cè)并能有效的診斷滾動(dòng)軸承的工作狀況。本文的研究提出利用獨(dú)立成分分析(Independent Component Analysis,ICA)和經(jīng)驗(yàn)?zāi)B(tài)分解(Empirical Mode Decomposition,EMD)技術(shù)對(duì)軸承故障信號(hào)進(jìn)行聯(lián)合分析[10],通過利用這兩種信號(hào)處理技術(shù)的優(yōu)點(diǎn)實(shí)現(xiàn)了對(duì)軸承故障信號(hào)的檢測(cè)。




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作者信息:

馮平興1,張洪波2

(1.成都工業(yè)學(xué)院 網(wǎng)絡(luò)與通信工程學(xué)院,四川 成都611731;2.成都信息工程大學(xué) 通信工程學(xué)院,四川 成都610225)




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