基于JADE-EMD的滾動軸承故障檢測
2021年電子技術應用第6期
馮平興1，張洪波2
1.成都工業學院 網絡與通信工程學院，四川 成都611731；2.成都信息工程大學 通信工程學院，四川 成都610225
摘要： 軸承故障分析在滾動傳動系統中一直是研究的熱點，傳統的軸承故障診斷方法往往建立在苛刻的約束條件之上，如檢測信號為單一的故障信號成分、既定的混合系統保持不變或者模型建立在無噪聲的環境等。針對這些局限，結合了獨立成分分析(Independent Component Analysis，ICA)方法，提出了一種基于特征矩陣聯合相似對角化及經驗模態分解(Joint Approximative Diagonalization of Eigen matrix-Empirical Mode Decomposition，JADE-EMD)的多故障動態盲分析技術。該方法的基本思想是基于多輸入多輸出的動態混合模型，利用四階統計量對隨機噪聲的盲辨識特性，將滾動軸承正常工作時的平穩隨機噪聲看成一類常規的信號輸入。
中圖分類號： TN91
文獻標識碼： 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的滾動軸承故障檢測[J].電子技術應用，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.
文獻標識碼： 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的滾動軸承故障檢測[J].電子技術應用，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
滾動軸承是轉動傳輸系統中的關鍵機械零件之一，由于其表面光滑、滾道的尺寸精密，因而早期故障的振動信號往往相對微弱[1-4]，常常淹沒在軸與齒輪的振動信號中，而軸承的工作狀態直接關系到整個機械傳輸系統的正常運行。為了保障機械系統的正常且安全可靠的運行，避免因軸承故障而對系統引起的次生損害[5-9]，需要一種能動態監測并能有效的診斷滾動軸承的工作狀況。本文的研究提出利用獨立成分分析(Independent Component Analysis，ICA)和經驗模態分解(Empirical Mode Decomposition，EMD)技術對軸承故障信號進行聯合分析[10]，通過利用這兩種信號處理技術的優點實現了對軸承故障信號的檢測。
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作者信息：
馮平興1，張洪波2
(1.成都工業學院 網絡與通信工程學院，四川 成都611731；2.成都信息工程大學 通信工程學院，四川 成都610225)
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