Lyapunov指数在异步电动机机械振动识别中的应用

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摘要基于非线性动力学理论，研究异步电动机振动信号的Lyapunov指数特征，并应用于故障诊断和识别。首先，搭建实验平台，并模拟异步电动机正常工作、转子不对中和底座安装不良的三种转动状态。分析电动机三种振动信号的波形，并进行去噪和预处理。然后，基于BBA算法计算振动信号在不同工作状态下的Lyapunov指数谱，选取最大Lyapunov指数作为特征用于识别异步电动机的机械振动；最后，为了对该分析方法的有效性及抗干扰性进行验证，引入了随机噪声，分析所提出算法在不同参数下的受噪声的影响水平。研究结果显示，异步电动机在正常运行时，其最大Lyapunov指数值在0.3-0.7之间；安装不良时其最大Lyapunov指数值在0-0.3之间，表明这两种工作状态下电动机振动信号序列出自于一个混沌过程；在电动机处于转子不对中状态时，其最大Lyapunov指数值近似为零，表明其振动序列中基本不存在混沌属性。在本文研究结果的基础上，配合特征融合与机器学习分类算法，将有效提高异步电动机机械振动识别的准确率和效率。
关键词：异步电动机；故障振动； Lyapunov指数；BBA算法

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	刘雁1
	高宽1
	黄炎1
	张赫1
	肖军2

关键词 ：异步电动机, 故障振动, Lyapunov指数, BBA算法

Abstract：Based on the theory of nonlinear dynamics, the Lyapunov exponential characteristics of asynchronous motor vibration signals are studied and applied to fault diagnosis and identification. Firstly, the experimental platform is built, and the three rotation states of the induction motor, normal operation, rotor misalignment and poor base installation, are simulated. Waveform characteristics of three vibration signals are analyzed, and denoising and preprocessing are finished. Secondly, the Lyapunov exponent spectrum of vibration signals under different working conditions was calculated based on BBA algorithm, and the largest Lyapunov exponent was selected as the feature to identify the mechanical vibration of asynchronous motors.Finally, random noise was introduced to verify the effectiveness and anti-interference of the analysis method, the influence of noise level on BBA algorithm under different parameters is analyzed. The results show that the largest Lyapunov exponent value of the asynchronous motor is between 0.3 and 0.7 when it is running normally.The largest Lyapunov exponent value is between 0 and 0.3 when the motor is poorly installed, which indicates that the vibration signal sequence of the motor under the two operating states is from a chaotic process.When the motor is in the rotor misalignment state, its largest Lyapunov exponent value is approximately zero, which indicates that there is basically no chaotic property in its vibration sequence.In the analysis method proposed On the basis of the research results in this paper, the accuracy and efficiency of mechanical vibration recognition of asynchronous motors will be effectively improved by combining feature fusion and machine learning classification algorithm.
Key words: asynchronous motor; fault vibration; Lyapunov exponent; BBA algorithm

Key words： asynchronous motor fault vibration Lyapunov exponent BBA algorithm

收稿日期: 2021-03-29 出版日期: 2022-07-15

引用本文:

刘雁1，高宽1，黄炎1，张赫1，肖军2. Lyapunov指数在异步电动机机械振动识别中的应用[J]. 振动与冲击, 2022, 41(13): 142-151.
LIU Yan1, GAO Kuan1, HUANG Yan1, ZHANG He1, XIAO Jun2. Application of Lyapunov exponent in mechanical vibration identification of asynchronous motor. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(13): 142-151.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2022/V41/I13/142

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