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Diagnosis of mechanical unbalance for double cage induction motor load in time-varying conditions based on motor vibration signature analysis

机译:基于电动机振动特征分析的双笼感应电动机负载时变机械不平衡诊断

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This paper investigates the detectability of mechanical unbalance in double cage induction motor load using motor vibration signature analysis technique. Rotor imbalances induce specific harmonic components in electrical, electromagnetical, and mechanical quantities. Harmonic components characteristic of this category of rotor faults, issued from vibration signals analysis, are closely related to rotating speed of the rotor, which complicates its detection under non-stationary operating conditions of the motor. Firstly, experimental results were performed first under healthy and mechanical load unbalance cases, for different load levels under steady-state operating conditions to evaluate the sensitivity of motor axial vibration signature analysis (MAVSA) and motor radial vibration signature analysis (MRVSA) techniques. Secondly, and in order to overcome the limitations of the FFT analysis in time-varying conditions, a simple and effective method based on advanced use of wavelet analysis is proposed, that allows the diagnosis of mechanical load unbalance for a double cage induction machine operating under non-stationary conditions. Experimental tests were conducted for these purposes showing the effectiveness of the presented technique under time-varying operating conditions.
机译:本文利用电动机的振动特征分析技术研究了双笼式感应电动机负载中机械不平衡的可检测性。转子不平衡会引起电气,电磁和机械量的特定谐波分量。由振动信号分析得出的这类转子故障的谐波分量特性与转子的转速密切相关,这使得在电动机的非平稳运行条件下对其进行检测变得复杂。首先,首先在健康和机械负载不平衡的情况下,针对稳态工作条件下的不同负载水平,进行实验结果,以评估电动机轴向振动特征分析(MAVSA)和电动机径向振动特征分析(MRVSA)技术的敏感性。其次,为克服时变条件下FFT分析的局限性,提出了一种基于小波分析先进应用的简单有效的方法,该方法可以对双笼感应电机在低速运行条件下的机械负载不平衡进行诊断。非平稳条件。为此目的进行了实验测试,显示了所提出技术在时变操作条件下的有效性。

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