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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时变条件下双笼感应电动机负荷机械不平衡的诊断

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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:本文研究了电机振动特征分析技术的双笼感应电动机负荷机械不平衡的可检测性。转子失衡诱导电,电磁和机械量的特定谐波分量。从振动信号分析发出这类转子故障的谐波分量特征,与转子的旋转速度密切相关,其在电动机的非静止操作条件下复杂其检测。首先,在健康和机械负载不平衡情况下首先进行实验结果,在稳态操作条件下进行不同的负载水平,以评估电动机轴向振动特征分析(MAVSA)和电机径向振动特征分析(MRVSA)技术的灵敏度。其次,为了克服时变条件的FFT分析的局限性,提出了一种基于小波分析的高级使用的简单有效的方法,允许诊断机械负荷不平衡,用于双笼式感应机非静止条件。为这些目的进行了实验测试,显示出呈现的技术在时变的操作条件下的有效性。

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