首页> 外文会议>2013 IEEE 1st International Conference on Condition Assessment Techniques in Electrical Systems >Mathematical analysis of unbalanced magnetic pull and detection of mixed air gap eccentricity in induction motor by vibration analysis using MEMS accelerometer
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Mathematical analysis of unbalanced magnetic pull and detection of mixed air gap eccentricity in induction motor by vibration analysis using MEMS accelerometer

机译:MEMS加速度计振动分析的不平衡磁拉力数学分析与混合气隙偏心检测

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摘要

Air gap eccentricity fault existing in the induction motor may be of the form static or dynamic or together known as mixed eccentricity. Due to this, an unbalanced magnetic pull (UMP) will be setup between stator and rotor. This can cause bearing damage, rubbing of rotor with stator and may develop unwanted vibration and noise, which may results in premature failure of the motor. In this context, this paper presents the mathematical analysis of unbalanced magnetic pull due to air gap eccentricity in induction motor. Experimental investigations have been carried out to detect mixed airgap eccentricity fault by vibration signature analysis using Micro-Electro-Mechanical Systems (MEMS) accelerometer under different operating conditions. The spectral analysis of motor vibration has been carried out using radix-2 decimation in time Fast Fourier Transform algorithm (DIT-FFT). The presence of side band harmonic frequencies around fundamental component in the motor vibration signal spectrum indicates mixed eccentricity fault. The experimental results demonstrate that it is possible to identify the mixed airgap eccentricity fault by vibration signature analysis using MEMS accelerometer. A simple method has been proposed to find the fault severity in the motor under variable load conditions due to mixed air gap eccentricity
机译:感应电动机中存在的气隙偏心故障可以是静态或动态的形式,或者一起称为混合偏心。因此,将在定子和转子之间设置不平衡的磁拉(UMP)。这可能会导致轴承损坏,转子与定子的摩擦,并可能产生有害的振动和噪音,从而可能导致电动机过早失效。在这种情况下,本文提出了感应电动机中由于气隙偏心引起的不平衡磁拉的数学分析。通过使用微机电系统(MEMS)加速度计在不同操作条件下的振动信号分析,已经进行了实验研究,以检测混合气隙偏心故障。电动机振动的频谱分析已使用基数2抽取及时快速傅里叶变换算法(DIT-FFT)进行。电机振动信号频谱中基本成分周围的边带谐波频率的存在表明存在混合偏心故障。实验结果表明,通过使用MEMS加速度计进行振动信号分析,可以识别混合气隙偏心故障。提出了一种简单的方法来查找由于混合气隙偏心引起的可变负载条件下电动机的故障严重性

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