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Wavelet Filter Selection Analysis for Air Gap Eccentricity in Three Phase Induction Motor

机译:三相异步电动机气隙偏心率的小波滤波器选择分析

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Electrical machines is more important in the industrial world. To maintain a continuous production that most of the process is supported by an induction motor it must be kept in good condition so that the damage can be avoided and make the equipment ages become longer. One of the damage to the induction motor is the air gap eccentricity which, if not detected, will cause friction between the rotor and the stator. For that needed a method for early detection. This research uses wavelet method. The type of wavelet families used there are 3. Wavelet families is haar, daubechies and symlet, it takes 3 wavelets to know which wavelet filter can better to detection air gap eccentricity. In the haar wavelet the success rate of dl (detail), d4 by 10%. For daubechies wavelet the percentage of success is in d1 by 90%, d2 and d4 by 20% and d3 by 10%. While for wavelet symlet the percentage of success in d1 is 100%, d2 is 80%, d3 is 30% and d4 is 20%. So for the type wavelet filter is haar the percentage of detection success rate is very low compared to the wavelet filters of daubechies and symlet.
机译:电机在工业世界中更为重要。为了保持连续生产,其中大部分过程都由感应电动机支持,必须保持良好的状态,以免造成损坏并延长设备寿命。感应电动机的损坏之一是气隙偏心率,如果未检测到,则会导致转子和定子之间产生摩擦。为此,需要一种早期检测的方法。本研究采用小波方法。这里使用的小波族的类型有3个。小波族是haar,daubechies和symlet,需要3个小波才能知道哪个小波滤波器可以更好地检测气隙偏心率。在haar小波中,dl(细节)的成功率d4降低了10%。对于Daubechies小波,成功率在d1中为90%,在d2和d4中为20%,在d3中为10%。对于小波symlet,d1中的成功百分比为100%,d2为80%,d3为30%,d4为20%。因此,对于小波滤波器是haar型的,与daubechies和symlet的小波滤波器相比,检测成功率的百分比非常低。

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