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Intelligent induction motor diagnosis system: A new challenge

机译:智能感应电动机诊断系统:新挑战

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Recently, One Class Support Vector Machines (OCSVM) have been the subject of much research. This paper introduces a novel pattern classification approach for Broken Rotor Bar (BRB) detection in Induction Motors (IM), which combines Stationary Wavelet Packet Transform (SWPT) and OCSVM. Among all the kernels available to OCSVM, wavelet kernels are tuned to improve accuracy and detection time of fault. The SWPT is applied for the relevant data under lower sampling rate and a reduced number of samples. The experimental results on different load levels prove that the proposed method has a better performance than other methods.
机译:最近,一类支持向量机(OCSVM)已经成为许多研究的主题。本文介绍了一种新颖的模式分类方法,该方法结合了静止小波包变换(SWPT)和OCSVM,用于感应电动机(IM)中的转子断条(BRB)检测。在OCSVM可用的所有内核中,对小波内核进行了调整,以提高准确性和故障检测时间。 SWPT适用于较低采样率和减少采样数的相关数据。在不同负载水平下的实验结果证明,该方法具有比其他方法更好的性能。

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