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Application and optimization of the discrete wavelet transform for the detection of broken rotor bars in induction machines

机译:离散小波变换在感应电机转子断条检测中的应用与优化

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The problem of the bar breakage diagnosis in electrical induction cage machines is a matter of increasing concern nowadays, due to the widely spread use of these machines in the industry. The classical approach, focused on the Fourier analysis of the steady-state current, has some drawbacks that could be avoided if a study of the transient behavior of the machine is performed. The discrete wavelet transform (DWT) is an ideal tool for this purpose, due to its suitability for the analysis of signals whose frequency spectrum is variable in time. The paper shows how the study of the high-level signals resulting from the DWT of the transient starting current of an induction motor allows the detection of a particular characteristic harmonic that occurs when a rotor bar breakage has taken place. This constitutes an alternative approach that avoids some problems that the traditional method implies and that can even lead to a wrong diagnosis of the fault. In the work, the application of the DWT for broken bar detection is optimized, regarding certain parameters of the transform such as type of the mother wavelet, number of decomposition levels, order of the mother wavelet and sampling frequency.
机译:由于这些机器在工业中的广泛使用,如今在电感应笼式机器中的棒断裂诊断问题已成为越来越多的关注问题。专注于稳态电流的傅立叶分析的经典方法具有一些缺点,如果对电机的瞬态行为进行研究,则可以避免这些缺点。离散小波变换(DWT)由于其适用于分析频谱随时间变化的信号,因此是用于此目的的理想工具。本文显示了对由感应电动机的瞬态启动电流的DWT产生的高电平信号的研究如何允许检测出发生转子条损坏时发生的特定特征谐波。这构成了一种替代方法,可以避免传统方法所隐含的某些问题,甚至可能导致错误的诊断。在工作中,针对变换的某些参数,例如母子波的类型,分解级别数,母子波的阶数和采样频率,优化了DWT在折线检测中的应用。

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