Application and Optimization of the Discrete Wavelet Transform for the Detection of Broken Rotor Bars in Induction Machines
By J. Antonino-Daviu, M. Riera-Guasp, J. Roger-Folch, Félix Martínez-Giménez, Alfredo Peris. 2006
127 citations recorded by the source corpus.
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.
Subfields: Control and Systems Engineering, Mechanics of Materials
View Paper: https://www.semanticscholar.org/paper/3bbc233426adbc4180300fbf57a8501a7b03dbe9
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In Control and Systems Engineering
Citations in the corpus
- Fault Diagnosis in Industrial Induction Machines Through Discrete Wavelet Transform (2011, background): “…for obtaining an approximation signal ( A nf ) so that the upper limit of its associated frequency band is under the fundamental frequency [17] is described by the following condition: From this condition, the decomposition level of the approximation signal, which includes the left…”