Aleksey Zinin, Stas Tarkovalin, Dmitriy Litvin, Roman Leukhin, Sergey Yanvarev, Dmitriy Shurygin, Danil Shaykhutdinov and Tatiana Kruglova
Page: 4694-4697 | Received 21 Sep 2022, Published online: 21 Sep 2022
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This study describes a fault diagnosis system for mechatronics modules realized through the combination of wavelet transformation, fuzzy logic and neural network techniques. As a reference base we have selected Daubechies wavelet. Fault diagnoses accomplish the characteristic frequencies using the fuzzy logic in aggregate neural network. The combination of advanced techniques reduces the learning time and increases the diagnosis accuracy. The experimental results indicate that the proposed method is promising for the mechatronics modules.
Aleksey Zinin, Stas Tarkovalin, Dmitriy Litvin, Roman Leukhin, Sergey Yanvarev, Dmitriy Shurygin, Danil Shaykhutdinov and Tatiana Kruglova. Intelligent Sensorless Fault Diagnosis of Mechatronics Module
Wavelet Transformation Based.
DOI: https://doi.org/10.36478/ajit.2016.4694.4697
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2016.4694.4697