@article{MAKHILLAJIT201615226524,
    title = {Intelligent Sensorless Fault Diagnosis of Mechatronics Module
Wavelet Transformation Based},
    journal = {Asian Journal of Information Technology},
    volume = {15},
    number = {22},
    pages = {4694-4697},
    year = {2016},
    issn = {1682-3915},
    doi = {ajit.2016.4694.4697},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2016.4694.4697},
    author = {Tatiana,Aleksey,Stas,Dmitriy,Roman,Sergey,Dmitriy and},
    keywords = {fault diagnosis,fuzzy model,Wavelet transformation,mechatronics module,stator current signal,sensorless control},
    abstract = {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.}
    }