DOAJ Open Access 2022

Application of Convolutional Neural Network for Fault Diagnosis of Bearing Scratch of an Induction Motor

Shrinathan Esaki Muthu Pandara Kone Kenichi Yatsugi Yukio Mizuno Hisahide Nakamura

Abstrak

The demand for the condition monitoring of induction motors is increasing in various fields, such as industry, transportation, and daily life. Bearing faults are the most common faults, and many fault diagnosis methods have been proposed using artificial pitting as the fault factor in most cases. However, the validity of a fault diagnosis method for other kinds of faults does not seem to be evaluated. Considering onsite scenarios and other possibilities of faults, this paper introduces scratches on the outer raceways of bearings. A study was performed on the detection of several kinds of bearing scratches using a proposed method that was based on an auto-tuning convolutional neural network. The developed approach was also compared with other diagnostic methods for validation. The results showed that the proposed technique provides the possibility of diagnosing several kinds of scratches with acceptable accuracy rates.

Topik & Kata Kunci

Technology Engineering (General). Civil engineering (General) Biology (General) Physics Chemistry

Penulis (4)

Shrinathan Esaki Muthu Pandara Kone

Kenichi Yatsugi

Yukio Mizuno

Hisahide Nakamura

Format Sitasi

APA MLA BibTeX

Kone, S.E.M.P., Yatsugi, K., Mizuno, Y., Nakamura, H. (2022). Application of Convolutional Neural Network for Fault Diagnosis of Bearing Scratch of an Induction Motor. https://doi.org/10.3390/app12115513

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Informasi Jurnal

Tahun Terbit: 2022
Sumber Database: DOAJ
DOI: 10.3390/app12115513
Akses: Open Access ✓