Regression Based Performance Analysis and Fault Detection in Induction Motors by Using Deep Learning Technique

Pradeep Katta; Karunanithi Kandasamy; Raja Soosaimarian Peter Raj; Ramesh Subramanian; Chandrasekar Perumal

doi:10.14201/adcaij.28435

Regression Based Performance Analysis and Fault Detection in Induction Motors by Using Deep Learning Technique

Pradeep Katta

School of Electrical and Communication Engineering pradeep.2048[at]gmail.com
Karunanithi Kandasamy

School of Electrical and Communication Engineering
Raja Soosaimarian Peter Raj

School of Electrical and Communication Engineering
Ramesh Subramanian

School of Electrical and Communication Engineering
Chandrasekar Perumal

School of Electrical and Communication Engineering

https://doi.org/10.14201/adcaij.28435

Metrics

39 Views

96 Downloads

135 Total

How to Cite

Katta, P., Kandasamy, K., Soosaimarian Peter Raj, R., Subramanian, R., & Perumal, C. (2023). Regression Based Performance Analysis and Fault Detection in Induction Motors by Using Deep Learning Technique. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 11(3), 349–365. https://doi.org/10.14201/adcaij.28435

Download Citation

Editorial dates

Submitted:

12-02-2022

Acceptance:

02-05-2022

Published:

24-01-2023

Issue

Vol. 11 No. 3 (2022)

Section

Articles

Keywords

induction motor
DBN
RBM
Fast Fourier Transform (FFT)
regression modeling

License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Ethical standards for the ADCAIJ journal

Upon submitting original contributions to the ADCAIJ joumal, the authors agree to accept the standard procedures for the scientific community: contributions will be original in nature, neither published nor under consideration by other journals. Likewise, any original material sent to ADCAIJ will not be sent to other publications until our joumal has completed its evaluation process.

The authors will adhere to international copyright standards for written, graphic and other materials included in their writings sent to ADCAIJ for publication. For their part, the editors, the editorial staff, and journal reviewers will ensure that the integrity of the research is upheld, an effort that corresponds first and foremost to the authors. Consequently, authors will be asked to continue avoiding the practice of plagiarism and self-?plagiarism. The Corresponding Author signs for and accepts responsibility for releasing this material on behalf of any and all Co-Authors.