<abstract xmlns="http://www.w3.org/1999/xhtml"><p> In this paper, a non-invasive method of early fault diagnostics of electric motors was proposed. This method uses acoustic signals generated by electric motors. Essential features were extracted from acoustic signals of motors. A plan of study of acoustic signals of electric motors was proposed. Researches were carried out for faultless induction motor, induction motor with one faulty rotor bar, induction motor with two faulty rotor bars and flawless Direct Current, and Direct Current motor with shorted rotor coils. Researches were carried out for methods of signal processing: log area ratio coefficients, Multiple signal classification, Nearest Neighbor classifier and the Bayes classifier. A pattern creation process was carried out using 40 samples of sound. In the identification process 130 five-second test samples were used. The proposed approach will also reduce the costs of maintenance and the number of faulty motors in the industry.</p></abstract>

In this paper, a non-invasive method of early fault diagnostics of electric motors was proposed. This method uses acoustic signals generated by electric motors. Essential features were extracted from acoustic signals of motors. A plan of study of acoustic signals of electric motors was proposed. Researches were carried out for faultless induction motor, induction motor with one faulty rotor bar, induction motor with two faulty rotor bars and flawless Direct Current, and Direct Current motor with shorted rotor coils. Researches were carried out for methods of signal processing: log area ratio coefficients, Multiple signal classification, Nearest Neighbor classifier and the Bayes classifier. A pattern creation process was carried out using 40 samples of sound. In the identification process 130 five-second test samples were used. The proposed approach will also reduce the costs of maintenance and the number of faulty motors in the industry.

Diagnostics of DC and Induction Motors Based on the Analysis of Acoustic Signals

AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatics and Biomedical Engineering, Al. A. Mickiewicza 30, 30-059 Kraków, Poland

Measurement Science Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Diagnostics of DC and Induction Motors Based on the Analysis of Acoustic Signals"}

In this paper, a non-invasive method of early fault diagnostics of electric motors was proposed. This method uses acoustic signals generated by electric...

Diagnostics of DC and Induction Motors Based on the Analysis of Acoustic Signals

Data publikacji: 05 lis 2014

Zakres stron: 257 - 262

Otrzymano: 18 lut 2014

Przyjęty: 30 wrz 2014

DOI: https://doi.org/10.2478/msr-2014-0035

© by A. Glowacz

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.