ABSTRACT
Overloading can shorten operating life of induction motors. It is also a primary cause of some faults, such as excessive temperatures or tooth breakage. Detecting and classifying overload levels are very essential to ensure durable and stable operations of those electromechanical energy converters. In our research, sounds recorded by a single microphone is analyzed to categorize five levels of overload status. Three acoustic features and six classification models are evaluated. Acquired results show that this is a promising way to build a real-time and inexpensive monitoring system for induction motor overload.
- Hasmat Malik, Atif Iqbal, and Amit K. Yadav. 2020. Soft Computing in Condition Monitoring and Diagnostics of Electrical and Mechanical Systems. Springer Singapore.Google Scholar
- Dubravko Miljković. Brief review of motor current signature analysis. https://www.researchgate.net/publication/304094187_Brief_Review_of_Motor_Current_Signature_Analysis, last accessed 2020/08/07.Google Scholar
- Lamiaâ El Menzhi and Saad Abdallah. 2009. Induction motor fault diagnosis using voltage Park components of an auxiliary winding-voltage unbalance. In Proceedings of ICEMS 2009.Google ScholarCross Ref
- Julio-César Urresty, Jordi-Roger Riba, Miguel Delgado, and Luís Romeral. 2012. Detection of demagnetization faults in surface-mounted permanent magnet synchronous motors by means of the zero-sequence voltage component. IEEE Trans. on Energy Conversion, vol. 27(1), 42–51.Google ScholarCross Ref
- Sérgio M. A. Cruz and Antonio J. M. Cardoso. 2006. Diagnosis of rotor faults in closed-loop induction motor drives. In Proceedings of the IEEE Industry Application Society Annual Meeting, Tampa, FL, United States, CD-Rom, 1–8.Google Scholar
- Sérgio M. A. Cruz, Andrea Stefani, Fiorenzo Filippetti, and Antonio J. M. Cardoso. 2008. Diagnosis of rotor faults in traction drives for railway applications. In Proceedings of the 18th Int. Conf. on Electrical Machines.Google Scholar
- Seungdeog Choi, Bilal Akin, Mina M. Rahimian, and HamidA. Toliyat. 2012. Performance-oriented electric motors diagnotics in modern energy conversion systems. IEEE Trans. on Industrial Electronics, vol. 59(2), 1266–1277.Google ScholarCross Ref
- David G. Dorrell, D.G., William T. Thomson, and Steven Roach. 1997. Analysis of airgap flux, current, and vibration signals as a function of the combination of static and dynamic airgap eccentricity in 3-phase induction motors. IEEE Trans. on Industry Applications, vol. 33(1).Google ScholarCross Ref
- A. J. Ellison and S. J. Yang. 1971. Effects of rotor eccentricity on acoustic noise from induction machines. In Proceedings of the Institution of Electrical Engineers. Vol. 118. No. 1. IET Digital Library.Google Scholar
- Naim Baydar and Andrew Ball. 2001. A comparative study of acoustic and vibration signals in detection of gear failures using Wigner–Ville distribution. In Mechanical systems and signal processing. 2001;15(6), 1091–1107.Google Scholar
- Patricia Scanlon, Darren F. Kavanagh, and Francis M. Boland. 2013. Residual Life Prediction of Rotating Machines Using Acoustic Noise Signals. IEEE Trans. on Instrumentation and Measurement, vol. 62(1), 95–108.Google ScholarCross Ref
- Humberto Henao, Shahin H. Kia, and Gérard-André Capolino. 2011. Torsional-vibration assessment and gear-fault diagnosis in railway traction system. IEEE Trans. on Industrial Electronics, vo. 58(5), 1707–1717.Google ScholarCross Ref
- Peyman Milanfar and Jeffrey H. Lang. 1996. Monitoring the thermal condition of permanent-magnet synchronous motors. IEEE Trans. on Aerospace and Electronic Systems, vol. 32(4), 1421–1429.Google ScholarCross Ref
- Peter J. Tavner. 2008. Review of condition monitoring of rotating electrical machines. Electric Power Applications, IET, vol. 2(4).Google Scholar
- Mohammad S. Laghari, Faheem Ahmed, and Junaid Aziz. 2010. Wear particle shape and edge detail analysis. In Proceedings of the 2nd Int. Conf. on Computer and Automation Engineering.Google ScholarCross Ref
- Arturo Garcia-Perez, René J. Romero-Troncoso, Eduardo Cabal-Yepez, Roque Osornio-Rios, and Jose A. Lucio-Martinez. 2012. Application of high-resolution spectral analysis for identifying faults in induction motors by means of sound. J. Vib. Control. 18 (2012).Google Scholar
- Maciej Orman and Cajetan Pinto. 2013. Acoustic analysis of electric motors in noisy industrial environment. In Proceedings of the 12th IMEKO TC10 Workshop on Technical Diagnostics.Google Scholar
- Yumi Ono, Yoshifumi Onishi, Takafumi Koshinaka, Soichiro Takata, and Osamu Hoshuyama, O.: 2013. Anomaly detection of motors with feature emphasis using only normal sounds. In Proceedings of the 2013 IEEE International Conference on Acoustics Speech and Signal Processing, 2800–2804.Google Scholar
- Huseyin Akcay and Emin Germen. 2013. Identification of acoustic spectra for fault detection in induction motors. In 2013 Africon, IEEE.Google Scholar
- Adam Glowacz. 2014. Diagnostics of DC and induction motors based on the analysis of acoustic signals. Measurement Science Review, vol. 14, 257–262.Google ScholarCross Ref
- Emin Germen, Murat Başaran, and Mehmet Fidan. 2014. Sound based induction motor fault diagnosis using Kohonen self-organizing map. J Mech. Syst. Signal Process. 46, 45–58.Google ScholarCross Ref
- Dong-Jin Choi, Ji-Hoon Han, Sang-Uk Park, and Sun-Ki Hong. 2019. Diagnosis of electric motor using acoustic noise based on CNN. In Proceedings of the 22nd International Conference on Electrical Machines and Systems.Google ScholarDigital Library
- Michael J. Carey, Eluned S. Parris, and Harvey Lloyd – Thomas. 1999. A comparison of features for speech, music discrimination. In Proceedings of ICASSP’99, 149–152 (1999).Google ScholarDigital Library
- Iain McCowan, Daniel Gatica-Perez, Samy Bengio, Guillaume Lathoud, Mark Barnard, and Dong Zhang. 2005. Automatic analysis of multimodal group actions in meetings. IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 27, no. 3, 305–317.Google ScholarDigital Library
- Ian Jolliffe. 1986. Principal Component Analysis. Springer-Verlag, New York.Google Scholar
- Christopher M. Bishop. 1995. Neural Networks for Pattern Recognition. Oxford University Press.Google ScholarDigital Library
- Leo Breiman, Jerome H. Friedman, Richard A. Olshen, and Charles J. Stone. 1984. Classification and Regression Trees. Belmont, USA.Google Scholar
- Roger J. Jang. 1993. ANFIS: Adaptive-Network-based Fuzzy Inference Systems. IEEE Trans. on Systems, Man, and Cybernetics, vol. 23(3), 665–685.Google ScholarCross Ref
- Geoffrey McLachlan and David Peel. 2000. Finite Mixture Models. Hoboken, NJ: John Wiley & Sons, Inc.Google Scholar
- Eric Scheirer and Malcolm Slaney. 1997. Construction and evaluation of a robust multifeature music/speech discriminator. In Proceedings of ICASSP' 97, vol. II, 1331–1334.Google ScholarCross Ref
- Vladimir N. Vapnik. 1998. Statistical Learning Theory. Wiley, N.Y.Google ScholarCross Ref
Index Terms
- A Simple and Effective Sound-based Five-Class Classifier for Induction Motor Overload
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