Health Monitoring of Induction Motor using Thermal Images

Authors

  • D. K. Chaturvedi Department of Electrical Engineering, Dayalbagh Educational Institute (Deemed University), Dayalbagh, Agra
  • M. P. Singh Faculty of Engineering and Technology, Dr. Ambedkar University, Agra

DOI:

https://doi.org/10.33686/pwj.v16i2.151493

Keywords:

Feature selection, Fault diagnostics, Health Monitoring, Intelligent system, Thermal image

Abstract

This paper deals with a system which monitors the health condition of a three phase induction motor by using infrared thermal images. Here two systems, real time and off line, are proposed to monitor the temperature variations and analyze the hot regions beyond the rated temperature in the three phase induction motor using infrared thermograms. This system helps to monitor the variation of temperature at the different parts of the induction motor. Abnormal temperature rise in any parts indicates the faults. This technique helps to prevent the parts of induction motor before any catastrophe would happen in the future. The color based segmentation technique is used to identify abnormal hot regions in the thermograms of three phase induction motor. A changing red color intensity algorithm is also implemented to recognize the hot spots and also the change in hotness in a particular area of induction motor to declare the health of that particular area. Similarly the conditions of various areas in the machine all together monitor the overall health of the Induction motor.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Downloads

Published

2020-12-28

How to Cite

Chaturvedi, D. K., & Singh, M. P. (2020). Health Monitoring of Induction Motor using Thermal Images. Power Research - A Journal of CPRI, 105–114. https://doi.org/10.33686/pwj.v16i2.151493

References

Jaffery ZA, Dubey AK. Design of early fault detection technique for electrical assets using infrared thermograms. International Journal of Electrical Power and Energy Systems, Science Direct. 2014 63:753-9. https://doi. org/10.1016/j.ijepes.2014.06.049

Huda ASN, Taib S. Suitable features selection for monitoring thermal condition of electrical equipment using infrared thermography. Infrared Physics and Technology, Science Direct. 2013 61:184-91. https://doi.org/10.1016/j. infrared.2013.04.012

Hu Y, Cao W, Wu J, Ji B. Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions. IEEE Transactions on Power Electronics. 2014 29(11):5667-72. https://doi.org/10.1109/ TPEL.2014.2325062

Ramirez-Rozo TJ, Garcia-Alvarez JC, Castellanos- Dominguez CG. Infrared thermal image segmentation using expectation-maximization-based clustering. Image, Signal Processing, and Artificial Vision (STSIVA). 17th Symposium IEEE; 2012. p. 223-6. https://doi. org/10.1109/STSIVA.2012.6340586

Chu FY, Williamson A. Fault location in SF6 insulated substations using thermal techniques. IEEE Transactions on Power Apparatus and Systems. 1982; PAS-101(7):1990-7. https://doi.org/10.1109/TPAS.1982.317446

Jiuqing W, Xingshan L. PCB infrared thermal imaging diagnosis using support vector classifier. IEEE Proceedings of the 4th World Congress Intelligent Control and Automation; 2002. p. 2718-22.

Chaturvedi DK, Iqbal MS, Singh MP, Singh VP. A review of health monitoring techniques of induction motor. CPRI. 2014 10(3):475-86.

Chaturvedi DK, Iqbal MS, Singh MP. Health monitoring techniques of induction motor. IJRTET. 2013; 469-477.

Chaturvedi DK, Iqbal MS, Singh MP. Condition monitoring of induction motor. International Conference on Recent Developments in Control, Automation and Power Engineering; Amity University: Noida; 2015. https://doi. org/10.1109/RDCAPE.2015.7281383

Chaturvedi DK, Iqbal MS, Singh MP. Intelligent health monitoring system for three phase induction motor using infrared thermal image. International Conference on Energy, Economics and Environment; Galgotia College of Engineering and Technoloy: Gr Noida; 2015. https://doi.org/10.1109/EnergyEconomics.2015.7235083

Chaturvedi DK, Iqbal MS, Singh MP. On line fault identification of induction motor using fuzzy system. International Conference on Advance Computing and Communication Technologies; Panipat, Hariyana; 2013. p. 106-12.

Chaturvedi DK, Karimpoure A, Singh MP. Health monitoring of induction motor using sound signals. International Conference on Contemporary Computing and Applications (Ic3a 2020); Lucknow, India; 2020. https://doi.org/10.1109/ IC3A48958.2020.233301

Most read articles by the same author(s)