Condition Monitoring of Single Phase Induction Motor Using Fuzzy Logic Scheme

Condition Monitoring of Single Phase Induction Motor Using Fuzzy Logic Scheme

Sudeep SamantaPushpak Seal Jitendra Nath Bera

MCKVIE, Liluah, Howrah, India

MCKVIE, Liluah, Howrah, India

Applied Physics Department, University College of Science and Technology

Corresponding Author Email: 
sudeep0809@gmail.com; sudeep0809@gmail.com
Page: 
80-88
|
DOI: 
https://doi.org/10.18280/mmc_d.380107
Received: 
April 2017
| |
Accepted: 
15 November 2017
| | Citation

OPEN ACCESS

Abstract: 

In this paper, the authors described a performance based health monitoring technique of the singlesingle-phase induction motor. When any internal damage occurs in induction motor, harmonic generates and its severity depends on how much internal damage occurs. Presented technique was bas ed on the analysis of voltage and current signals of induction motor. A Fuzzy logic based

algorithm has been made for condition monitoring of Induction motor. The proposed methodology has been tested experimentally on a 100W, 230 V, 50 Hz domestic fan moto r to check the accuracy of Fuzzy inference system.

Keywords: 

Single phase induction motor, fast Fourier transform, total harmonic distortion, motor current signature analysis, Labview, fuzzy logic.

1. Introduction
2. Fault Detection Methodology
3. Hardware Experimentation
4. Conclusions
  References

[1]. H. Henao, G.A. Capolino, M.C. Fernandez, F. Filippetti, C. Bruzzese, Trends in fault diagnosis for electrical machines a review of diagnostic techniques, 2014, IEEE Industrial Electronics Magazine, vol. 8, no. 2, pp. 31-42.

[2]. R. Islam, S.A. Khan, J.M. Kim, Discriminant feature distribution analysis-based hybrid feature selection for online bearing fault diagnosis in induction motors, 2015, Journal of Sensors, Article Number: 7145715.

[3]. Z.J. Wang, Z.N. Han, F.S. Gu, J.X. Gu, S.H. Ning, A novel procedure for diagnosing multiple faults in rotating machinery, 2015, ISA Transactions, vol. 55, no. 2, pp. 208-218.

[4]. M. Irfan, N. Saad, R. Ibrahim, V.S. Asirvadam, An on-line condition monitoring system for induction motors via instantaneous power analysis, 2015, Journal of Mechanical Science and Technology, vol. 29, no. 4, pp. 1483-1492.

[5]. C.D. Costa, M. Kashiwagi, M.H. Mathias, Rotor failure diagnosis of induction motors by wavelet transform and fourier transform in function of the load, 2015, International Conference on Computer Science and Artificial Intelligence (ICCSAI 2014), vol. 8, pp.109-113.

[6]. D. Valis, K.U. Pietrucha, Utilization of diffusion processes and fuzzy logic for vulnerability Assessment, 2014, Journal of Eksploatacja i Niezawodnosc–Maintenance and Reliability, vol. 16, no. 1, pp. 48-55,

[7]. Y.L. Ching, B.K. Chen, L.W. Jen, Y. Fenghsu, Effects of various unbalanced voltages on the operation of an induction motor under the same voltage unbalance factor condition, 1997, IEEE Transaction Digital Library, pp. 51-59.

[8]. B.P. Cummings, J.R. Jacobs, H. Robert, Protection of induction motor against unbalanced voltage operation, 1985, IEEE Transactions on Industry Applications, vol. IA-21, no. 4, pp. 778-792.

[9]. P. Zhang, Y. Du, T.G. Habetler, B. Lu, A servey of condition monitoring & protection methods for medium-voltage induction motor, 2011, IEEE Transactions on Industry Applications, vol. 47, no. 1, pp. 34-46.

[10]. V.P. Mini, S. Ushakumari, Incipient fault detectionand diagnosis of induction motor using fuzzy logic, 2011, IEEE Transaction on Industry Application, vol. 47, no. 1, pp. 675-681.