journal article·2022-02-16Open access

Application of Frequency Response Analysis Method to Detect Short-Circuit Faults in Three-Phase Induction Motors

Salem Mgammal Al-Ameri, Ahmed Allawy Alawady, Mohd Fairouz Mohd Yousof, Muhammad Saufi Kamarudin, Ali Ahmed Salem, Ahmed Abu-Siada, Mohamed I. Mosaad

Applied Sciences· Volume 12· Issue 4

Abstract

The industry has widely accepted Frequency Response Analysis (FRA) as a reliable method to detect power transformers mechanical deformations. While the FRA technique has been recommended in recent literature as a potential diagnostic method to detect internal faults within rotating machines, detailed feasibility studies have not been fully addressed yet. This paper investigates the feasibility of using the FRA technique to detect several short circuit faults in the stator winding of three-phase induction motors (TPIMs). In this regard, FRA testing is conducted on two sets of induction motors with various short circuit faults. Investigated faults include short circuits between two phases, short circuit turns within the same phase, phase-to-ground, and phase-to-neutral short circuit. The measured FRA signatures are divided into three frequency ranges: low, medium, and high. Several statistical indicators are employed to quantify the variation between faulty and healthy signatures in each frequency range. Experimental results attest the feasibility of the FRA technique as a diagnostic tool to detect internal faults in rotating machines, such as induction motors.
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Research context

OpenAlex topics: Power Transformer Diagnostics and Insulation · Machine Fault Diagnosis Techniques · Magnetic Properties and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja 86400, Malaysia

College of Technical Engineering, The Islamic University, Najaf 54001, Iraq

Institute of High Voltage and High Current, School of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia

Electrical and Computer Engineering Discipline, Curtin University, Bentley, WA 6102, Australia

Electrical & Electronics Engineering Technology Department, Royal Commission Yanbu Colleges & Institutes, Alnahdah, Yanbu Al Sinaiyah, Yanbu 46452, Saudi Arabia

References (40)

Show source-provided references
1. Hsiao, C.-H., and Liu, M.-K. (2017, January 13–17). Failure mode analysis of induction motor model. Proceedings of the 2017 IEEE International Conference on Applied System Innovation, Sapporo, Japan.10.1109/ICASI.2017.7988336 ↗
2. Fault Diagnosis and Detection in Industrial Motor Network Environment Using Knowledge-Level Modelling Technique
3. Cornell, P.F.E.P., Owen, E.L., Appiarius, J.C., McCoy, R.M., and Albrecht, D.W.H. (1982). Improved Motors for Utility Applications. Final Report, General Electric Co.10.2172/6759687 ↗
4. IEEE Motor Reliability Working Group (1985). Report of Large Motor Reliability Survey of Industrial and Commercial Installations, Part I. IEEE Trans. Ind. Appl., IA-21, 853–864.10.1109/TIA.1985.349532 ↗
5. Detection of Stator Short-Circuit Faults in Induction Motors Using the Concept of Instantaneous Frequency10.1109/TII.2018.2881921 ↗
6. Florkowski, M., Florkowska, B., and Zydron, P. (2019). Partial Discharges in Insulating Systems of Low Voltage Electric Motors Fed by Power Electronics—Twisted-Pair Samples Evaluation. Energies, 12.10.3390/en12050768 ↗
7. Hossain, M.L., Abu-Siada, A., and Muyeen, S.M. (2018). Methods for Advanced Wind Turbine Condition Monitoring and Early Diagnosis: A Literature Review. Energies, 11.10.3390/en11051309 ↗
8. Improved Condition Monitoring Technique for Wind Turbine Gearbox and Shaft Stress Detection10.1049/iet-smt.2016.0338 ↗
9. Shulphqwdo, Q.Q., Vlv, Q.D.O., and Ghsduwphqw, O.Q. (2021, January 11–13). Condition Monitering and fault Diagnosis of Induction motor–An Experimental Analysis. Proceedings of the 7th International Conference on Electrical Energy Systems (ICEES), Chennai, India.
10. OMICRON (2021, October 28). Diagnostic Testing and Monitoring of Rotating Machines. Available online: https://www.omicronenergy.com/download/document/40CEA890-3E5B-447D-BEF5-51CBE544A6E0/.
11. Yousof, M.F.M., Alawady, A.A., Al-Ameri, S.M., Azis, N., and Illias, H.A. (2021, January 12–14). FRA Indicator Limit for Faulty Winding Assessment in Rotating Machine. Proceedings of the 2021 IEEE International Conference on the Properties and Applications of Dielectric Materials (ICPADM), Johor Bahru, Malaysia.
12. Vilhekar, T.G., Ballal, M.S., and Umre, B.S. (2016, January 23–26). Application of Sweep Frequency Response Analysis for the detection of winding faults in induction motor. Proceedings of the IECON 2016—42nd Annual Conference of the IEEE Industrial Electronics Society, Florence, Italy.10.1109/IECON.2016.7793565 ↗
13. Understanding power transformer frequency response analysis signatures10.1109/MEI.2013.6507414 ↗
14. Estimating Power Transformer High Frequency Model Parameters Using Frequency Response Analysis
15. A New Approach for Estimating Insulation Condition of Field Transformers Using FRA10.4316/AECE.2020.01005 ↗
16. Mechanical Condition Assessment of Transformer Windings Using Frequency Response Analysis (Fra)
17. (2012). Power Transformers—Part 18, Measurement of Frequency Response (Standard No. IEC 60076-18 Ed.1).
18. (2013). IEEE Guide for the Application and Interpretation of Frequency Response Analysis for Oil-Immersed Transformers IEEE Power and Energy Society (Standard No. C57.149-2012).
19. Al-Ameri, S., Yousof, M.F.M., Ahmad, H., Alsubari, M., and Talib, M.A. (2017, January 11–15). Examining faulty transformer tap changer using frequency response analysis. Proceedings of the 2017 International Symposium on Electrical Insulating Materials (ISEIM), Toyohashi, Japan.10.23919/ISEIM.2017.8088736 ↗
20. Using Lumped Element Equivalent Network Model to Derive Analytical Equations for Interpretation of Transformer Frequency Responses10.1109/ACCESS.2020.3027798 ↗
21. Al-Ameri, S., Kamarudin, M., Yousof, M., Salem, A., Siada, A., and Mosaad, M. (2021). Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers. Appl. Sci., 11.10.3390/app11072923 ↗
22. Uhrig, S., Ottl, F., Hinterholzer, R., and Augeneder, N. (2019). Reliable Diagnostics on Rotating Machines using FRA. The International Symposium on High Voltage Engineering, Springer.10.1109/Diagnostika49114.2020.9214647 ↗
23. Frequency response analysis technique for induction motor short circuit faults detection
24. Phase to phase fault detection of 3-phase induction motor using FRA technique
25. Brandt, M., and Kascak, S. (2016, January 16–18). Failure identification of induction motor using SFRA method. Proceedings of the ELEKTRO 2016—11th International Conference, Tatry-Štrbské Pleso, Slovakia.10.1109/ELEKTRO.2016.7512079 ↗
26. Brandt, M., Gutten, M., and Kascak, S. (2016, January 6–8). Diagnostic of induction motor using SFRA method. Proceedings of the 2016 Conference on Diagnostics in Electrical Engineering, Pilsen, Czech.10.1109/DIAGNOSTIKA.2016.7736474 ↗
27. Internal Fault Detection of Induction Motor using Frequency Response Analysis Technique10.30534/ijatcse/2020/1591.22020 ↗
28. Induction motor inter-turn fault modeling and simulation using SSFR test for diagnosis purpose10.7305/automatika.2017.10.1805 ↗
29. Fan, F., Zhao, Z., Tu, P., Jie, H., and See, K.Y. (2021, January 6). Impact of Motor Stator Winding Faults on Common-Mode Current. Proceedings of the Asia-Pacific International Symposium on Electromagnetic Compatibility (APEMC), Bali, Indonesia.10.1109/APEMC49932.2021.9597053 ↗
30. Sant’Ana, W.C., Lambert-Torres, G., Bonaldi, E.L., Gama, B.R., Zacarias, T.G., Areias, I.A.d.S., Arantes, D.D.A., Assuncao, F.D.O., Campos, M.M., and Steiner, F.M. (2021). Online Frequency Response Analysis of Electric Machinery through an Active Coupling System Based on Power Electronics. Sensors, 21.10.3390/s21238057 ↗
31. Evaluation of numerical indices for the assessment of transformer frequency response10.1049/iet-gtd.2016.0879 ↗
32. Understanding the Influence of Power Transformer Faults on the Frequency Response Signature Using Simulation Analysis and Statistical Indicators10.1109/ACCESS.2021.3076984 ↗
33. A survey on statistical indexes applied on frequency response analysis of electric machinery and a trend based approach for more reliable results10.1016/j.epsr.2016.03.044 ↗
34. Detection and quantitative diagnosis of axial displacement of transformer winding byfrequency response analysis10.1049/iet-gtd.2018.6032 ↗
35. Application of DIP to Detect Power Transformers Axial Displacement and Disk Space Variation Using FRA Polar Plot Signature10.1109/TII.2016.2626779 ↗
36. Alternative statistical techniques for aiding SFRA diagnostics in transformers10.1049/iet-gtd.2011.0268 ↗
37. Hashemnia, N., Abu-Siada, A., Masoum, M.A.S., and Islam, S.M. (2012, January 23–27). Characterization of transformer FRA signature under various winding faults. Proceedings of the 2012 IEEE International Conference on Condition Monitoring and Diagnosis, Bali, Indonesia.10.1109/CMD.2012.6416174 ↗
38. Detecting incipient radial deformations of power transformer windings using polar plot and digital image processing10.1049/iet-smt.2017.0412 ↗
39. Statistical approach for interpretation of power transformers frequency response analysis results10.1049/iet-smt.2014.0097 ↗
40. Detection of stator short circuit faults in three-phase induction motors using motor current zero crossing instants10.1016/j.epsr.2010.12.003 ↗