Induction Motor Stator Fault Detection by a Condition Monitoring Scheme Based on Parameter Estimation Algorithms

Journal article


Duan, F and Živanović, R (2016). Induction Motor Stator Fault Detection by a Condition Monitoring Scheme Based on Parameter Estimation Algorithms. Electric Power Components and Systems. 44 (10).
AuthorsDuan, F and Živanović, R
Abstract

This article presents a simple, low-cost, and effective method for the early diagnosis of stator short-circuit faults. The approach relies on the combination of an induction motor mathematical model and parameter estimation algorithm. The kernel of the method is the efficient search for the characteristic parameters that indicate stator short-circuit faults. However, the non-linearity of a machine model may imply multiple local minima of an objective function implemented in the estimation algorithm. Taking this into consideration, the suitability of two industry-proven optimization algorithms (pattern search algorithm and genetic algorithm) as applied in the proposed condition monitoring method was investigated. Experimental results show that the proposed diagnosis method is capable of detecting stator short-circuit faults and estimating level and location of faults. The study also indicates that the proposed method is robust to motor parameters offset and unbalanced voltage supply. Application of the pattern search algorithm is suitable for a continuous monitoring system, where the previous result can be used as starting point of the new search. The genetic algorithm requires longer computation time and is suitable for the offline diagnostic system. It is not sensitive to the starting point, and achieving global solution is guaranteed.

Keywordsinduction motor; condition monitoring; stator fault detection; parameter estimation algorithms
Year2016
JournalElectric Power Components and Systems
Journal citation44 (10)
PublisherLondon South Bank University
Digital Object Identifier (DOI)doi:10.1080/15325008.2015.1089336
Publication dates
Print26 May 2016
Publication process dates
Deposited01 Dec 2017
Accepted22 Aug 2015
Accepted author manuscript
License
CC BY 4.0
Permalink -

https://openresearch.lsbu.ac.uk/item/873zy

  • 12
    total views
  • 0
    total downloads
  • 2
    views this month
  • 0
    downloads this month

Related outputs

A study on helicopter main gearbox planetary bearing fault diagnosis
Zhou, L, Duan, F, Corsar, M, Elasha, F and Mba, D (2017). A study on helicopter main gearbox planetary bearing fault diagnosis. Applied Acoustics.
Canonical variable analysis and long short-term memory for fault diagnosis and performance estimation of a centrifugal compressor
Li, X, Duan, F, Loukopoulos, P, Bennett, I and Mba, D (2018). Canonical variable analysis and long short-term memory for fault diagnosis and performance estimation of a centrifugal compressor. Control Engineering Practice. 72, pp. 177-191.
Canonical Variable Analysis for Fault Detection, System Identification and Performance Estimation
Duan, F, Xiaochuan, L, Tariq, S, Ian, B and David, M (2017). Canonical Variable Analysis for Fault Detection, System Identification and Performance Estimation. Lecture Notes in Mechanical Engineering. 3, pp. 247-257.
Induction Motor Stator Fault Detection by a Condition Monitoring Scheme Based on Parameter Estimation Algorithms
Duan, F and Zivanovic, R (2013). Induction Motor Stator Fault Detection by a Condition Monitoring Scheme Based on Parameter Estimation Algorithms. 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED). Valencia 27 - 30 Aug 2013 London; Taylor & Francis. doi:10.1080/15325008.2015.1089336
Dealing with missing data for prognostic purposes
Loukopoulos, P, Sampath, S, Pilidis, P, Zolkiewski, G, Bennett, I, Duan, F and Mba, D (2016). Dealing with missing data for prognostic purposes. Prognostics and System Health Management Conference. Chengdu, China 19 - 21 Oct 2016 London South Bank University. doi:10.1109/PHM.2016.7819934
Reciprocating compressor prognostics of an instantaneous failure mode utilising temperature only measurements
Loukopoulos, P, Zolkiewski, G, Bennet, I, Sampath, S, Pilidis, P, Duan, F, Sattar, TP and Mba, D (2017). Reciprocating compressor prognostics of an instantaneous failure mode utilising temperature only measurements. Applied Acoustics.
Combining Canonical Variate Analysis, Probability Approach and Support Vector Regression for Failure Time Prediction
Xiaochuan, L, Duan, F, Bennett, I and Mba, D (2017). Combining Canonical Variate Analysis, Probability Approach and Support Vector Regression for Failure Time Prediction. 2017 International Conference on Sensing, Diagnostics, Prognostics and Control. Shangai, China 16 - 18 Aug 2017 London South Bank University.
Using empirical mode decomposition scheme for helicopter main gearbox bearing defect identification
Duan, F, Corsar, M and Mba, D (2016). Using empirical mode decomposition scheme for helicopter main gearbox bearing defect identification. Prognostics and System Health Management Conference (PHM-Chengdu), 2016. Chengdu, China 19 - 21 Oct 2016 London South Bank University. doi:10.1109/PHM.2016.7819829
Using independent component analysis scheme for helicopter main gearbox bearing defect identification
Duan, F, Corsar, M, Zhou, L and Mba, D (2017). Using independent component analysis scheme for helicopter main gearbox bearing defect identification. 2017 IEEE International Conference on Prognostics and Health Management (ICPHM). Texas, USA 19 - 21 Jun 2017 London South Bank University. pp. 252-259 doi:10.1109/ICPHM.2017.7998337
Rotating machine prognostics using system-level models
Li, X, Duan, F, Mba, D and Bennett, I (2016). Rotating machine prognostics using system-level models. 2016 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE 2016) 2016 World Congress on Engineering Asset Management (WCEAM 2016). Jiuzhaigou, Sichuan, China 25 - 28 Jul 2016 London South Bank University.
Multidimensional prognostics for rotating machinery: A review
Li, X, Duan, F, Mba, D and Bennett, I (2017). Multidimensional prognostics for rotating machinery: A review. Advances in Mechanical Engineering. 9 (2).
A comparative study of helicopter planetary bearing diagnosis with vibration and acoustic emission data
Zhou, L, Duan, F, Mba, D and Faris, E (2017). A comparative study of helicopter planetary bearing diagnosis with vibration and acoustic emission data. 2017 IEEE International Conference on Prognostics and Health Management (ICPHM). Dallas, TX, USA 19 - 21 Jun 2017 London South Bank University. pp. 246-251 doi:10.1109/ICPHM.2017.7998336
Helicopter gearbox bearing fault detection using separation techniques and envelope analysis
Zhou, L, Duan, F, Mba, D, Corsar, M, Greaves, M, Sampath, S and Elasha, F (2016). Helicopter gearbox bearing fault detection using separation techniques and envelope analysis. Prognostics and System Health Management Conference (PHM-Chengdu), 2016. Chengdu, China 19 - 21 Oct 2016 London South Bank University. doi:10.1109/PHM.2016.7819888
Wireless Acoustic Emission Transmission System Designed for Fault Detection of Rotating Machine
Zhou, L, Duan, F and Mba, D (2016). Wireless Acoustic Emission Transmission System Designed for Fault Detection of Rotating Machine. Lecture Notes in Networks and Systems. 4, pp. 201-207.
Reciprocating compressor prognostics
Loukopoulos, P, Sampath, S, Plidis, P, Zolkiewski, G, Bennett, I, Duan, F, Sattar, TP and Mba, D (2017). Reciprocating compressor prognostics. CMSM 2017 7th International Congress Design and Modelling of Mechanical Systems. Hammamet, Tunisia 27 - 29 Mar 2017 London South Bank University.
Helicopter Main Gearbox Bearing Defect Identification using Vibration and Acoustic Emission Techniques
Duan, F, Elasha, F, Greaves, M and Mba, D (2016). Helicopter Main Gearbox Bearing Defect Identification using Vibration and Acoustic Emission Techniques. P2016 IEEE International Conference on Prognostics and Health Management (ICPHM). Carleton University Ottawa, ON, Canada 20 - 22 Jun 2016 IEEE. doi:https://doi.org/10.1109/ICPHM.2016.7542856
Low Speed Bearing Condition Monitoring – A Case Study
Duan, F, Nze, I and Mba, D (2016). Low Speed Bearing Condition Monitoring – A Case Study. Proceedings of 2016 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE 2016) and 2016 World Congress on Engineering Asset Management (WCEAM2016). Jiuzhaigou, Sichuan, China 25 - 28 Jul 2016 London South Bank University.
Feasibility study on using thioether as an emergency backup lubrication system on a large helicopter main gearbox
Duan, F, Tee, S, Corsar, M, Healey, A, Kleine-Beek, W and Mba, D (2016). Feasibility study on using thioether as an emergency backup lubrication system on a large helicopter main gearbox. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.
Helicopter Main Gearbox Bearing Defect Identification with Acoustic Emission Techniques
Duan, F, Elasha, F, Mba, D and Bennett, I (2016). Helicopter Main Gearbox Bearing Defect Identification with Acoustic Emission Techniques. IEEE International Conference on Prognostics and Health Management. Ottawa, Canada 20 - 22 Jun 2016 London South Bank University.
Induction Motor Parameter Estimation Using Sparse Grid Optimization Algorithm
Duan, F, Zivanovic, R, Al-Sarawi, S and Mba, D (2016). Induction Motor Parameter Estimation Using Sparse Grid Optimization Algorithm. IEEE Transactions on Industrial Informatics. PP (99).
A comparative study of the effectiveness of vibration and acoustic emission in diagnosing a defective bearing in a planetary gearbox
Elasha, F, Greaves, M, Mba, D and Duan, F (2016). A comparative study of the effectiveness of vibration and acoustic emission in diagnosing a defective bearing in a planetary gearbox. Applied Acoustics. 115, pp. 181-195.