An Intelligent Diagnostic Condition Monitoring System for AC Motors via Instantaneous Power Analysis


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Abstract


A novel intelligent diagnostic condition monitoring system for electric motors via instantaneous power analysis is proposed. Although several types of condition monitoring and fault diagnosis techniques are available, however they have limitations in terms of the hardware costs and installation of the sensors for data acquisition. The proposed sensor-less condition monitoring system will allow real-time continuous tracking of various defects and will determine the severity of the defects to provide automatic decision making. To illustrate the viability of the approach, experiments were carried out on two different defect levels of the motor bearings. It is anticipated that the proposed motor protection system will be quicker, more efficient and more user friendly than the existing methods
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Keywords


Condition Monitoring; Induction Motor; Intelligent Diagnostic; Programmable Logic Controllers; Labview; Signal Processing; Preventive Maintenance

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References


Y.Han and Y. H. Song, Condition Monitoring Techniques for Electrical Equipment: A Literature Survey, IEEE Power Engineering Review, vol. 22,2002, pp. 59-59.

O. Duque-Perez, D. Morinigo-Sotelo, and M. Perez-Alonso, Diagnosis of Induction Motors Fed By Supplies With High Harmonic Content Using Motor Current Signature Analysis, International Conference onPower Engineering, Energy and Electrical Drives, pp. 1-6, 2011.

W. T. Thomson and M. Fenger, Case Histories Of Current Signature Analysis To Detect Faults In Induction Motor Drives, IEEE International Electric Machines and Drives Conference, vol.3, 2003, pp. 1459-1465.

R. R. Schoen, T. G. Habetler, F. Kamran, and R. G. Bartfield, Motor Bearing Damage Detection Using Stator Current Monitoring, IEEE Transactions on Industry Applications, vol. 31,1995, pp. 1274-1279.

Report of Large Motor Reliability Survey of Industrial and Commercial Installations, Part I, IEEE Transactions on Industry Applications, vol. IA-21, 1985,pp. 853-864.

J. R. Stack, T. G. Habetler, and R. G. Harley, Fault Classification And Fault Signature Production For Rolling Element Bearings In Electric Machines,IEEE Transactions onIndustry Applications, vol. 40, 2004, pp. 735-739.

C. Bianchini, F. Immovilli, M. Cocconcelli, R. Rubini, and A. Bellini, Fault Detection Of Linear Bearings In Brushless Ac Linear Motors By Vibration Analysis, IEEE Transactions on Industrial Electronics, vol. 58, 2011, pp. 1684-1694.

M. E. H. Benbouzid, A Review Of Induction Motors Signature Analysis As A Medium For Faults Detection, Proceedings of the 24th Annual Conference of the IEEEIndustrial Electronics Society,vol.4, 1998,pp. 1950-1955.

M. Pineda-Sanchez, R. Puche-Panadero, M. Riera-Guasp, A. Sapena-Bano, J. Roger-Folch, and J. Perez-Cruz, Motor Condition Monitoring Of Induction Motor With Programmable Logic Controller And Industrial Network," Proceedings of the 2011-14th European Conference onPower Electronics and Application,2011, pp. 1-10.

S. F. Farag and M. K. Jhaveri, Intelligent Microprocessor-Based Devices Provide Advanced Motor Protection, Flexible Control, And Communication In Paper Mills,IEEE Transactions onIndustry Applications, vol. 33,1997, pp. 840-847.

M. Elmaleeh and N. Saad, Development Of Acoustic Emission Diagnostic System For Condition Monitoring Of Rotating Machines, IEEE 2nd InternationalPower and Energy Conference, 2008, pp. 1049-1054.

M. A. A. Elmaleeh, N. Saad, and M. Awan, Condition Monitoring Of Industrial Process Plant Using Acoustic Emission Techniques, International Conference onIntelligent and Advanced Systems,2010, pp. 1-6.

T. J. Holroyd, Machine Condition And Dynamic Diagnostics Via Acoustic Emission, IEE Seminar onOn-line Monitoring Techniques for the Off-Shore Industry (Ref. No. 1999/143), 1999, pp. 5/1-5/4.

O. Thorsen and M. Dalva, Condition monitoring Methods, Failure Identification And Analysis For High Voltage Motors In Petrochemical Industry, Eighth International Conference onElectrical Machines and Drives, 1997, pp. 109-113.

K. Teotrakool, M. J. Devaney, and L. Eren, Bearing Fault Detection In Adjustable Speed Drives Via A Support Vector Machine With Feature Selection Using A Genetic Algorithm, IEEEInstrumentation and Measurement Technology Conference Proceedings,2008, pp. 1129-1133.

R. S. Kumar, K. K. Ray, and K. V. Kumar, Fault Diagnosis Of Industrial Drives Using MCSA Techniques, International Conference onControl, Automation, Communication and Energy Conservation, 2009, pp. 1-7.

M. E. H. Benbouzid, H. Nejjari, R. Beguenane, and M. Vieira, Induction Motor Asymmetrical Faults Detection Using Advanced Signal Processing Techniques, IEEE Transactions on Energy Conversion, vol. 14,1999, pp. 147-152.

S. F. Legowski, A. H. M. Sadrul Ula, and A. M. Trzynadlowski, Instantaneous Stator Power As A Medium For The Signature Analysis Of Induction Motors, IEEE Thirtieth IAS AnnualIndustry Applications Conference, vol.1,1995, pp. 619-624.

M. E. H. Benbouzid, M. Vieira, and C. Theys, Induction Motors' Faults Detection And Localization Using Stator Current Advanced Signal Processing Techniques, IEEE Transactions on Power Electronics, vol. 14,1999, pp. 14-22.

J. A. Rosero, J. Cusido, A. Garcia, J. A. Ortega, and L. Romeral, Broken Bearings And Eccentricity Fault Detection For A Permanent Magnet Synchronous Motor, IEEE 32nd Annual Conference onIndustrial Electronics, 2006, pp. 964-969.

A. M. Trzynadlowski, M. Ghassemzadeh, and S. F. Legowski, Diagnostics Of Mechanical Abnormalities In Induction Motors Using Instantaneous Electric Power, IEEE Transactions on Energy Conversion , vol. 14,1999, pp. 1417-1423.

J. L. H. Silva and A. J. M. Cardoso, Bearing Failures Diagnosis In Three-Phase Induction Motors By Extended Park's Vector Approach, 31st Annual Conference of IEEEIndustrial Electronics Society, 2005.

Filippetti, F., Franceschini, G., Ometto, A., Meo, S., Survey of neural network approach for induction machine on-line diagnosis, Proceedings of the 1996 31st Universities Power Engineering Conference. Part 1 (of 3);Iraklio, Greece;18 September 1996through20 September 1996, pp. 17-20.

S. Meo, A. Ometto, N. Rotondale, Diagnostic-Oriented Modelling of Induction Machines with Stator Short Circuits, (2012) International Review on Modelling and Simulations (IREMOS), 5 (3), pp. 1202-1209.

S. Meo, A. Ometto, N. Rotondale, Influence of Closed-Loop Control Operations on Detecting Induction Machine Stator Faults, (2012) International Review of Electrical Engineering (IREE), 7 (3), pp. 4359-4365.

Filippetti, F., Franceschini, G., Tassoni, C., Meo, S., Ometto, A., Neural network aided on-line diagnostics of induction machine stator faults, (1995) Proceedings of the Universities Power Engineering Conference, 1, pp. 148-151.


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