The doctoral dissertations of the former Helsinki University of Technology (TKK) and Aalto University Schools of Technology (CHEM, ELEC, ENG, SCI) published in electronic format are available in the electronic publications archive of Aalto University - Aaltodoc.
Aalto

Current-, Force-, and Vibration-Based Techniques for Induction Motor Condition Monitoring

Pedro Vicente Jover Rodríguez

Dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the Department of Electrical and Communications Engineering for public examination and debate in Auditorium S4 at Helsinki University of Technology (Espoo, Finland) on the 14th of September, 2007, at 12 noon.

Overview in PDF format (ISBN 978-951-22-8938-7)   [878 KB]
Dissertation is also available in print (ISBN 978-951-22-8937-0)

Abstract

The aim of this research was to discover the best indicators of induction motor faults, as well as suitable techniques for monitoring the condition of induction motors. Numerical magnetic field analysis was used with the objective of generating reliable virtual data to be analysed with modern signal processing and soft-computing techniques. In the first part of the research, a fuzzy system, based on the amplitudes of the motor current, was implemented for online detection of stator faults. Later on, from the simulation studies and using support vector machine (SVM), the electromagnetic force was shown to be the most reliable indicator of motor faults. Discrete wavelet transform (DWT) was applied to the stator current during the start-up transient, showing how the evolution of some frequency components allows the identification and discrimination of induction motor faults. Predictive filtering was applied to separate the harmonic components from the main current signal.

The second part of the research was devoted to the development of a mechanical model to study the effects of electromagnetic force on the vibration pattern when the motor is working under fault conditions. The third part of this work, following the indications given by the second part, is concerned with a method that allows the prediction of the effect of the electromechanical faults in the force distribution and vibration pattern of the induction machines. The FEM computations show the existence of low-frequency and low-order force distributions acting on the stator of the electrical machine when it is working under an electrical fault. It is shown that these force components are able to produce forced vibration in the stator of the machine. This is corroborated by vibration measurements. These low-frequency components could constitute the primary indicator in a condition monitoring system.

During the research, extensive measurements of current, flux and vibration were carried out in order to supply data for the research group. Various intentional faults, such as broken rotor bars, broken end ring, inter-turn short circuit, bearing and eccentricity failures, were created. A real dynamic eccentricity was also created. Moreover, different supply sources were used. The measurements supported the analytical and numerical results.

This thesis consists of an overview and of the following 8 publications:

  1. Pöyhönen, S., Negrea, M., Jover Rodríguez, P., Arkkio, A., Hyötyniemi, H., 2003, Numerical Magnetic Field Analysis and Signal Processing for Fault Diagnostics of Electrical Machines, COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, Vol. 22, No. 4, pp. 969-981.
  2. Jover Rodríguez, P., Arkkio, A., 2008, Detection of Stator Winding Fault in Induction Motor Using Fuzzy Logic, Applied Soft Computing, Vol. 8, No. 2, pp. 1112-1120. © 2008 by authors and © 2008 Elsevier Science. By permission.
  3. Jover Rodríguez, P., Negrea, M., Arkkio, A., 2005, A General Scheme for Induction Motor Condition Monitoring, Proceedings of the 5th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED 2005), Vienna, Austria, September 2005, Conference Proceeding CD, 6 p. © 2005 IEEE. By permission.
  4. Jover Rodríguez, P., Antonino-Daviu, J., Muñoz, E., Arkkio, A., 2006, A Simplified Online Technique for the Detection of Eccentricity in Induction Motors, Proceedings of the 17th International Conference on Electrical Machines (ICEM 2006), Crete Island, Greece, September 2006, Conference Proceeding CD, Paper No. 114, 6 p.
  5. Antonino-Daviu, J., Jover Rodríguez, P., Riera, M., Arkkio, A., Roger-Folch, J., 2007, DWT Analysis of Numerical and Experimental Data for the Diagnosis of Dynamic Eccentricities in Induction Motors, Mechanical Systems and Signal Processing, Volume 21, Issue 6, pp. 2575-2589.
  6. Jover Rodríguez, P., Negrea, M., Arkkio, A., 2004, Mechanical Model to Study Induction Motor under Fault Conditions, Proceedings of the 16th International Conference on Electrical Machines (ICEM 2004), Cracow, Poland, September 2004, Conference Proceeding CD, Paper No. 100, 6 p.
  7. Jover Rodríguez, P., Belahcen, A., Arkkio, A., 2006, Signatures of Electrical Faults in the Force Distribution and Vibration Pattern of Induction Motors, IEE Proceedings - Electric Power Applications, Vol. 153, No. 4, pp. 523-529.
  8. Jover Rodríguez, P., Belahcen, A., Arkkio, A., Laiho, A., Antonino-Daviu, J., 2007, Air-Gap Force Distribution and Vibration Pattern of Induction Motors under Dynamic Eccentricity, Electrical Engineering (Archiv für Elektrotechnik), article in press, 16 p.

Keywords: fault diagnostics, indicator, induction motor, vibration, stress, finite element methods, fuzzy logic, DWT, predictive filtering

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© 2007 Helsinki University of Technology

Last update 2011-05-26