Using immunology principles for fault detection

The immune system is a cognitive system of complexity comparable to the brain and its computational algorithms suggest new solutions to engineering problems or new ways of looking at these problems. Using immunological principles, a two- (or three-) module algorithm is developed which is capable of launching a specific response to an anomalous situation for diagnostic purposes. Experimental results concerning fault detection in an induction motor are presented as an example illustrating how the immune-based system operates, discussing its capabilities, drawbacks, and future developments.

[1]  M. M. O'Kane,et al.  Intelligent motors move to the forefront of predictive maintenance , 2000 .

[2]  C. F. Landy,et al.  Determination of interbar current effects in the detection of broken rotor bars in squirrel cage induction motors , 1994 .

[3]  R. Zinkernagel,et al.  Immunological Memory , 2006 .

[4]  B. Rocha,et al.  Population biology of lymphocytes: the flight for survival. , 2000, Annual review of immunology.

[5]  Birsen Yazici,et al.  An adaptive statistical time-frequency method for detection of broken bars and bearing faults in motors using stator current , 1999 .

[6]  Thomas G. Habetler,et al.  An unsupervised, on-line system for induction motor fault detection using stator current monitoring , 1994, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting.

[7]  Mo-Yuen Chow,et al.  Using a neural/fuzzy system to extract heuristic knowledge of incipient faults in induction motors. Part I-Methodology , 1995, IEEE Trans. Ind. Electron..

[8]  C. F. Landy,et al.  Evaluation of current and vibration signals for squirrel cage induction motor condition monitoring , 1997 .

[9]  J. Lang,et al.  Detection of broken rotor bars in induction motors using state and parameter estimation , 1989, Conference Record of the IEEE Industry Applications Society Annual Meeting,.

[10]  G.C. Soukup,et al.  Cause and analysis of stator and rotor failures in 3-phase squirrel cage induction motors , 1991, Conference Record of 1991 Annual Pulp and Paper Industry Technical Conference.

[11]  Thomas G. Habetler,et al.  Effects of time-varying loads on rotor fault detection in induction machines , 1993 .

[12]  J Timmis,et al.  An artificial immune system for data analysis. , 2000, Bio Systems.

[13]  Mohamed Benbouzid,et al.  Induction motors' faults detection and localization using stator current advanced signal processing techniques , 1999 .

[14]  F. Filippetti,et al.  AI techniques in induction machines diagnosis including the speed ripple effect , 1996 .

[15]  Hamid A. Toliyat,et al.  Transient analysis of cage induction machines under stator, rotor bar and end ring faults , 1995 .

[16]  Debaprasad Kastha,et al.  An improved starting strategy for voltage-source inverter fed three phase induction motor drives under inverter fault conditions , 2000 .

[17]  H.A. Toliyat,et al.  A novel approach for broken rotor bar detection in cage induction motors , 1998, Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242).

[18]  R. Natarajan.  Failure identification of induction motors by sensing unbalanced stator currents , 1989 .

[19]  F. Filippetti,et al.  AI techniques in induction machines diagnosis including the speed ripple effect , 1996, IAS '96. Conference Record of the 1996 IEEE Industry Applications Conference Thirty-First IAS Annual Meeting.

[20]  Dipankar Dasgupta,et al.  Novelty detection in time series data using ideas from immunology , 1996 .

[21]  J. Penman,et al.  Condition monitoring of electrical drives , 1986 .

[22]  P. Doherty,et al.  Accessing complexity: the dynamics of virus-specific T cell responses. , 2000, Annual review of immunology.

[23]  L. Bradley,et al.  T cell memory. , 1998, Annual review of immunology.

[24]  Antonio J. Marques Cardoso,et al.  Inter-turn stator winding fault diagnosis in three-phase induction motors, by Park's Vector approach , 1997 .

[25]  C Caux,et al.  Immunobiology of dendritic cells. , 2000, Annual review of immunology.