A Comparative Study into Observer based Fault Detection and Diagnosis in DC Motors: Part-I

A model based fault detection and diagnosis technique for DC motor is proposed in this paper. Fault detection using Kalman filter and its different variants are compared. Only incipient faults are considered for the study. The Kalman Filter iterations and all the related computations required for fault detection and fault confirmation are presented. A second order linear state space model of DC motor is used for this work. A comparative assessment of the estimates computed from four different observers and their relative performance is evaluated.

Authors:

• Padmakumar S.
• Vivek Agarwal
• Kallol Roy

Keywords:

• DC motor model
• Fault detection and diagnosis Kalman Filter
• Unscented Kalman Filter

References:

[1] Nandi S.,Toliyat H.A, Ziaodong Li, "condition monitoring and
fault diagnosis of electrical machines - a review," in IEEE trans. on
Energy Conv, vol. 20, no. 4, pp. 709-729, Dec. 2005.
[2] Matlab® LTI models, control system tool box documentation.
[3] Peter. S Maybeck,- Stochastic models-estimation and control- vol.
1, Academy press, New York, 1982.
[4] Grewal M. S and Andrews A. P, ÔÇÿKalman Filtering theory and
practice-, book by Englewood Cliffs, Prentice Hall, 1993.
[5] J. Prakash, S.C. Patwardhan, S. Narasimhan, "A supervisory
approach to fault tolerant control of linear multivarioable systems",
Ind. Eng. Chem. Res, vol.. 41, pp. 2270-2281, 2002
[6] R.Isermann, Fault -Diagnosis Systems, An introduction from Fault
detection to Fault Tolerance, book, pp. 210-214, Springer, 2006.