Research of Motor Fault Diagnosis by Detecting Dynamic Model Parameters

Abstract:

A diagnosis ellipsoid equation is put forward in order to solve motor fault on-line diagnosis. It is first to estimate the motor dynamic model parameters by the on-line least squares estimation, then to detect the parameters changes in the system model, and last to identify t the parts of the system failure occurred and factors. Through a practical example of the application to diagnose a motor fault, the motor fault can be detected according to the parameter changes of the motor model, and the failure factors can be diagnosed by using the diagnosis equation. It is proved feasible and effective.

• Periodical: Applied Mechanics and Materials (Volumes 44-47)
• Pages: 3716-3720
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.44-47.3716
• Online since: December 2010
• Authors: Jian Xiong Long
• Keywords: Motor Dynamic Model, Motor Fault Diagnosis, Motor Model Detection Equation, System Model Identification

References

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[2] R. A. Johnson and D. W. Wichen, Applied Multivariate Statistical Analysis [M], Pearson Education Inc., (2007).

[3] Jianxiong Long, Implementation of Motor Electromagnetic Noise Detection by Mutual Induction [J], 2010 2nd International Conference on Signal Processing Systems (ICSPS 2010), 2010, Vol. 3 pp.298-300.

DOI: 10.1109/icsps.2010.5555807