Application of model-based fault detection to a brushless DC motor
Moseler, O.; Isermann, R.
Industrial Electronics, IEEE Transactions on
Volume 47, Issue 5, Oct 2000 Page(s):1015 - 1020
Digital Object Identifier 10.1109/41.873209
Summary:In comparison to classical DC motors, brushless DC motors are very
reliable, Nevertheless, they can also fail, caused by, e.g., overheating
or mechanical wear. This paper proposes a parameter estimation technique
for fault detection on this type of motor. Simply by measuring the
motor's input and output signals, its parameters can be estimated. This
method is based on a mathematical model of the process. In the presented
work, a square-wave motor is considered. An appropriate model is
derived. To be able to implement the method also on low-cost
microcontroller-based control units, only the power inverter supply
voltage, DC current, and the motor's angular velocity have to be
measured. The parameter estimation technique provides information about
the electrical resistance and the back-EMF constant as well as about the
mechanical parameters. Comparing the nominal with the computed
parameters, faults can be detected. The approach might be applied to
both end-of-line and online fault detection. Results for simulated data
demonstrate the capabilities of the proposed procedure. Finally, a
real-world application-an actuation system with a brushless DC motor
mounted to a gearbox-is given
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