Fault Analysis of Magnetic Bearing Displacement Sensor Based on FPGA Adaptive Filter

doi:10.11985/2018.08.001

Abstract

Abstract:

According to the active magnetic bearing equipped with different displacement sensors, the relationship between the fault signal of eddy current displacement sensors and the output signal of the controller is studied. The characteristics of the output of the displacement sensor and the output of the controller are analyzed in the event of failure of the different probe. The principle of adaptive filtering is introduced, and then a sensor fault diagnosis method based on the adaptive filtering is proposed. The method uses the difference between the two sensor output signals as the reference signal to filter the output signal of the controller to obtain the correlation coefficient between the controller output signal and the difference signals between the two sensors, so that the polarity of the correlation coefficient can be judged accurately faulty sensor. The simulation is carried out by Matlab, and the experimental results are verified by the adaptive filter based on field-programmable gate array (FPGA). The results show that the method can detect the sensor fault and identify the fault sensor accurately.

Key words: Eddy current displacement sensor, field-programmable gate array, adaptive filtering, fault diagnosis

CLC Number:

TM571

Zong Ming Feng,Chao Zheng, . Fault Analysis of Magnetic Bearing Displacement Sensor Based on FPGA Adaptive Filter[J]. Journal of Electrical Engineering, 2018, 13(8): 1-6.

Figures/Tables 7

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