A Support Vector Machine Based Approach to Real Time Fault Signal Classification for High Speed BLDC Motor

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 736)

Abstract

In this paper we propose a new methodology for designing an intelligent incipient fault signal classifier. This classifier can classify the fault signal. The design has been validated to a sate observer which indicates the valve controller output signal and communicate the health status of the embedded processor based valve controller in right time without any false alert signal to the actuator through FPGA processor. This has been achieved by using an SVM-based classifier and time duration based state machine modeling. The design methodology of a fault aware controller using one against all strategy is selected for classification tool due to good generalization properties. Performance of the proposed system is validated by applying the system to induction motor faults diagnosis. Experimental result for BLDC motor (which is mostly used for aircraft) valve controller, and computer simulations indicate that the proposed scheme for intelligent control based on signal classification is simple and robust, with good accuracy.

Keywords

Cyber physical system Short Term Fourier Transform (STFT) Support Vector Machine (SVM) Intelligent control Fault signal classifier 

Notes

Acknowledgement

The author is thankful to Embedded System Lab of CMERI, Durgapur for giving support to his work in experimental setup and funding support to continue his research.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.B. C. Roy Engineering CollegeDurgapurIndia
  2. 2.Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research ExcellenceAuburnUSA

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