Detection of DC Voltage Fault in SRM Drives Using K-Means Clustering and Classification with SVM

Journal Title: International Journal of Modern Engineering Research (IJMER) - Year 2014, Vol 4, Issue 1

Abstract

This paper presents a new method of detection of DC voltage fault in SRM drives based on K Means Clustering technique. Also the range of fault is classified using Support Vector Machines (SVM). Switched reluctance motors are very popular in these days, because of ease in manufacturing and operation. Though an electronic circuit can detect the fault like under voltage and over voltage but, the classification cannot be done effectively with electronic circuitry. More over an intelligent method can easily identify the fault and classify and hence the root cause of the fault may be guessed and rectified using this method of classification. The information used to include this intelligence in the system are just torque waveforms. Moreover, the early detection minimizes the faulty operation time and ensures the plant stability and saves the life of motor too. Hence a system to detect such fault under a simulation model has been proposed in this study

Authors and Affiliations

V. Chandrika

Keywords

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  • EP ID EP88140
  • DOI -
  • Views 157
  • Downloads 0

How To Cite

V. Chandrika (2014). Detection of DC Voltage Fault in SRM Drives Using K-Means Clustering and Classification with SVM. International Journal of Modern Engineering Research (IJMER), 4(1), 38-42. https://europub.co.uk/articles/-A-88140