Embedded Instrumentation for Smart Grid Equipment’s Condition Monitoring

Embedded Instrumentation for Smart Grid Equipment’s Condition Monitoring

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2015 by IJETT Journal
Volume-22 Number-11
Year of Publication : 2015
Authors : S.Thiyagarajan, K.Deepa
DOI :  10.14445/22315381/IJETT-V22P303

Citation 

S.Thiyagarajan, K.Deepa"Embedded Instrumentation for Smart Grid Equipment’s Condition Monitoring", International Journal of Engineering Trends and Technology (IJETT), V22(11),508-512 April 2015. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
Renewable energy sources (RES) have been into prominence all over the world and wind energy is the most developed energy sources in RES. This research develops an induction motor fault diagnosis system during electricity production using Park Vector and Virtual instrumentation approach. Generally, it is very difficult to diagnose a machine fault by conventional methods based on mathematical models because of system complexity and the existence of nonlinear factors. In this research, Virtual instrumentation technology is applied to the fault diagnosis of the machine. By the learning of normal and abnormal states of the object system, a new-method with Virtual instrumentation is involved which can diagnose a fault of the machine. The fault diagnosis system is based on the park vector analysis of the signal from the operating machine. Under any abnormal condition in working of machines, these patterns get changed. The amount of variation can be detected and the nature of abnormalities can be analysed with the help of Virtual instrumentation to get an idea about the fault in the machine. The variation between normal and abnormal data becomes clearer by comparing park vector components data. It is suitable for the detection of the fault to utilize changes in data. Using this method, it is shown that it can detect unknown fault patterns. Through these results, the effectiveness of the fault diagnosis system is verified. The amount of deviation can be detected and the nature of abnormalities can be analysed with LabVIEW to get an idea about the fault in the machine.

 References

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Keywords
Condition Monitoring, Wind Farms, Smart grid, Park vector approach, Virtual Instrumentation, LabVIEW.