Abstract
In this paper a modified inverse Stockwell transform has been proposed for the identification of industrial nonlinear loads. The proposed method is based on the maximum values of unfiltered inverse Stockwell Transform termed as MUNIST. It is a well known fact that Stockwell transform technique produces time-frequency representation. As the proposed MUNIST technique is obtained from inverse operation of time-frequency data it gives only time resolution. MUNIST technique found to provide unique signatures for accurate identification of the industrial loads. Later the results obtained using the proposed technique has been used as input to the fuzzy decision box. Using the fuzzy logic design automatic identification of different nonlinear loads has been carried out efficiently and accurately. Current measurements of different industrial loads have been used as the input for the proposed MUNIST algorithm. The results obtained using the proposed technique, have been compared with the existing techniques to show its efficacy.
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Pullabhatla, S., Koley, C. (2015). Fuzzified Inverse S-Transform for Identification of Industrial Nonlinear Loads. In: Satapathy, S., Govardhan, A., Raju, K., Mandal, J. (eds) Emerging ICT for Bridging the Future - Proceedings of the 49th Annual Convention of the Computer Society of India (CSI) Volume 1. Advances in Intelligent Systems and Computing, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-319-13728-5_39
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DOI: https://doi.org/10.1007/978-3-319-13728-5_39
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13727-8
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