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Multiple power quality events recognition and classification based on adaptive Eigen-based type-2 fuzzy logic algorithm

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Abstract

This work proposes an Eigen-based type-2 fuzzy algorithm for analysis of power signal disturbances. The power quality disturbances are random and non-linear by nature so the role of a particle filter is to estimate various parameters such as amplitude and phase. Particle filtering is now the most popular for tracking and signal processing. It has gained popularity in the signal processing by virtue of its ability to deal with non-linear and non-Gaussian systems.Our approach is to define an orthogonal matrix, for multiple power quality events then to evaluate Eigen values of estimated parameters. These Eigen values play an important role in detection of power quality events the estimated parameters and Eigen values applied as input to type-2 fuzzy for classification of power quality events. Finally robustness of algorithm in terms of improved accuracy and correctness with actual industrial data set of power quality events is compared under three different SNR conditions of 30, 20 and 10 dB with support vector machine, neural network based techniques and type-1 fuzzy logic based classification methods. High accuracy and less computation time make this algorithm robust and a suitable choice for non-linear and non-stationary power quality events analysis.

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  1. Delhi Technological University, Bawana Road, Delhi, India

    Rahul

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Rahul Multiple power quality events recognition and classification based on adaptive Eigen-based type-2 fuzzy logic algorithm. Iran J Comput Sci 5, 55–68 (2022). https://doi.org/10.1007/s42044-021-00088-0

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