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Information Journal Paper

Title

AN INTELLIGENT METHOD FOR DETECTION AND CLASSIFICATION OF POWER QUALITY EVENTS

Pages

  23-37

Abstract

 This paper presents a new method based on S-TRANSFORM and PROBABILISTIC NEURAL NETWORK (PNN) for detection of POWER QUALITY disturbances. Since POWER QUALITY disturbances are nonstationary signals, S-TRANSFORM can analyze these events in both time and frequency domains, effectively. The PNN is trained by extracted features obtained from S-TRANSFORM output. This new method can reduce distinguished features of disturbed signals without loss of main characteristics of signals, hence required time and memory for data training process decrease. On the other hand the PNN classifier does not need any time consuming training process and only one parameter (smoothing factor) is needed to be set. This parameter has a great impact on classifier accuracy, thus an evolutionary search algorithm i.e. PARTICLE SWARM OPTIMIZATION (PSO) is used for precise setting of this parameter. Simulation results show that the combination of S transform and PNN can classify POWER QUALITY events, effectively. The operation of proposed algorithm has been evaluated in noisy condition and the obtained results show the less sensitivity of the proposed method in the presence of noise.

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  • Cite

    APA: Copy

    MORAVEJ, Z., ABDOOS, A.A., & PAZOKI, M.. (2012). AN INTELLIGENT METHOD FOR DETECTION AND CLASSIFICATION OF POWER QUALITY EVENTS. JOURNAL OF MODELING IN ENGINEERING, 9(27), 23-37. SID. https://sid.ir/paper/173769/en

    Vancouver: Copy

    MORAVEJ Z., ABDOOS A.A., PAZOKI M.. AN INTELLIGENT METHOD FOR DETECTION AND CLASSIFICATION OF POWER QUALITY EVENTS. JOURNAL OF MODELING IN ENGINEERING[Internet]. 2012;9(27):23-37. Available from: https://sid.ir/paper/173769/en

    IEEE: Copy

    Z. MORAVEJ, A.A. ABDOOS, and M. PAZOKI, “AN INTELLIGENT METHOD FOR DETECTION AND CLASSIFICATION OF POWER QUALITY EVENTS,” JOURNAL OF MODELING IN ENGINEERING, vol. 9, no. 27, pp. 23–37, 2012, [Online]. Available: https://sid.ir/paper/173769/en

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