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Detection and Classification of Power Quality Disturbances Using Discrete Wavelet Transform and Rule Based Decision Tree


Affiliations
1 Department of Electronics and Communication Engineering, Government Engineering College Jhalwar, Rajasthan, India
2 Government Engineering College Baran, Rajasthan, India
     

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This paper presents a method for the detection and classification of power quality (PQ) disturbances using discrete wavelet transform (DWT) based decision tree. The power quality disturbances are generated with the help of MATLAB using the mathematical relations as per IEEE Standard-1159. The investigated PQ disturbances include pure sine wave, voltage sag, voltage swell, momentary interruption, harmonics, oscillatory transient, impulsive transient and notch. These power quality signals are decomposed using discrete wavelet transform with db4 as mother wavelet up to third level of decomposition. The detail coefficients and approximation coefficients are used for the detection of PQ disturbances. The features extracted from these coefficients are fed to the rule-based decision tree for classification purpose. The effectiveness of proposed algorithm has been established by testing the 30 data sets of each PQ disturbance obtained by varying the parameters.

Keywords

Discrete Wavelet Transform, Power Quality, Rule Based Decision Tree.
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  • Detection and Classification of Power Quality Disturbances Using Discrete Wavelet Transform and Rule Based Decision Tree

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Authors

Nitin Kumar Suyan
Department of Electronics and Communication Engineering, Government Engineering College Jhalwar, Rajasthan, India
Mahendra Kumar
Government Engineering College Baran, Rajasthan, India
Fateh L. Lohar
Department of Electronics and Communication Engineering, Government Engineering College Jhalwar, Rajasthan, India

Abstract


This paper presents a method for the detection and classification of power quality (PQ) disturbances using discrete wavelet transform (DWT) based decision tree. The power quality disturbances are generated with the help of MATLAB using the mathematical relations as per IEEE Standard-1159. The investigated PQ disturbances include pure sine wave, voltage sag, voltage swell, momentary interruption, harmonics, oscillatory transient, impulsive transient and notch. These power quality signals are decomposed using discrete wavelet transform with db4 as mother wavelet up to third level of decomposition. The detail coefficients and approximation coefficients are used for the detection of PQ disturbances. The features extracted from these coefficients are fed to the rule-based decision tree for classification purpose. The effectiveness of proposed algorithm has been established by testing the 30 data sets of each PQ disturbance obtained by varying the parameters.

Keywords


Discrete Wavelet Transform, Power Quality, Rule Based Decision Tree.

References