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Saini M, Beniwal R. Recognition of Multiple PQ Issues using Modified EMD and Neural Network Classifier. IJEEE. 2018;
URL: http://ijeee.iust.ac.ir/article-1-1074-en.html
Abstract:   (391 Views)
This paper presents a new framework based on modified EMD method for detection of single and multiple PQ issues. In modified EMD, DWT precedes traditional EMD process. This scheme makes EMD better by eliminating the mode mixing problem. This is two step algorithm; in first step, input PQ signal is decomposed in low and high frequency component using DWT. In the second stage, the low frequency component is further processed with EMD technique to get IMFs. Eight features are extracted from IMFs of low frequency component. Features are directly extracted from the high frequency component. All these features form feature vector which is fed to PNN classifier for classification of PQ issues. For comparative analysis of PNN, results are compared with SVM classifier and performance of proposed methodology is also validated with noisy signal. PNN has outperformed SVM for both noiseless and noisy PQ signal.
Full-Text [PDF 3473 kb]   (84 Downloads)    
Type of Study: Research Paper | Subject: Power Quality
Received: 2017/04/01 | Accepted: 2017/12/26 | Published: 2017/12/29