scholarly journals Power Quality Disturbances Detection and Classification Rule-Based Decision Tree

2021 ◽  
Vol 17 ◽  
pp. 22-27
Author(s):  
Fouad R. Zaro

In this paper, the power quality (PQ) disturbances have been detected and classified using Stockwell’s transform (S-transform) and rule-based decision tree (DT) according to IEEE standards. The proposed technique based on the extracted features of the PQ events signals, which are extracted from the timefrequency analysis. Several PQ disturbances are considered with simple and complex disturbances to include spike, flicker, oscillatory transient, impulsive transient, and notch. The performance and robustness of the proposed technique for the recognition of PQ disturbances have been demonstrated through the results of the various disturbances. By comparing the performance of the proposed technique with other reported studies it was distinguished results under noiseless and noisy conditions

2015 ◽  
Vol 51 (2) ◽  
pp. 1249-1258 ◽  
Author(s):  
Raj Kumar ◽  
Bhim Singh ◽  
D. T. Shahani ◽  
Ambrish Chandra ◽  
Kamal Al-Haddad

2013 ◽  
Vol 860-863 ◽  
pp. 1891-1894
Author(s):  
Ji Liang Yi ◽  
Ou Yang Qin

A novel method for power quality disturbances classification is presented using modified S transform (MST) and decision tree. The time-frequency properties of power quality disturbances are analyzed and the effects of window-wide parameter g on the properties are discussed. Four statistical features are extracted from the MST module time-frequency matrix and a decision tree is utilized to recognize 9 power quality disturbances. The simulations are made to illustrate the validity of the method proposed for power quality disturbances recognition.


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