A rule-based S-Transform and AdaBoost based approach for power quality assessment

2016 ◽  
Vol 134 ◽  
pp. 66-79 ◽  
Author(s):  
Motakatla Venkateswara Reddy ◽  
Ranjana Sodhi
Keyword(s):  
Quality Assessment ◽  
Power Quality ◽  
Rule Based ◽  
S Transform

Recognition of Power-Quality Disturbances Using S-Transform-Based ANN Classifier and Rule-Based Decision Tree

2015 ◽  
Vol 51 (2) ◽  
pp. 1249-1258 ◽  
Author(s):  
Raj Kumar ◽  
Bhim Singh ◽  
D. T. Shahani ◽  
Ambrish Chandra ◽  
Kamal Al-Haddad
Keyword(s):  
Decision Tree ◽  
Power Quality ◽  
Rule Based ◽  
S Transform ◽  
Power Quality Disturbances ◽  
Ann Classifier

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

2021 ◽  
Vol 17 ◽  
pp. 22-27
Author(s):  
Fouad R. Zaro
Keyword(s):  
Decision Tree ◽  
Power Quality ◽  
Classification Rule ◽  
Rule Based ◽  
S Transform ◽  
Ieee Standards ◽  
Noisy Conditions ◽  
Power Quality Disturbances

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

Integrated Hardware System for Power Quality Disturbance Classification

2009 ◽  
Vol 10 (2) ◽  
Author(s):  
Azah Mohamed ◽  
Mohamed E. Salem ◽  
Salina Abdul Samad
Keyword(s):  
Power Quality ◽  
Digital Signal Processor ◽  
Digital Signal ◽  
Rule Based ◽  
Rule Based System ◽  
Hardware System ◽  
S Transform ◽  
Power Quality Disturbance ◽  
Network Approaches

Detection and classification of power quality (PQ) disturbances in real-time is an important consideration to electric utilities and many industrial customers so that diagnosis and mitigation of such disturbances can be implemented quickly. This paper presents the design and development of an integrated hardware system for classification of PQ disturbances using the rule based system. A hardware system has been designed using advanced digital signal processor to provide fast data capture and processing of signals using the S-transform analysis. Distinct features of various disturbances are extracted from the S-transform analysis in which these features are used to formulate rules. A rule based expert system is developed to automate the process of classifying the various types of disturbances. The disturbance classification results prove that the developed rule based system is more accurate than the neural network approaches in classifying PQ disturbances such as voltage sag, swell, impulsive transient, notching and interruption.

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