Proceedings ArticleDOI
Discrete wavelet transform and Fuzzy Logic algorithm for identification of fault types on transmission line
Pathomthat Chiradeja,Chaichan Pothisarn +1 more
- pp 1-6
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TLDR
Fuzzy logic is compared with the Back-propagation (BP) neural network in this paper and gives a satisfactory accuracy, and will be very useful in the development of a modern protection scheme for electrical power transmission systems.Abstract:
This paper proposes a new technique using discrete wavelet transform (DWT) and Fuzzy Logic in order to identify the fault types on single circuit transmission lines. The mother wavelet daubechies4 (db4) is employed to decompose, high frequency component from these signals. Positive sequence current signals are used in fault detection decision algorithm. The variations of first scale high frequency component that detect fault are used as an input for the fuzzy logic. Fuzzy logic is also compared with the Back-propagation (BP) neural network in this paper. The proposed method gives a satisfactory accuracy, and will be very useful in the development of a modern protection scheme for electrical power transmission systems. (6 pages)read more
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Journal ArticleDOI
Fault Detection and Classification on a Transmission Line using Wavelet Multi Resolution Analysis and Neural Network
Mamta Patel,Ramnarayan Patel +1 more
TL;DR: D discrete wavelet transform of voltage signals at the two ends of the transmission lines have been analyzed and four layer feed forward back propagation neural networks are designed to classify and locate the fault at different single line to ground fault conditions.
Proceedings ArticleDOI
Selection of proper input pattern in fuzzy logic algorithm for classifying the fault type in underground distribution system
TL;DR: The obtained results in term of average accuracy have shown that the maximum ratio of DWT can achieved satisfactory accuracy in fault type classification.
Proceedings ArticleDOI
An Application of Discrete Wavelet Transform and Support Vector Machines Algorithm for Classification of Fault Types on Underground Cable
TL;DR: A new technique using discrete wavelet transform (DWT) and support vector machines (SVM) to classify the fault types in underground distribution systems gives satisfactory accuracy, and will be very useful in the development of a modern protection scheme for electrical power transmission and distribution systems.
A Novel Approach for Fault Diagnosis of Multilevel Inverter Using Dwt and Fuzzy Logic Algorithm
TL;DR: In this article, fault diagnosis is performed using discrete wavelet transform (DWT) and fuzzy logic and valuable features for output voltage signals are extracted by DWT and Fuzzy logic is used for switch fault detection in the last stage.
Proceedings ArticleDOI
Coefficient comparison technique for identifying the fault types in underground cable
Abstract: This paper proposes a novel comparison technique for identifying the phase with fault appearance in underground cable using Discrete Wavelet Transform. The Wavelet transform has been employed to extract high frequency components superimposed on fault signals simulated using ATP/EMTP. The fault type algorithm is constructed on the basis of coefficient comparison from signals decomposed from Discrete Wavelet Transform. Various cases studies based on Thailand electricity distribution underground systems have been investigated so that the algorithm can be implemented. It is found that the proposed method can indicate the fault types with satisfactory accuracy.