This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system. Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can...
Synchronous generators are considered the most important part in power generation equipment, hence p...
This paper proposes a fault location method employing wavelet fuzzy neural network to use post-fault...
Underground cables are being faced with a wide variety of faults due to underground conditions, wea...
This paper presents a fault identification, classification and fault location estimation method base...
This paper presents a fault identification, classification and fault location estimation method base...
AbstractThis paper presents an accurate algorithm for locating faults in a medium voltage undergroun...
This paper presents an accurate algorithm for locating faults in a medium voltage underground power ...
Transmissionlinesare thebackboneof electricalpower systems and other power utilities as they are use...
In the past decade, electricity demand has increased rapidly in metropolitan areas. All over the wor...
A novel method to locate the zone of transient faults and to classify the fault type in Power Distri...
This thesis presents a novel approach to automating Time Domain Reflectrometry (TDR) waveform acquis...
This paper presents an improved approach for locating and identifying faults for UHV overhead Transm...
This paper describes a method of Adaptive Neuro Fuzzy Inference System (ANFIS) for identifying and l...
A quick, reliable, and accurate fault location approach is essential in underground power systems pr...
Synchronous generators are considered the most important part in power generation equipment, hence p...
This paper proposes a fault location method employing wavelet fuzzy neural network to use post-fault...
Underground cables are being faced with a wide variety of faults due to underground conditions, wea...
This paper presents a fault identification, classification and fault location estimation method base...
This paper presents a fault identification, classification and fault location estimation method base...
AbstractThis paper presents an accurate algorithm for locating faults in a medium voltage undergroun...
This paper presents an accurate algorithm for locating faults in a medium voltage underground power ...
Transmissionlinesare thebackboneof electricalpower systems and other power utilities as they are use...
In the past decade, electricity demand has increased rapidly in metropolitan areas. All over the wor...
A novel method to locate the zone of transient faults and to classify the fault type in Power Distri...
This thesis presents a novel approach to automating Time Domain Reflectrometry (TDR) waveform acquis...
This paper presents an improved approach for locating and identifying faults for UHV overhead Transm...
This paper describes a method of Adaptive Neuro Fuzzy Inference System (ANFIS) for identifying and l...
A quick, reliable, and accurate fault location approach is essential in underground power systems pr...
Synchronous generators are considered the most important part in power generation equipment, hence p...
This paper proposes a fault location method employing wavelet fuzzy neural network to use post-fault...
Underground cables are being faced with a wide variety of faults due to underground conditions, wea...