AbstractIt is of important to recognize the mechanical fault for extra-high voltage Circuit Breakers (CBs) in GIS, when the condition monitoring of CBs is realized. In this paper, a new efficiency fault recognition method is provided, by using improved Support Vector Machines (LibSVMs). The recognition methods, ANN and LibSVM are compared on their recognition accuracy, and the results show that the LibSVM is more efficient than ANN. The algorithm of LibSVM is improved by using Genetic Algorithm (GA), and the GA-LibSVM can obtain higher recognition accuracy than usual LibSVM for mechanical fault recognition of CB
Power system disturbances are often caused by faults on transmission lines. When faults occur in a p...
The mechanical fault diagnosis results of the high voltage circuit breakers (HVCBs) are mainly deter...
[EN] This paper presents a support vector machine classifier for broken bar detection in electrical ...
AbstractIt is of important to recognize the mechanical fault for extra-high voltage Circuit Breakers...
The development of power grid system not only increases voltage and capacity, but also increases pow...
Mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) based on vibration signal analys...
Mechanical faults of high voltage circuit breakers (HVCBs) are one of the most important factors tha...
High voltage circuit breakers (HVCB) are significant protection and control devices for electric sys...
Mechanical fault diagnosis of a circuit breaker can help improve the reliability of power systems. T...
In this paper, an improved method based on HOG-SVM (histogram of oriented gradient characteristic an...
This paper presents a genetic algorithm (GA)- support vector machine (SVM) hybrid classifier for mul...
Abstract This paper proposes a novel scheme for detecting and classifying faults in stator windings ...
In power system networks, automatic fault diagnosis techniques of switchgears with high accuracy and...
In order to improve the identification accuracy of the high voltage circuit breakers’ (HVCBs) mechan...
With the wide applications of the asynchronous induction motor (IM), various kinds of the electrical...
Power system disturbances are often caused by faults on transmission lines. When faults occur in a p...
The mechanical fault diagnosis results of the high voltage circuit breakers (HVCBs) are mainly deter...
[EN] This paper presents a support vector machine classifier for broken bar detection in electrical ...
AbstractIt is of important to recognize the mechanical fault for extra-high voltage Circuit Breakers...
The development of power grid system not only increases voltage and capacity, but also increases pow...
Mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) based on vibration signal analys...
Mechanical faults of high voltage circuit breakers (HVCBs) are one of the most important factors tha...
High voltage circuit breakers (HVCB) are significant protection and control devices for electric sys...
Mechanical fault diagnosis of a circuit breaker can help improve the reliability of power systems. T...
In this paper, an improved method based on HOG-SVM (histogram of oriented gradient characteristic an...
This paper presents a genetic algorithm (GA)- support vector machine (SVM) hybrid classifier for mul...
Abstract This paper proposes a novel scheme for detecting and classifying faults in stator windings ...
In power system networks, automatic fault diagnosis techniques of switchgears with high accuracy and...
In order to improve the identification accuracy of the high voltage circuit breakers’ (HVCBs) mechan...
With the wide applications of the asynchronous induction motor (IM), various kinds of the electrical...
Power system disturbances are often caused by faults on transmission lines. When faults occur in a p...
The mechanical fault diagnosis results of the high voltage circuit breakers (HVCBs) are mainly deter...
[EN] This paper presents a support vector machine classifier for broken bar detection in electrical ...