Classification of abnormal location in medium voltage switchgears using hybrid gravitational search algorithm-artificial intelligence.

ABSTRACT: In power system networks, automatic fault diagnosis techniques of switchgears with high accuracy and less time consuming are important. In this work, classification of abnormal location in switchgears is proposed using hybrid gravitational search algorithm (GSA)-artificial intelligence (AI) techniques. The measurement data were obtained from ultrasound, transient earth voltage, temperature and sound sensors. The AI classifiers used include artificial neural network (ANN) and support vector machine (SVM). The performance of both classifiers was optimized by an optimization technique, GSA. The advantages of GSA classification on AI in classifying the abnormal location in switchgears are easy implementation, fast convergence and low computational cost. For performance comparison, several well

SUBMITTER: Illias HA 

PROVIDER: S-EPMC8248718 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature