In this study, a different application of the signal recognition is presented for classification of source voltage level, which leads to produce corona noise in an experimental set-up, using recorded sound data of corona (electrical discharge) and utilizing probabilistic neural network (PNN). By applying different levels of 50 Hz ac high-voltage, the corona sound data are acquired experimentally from a test set-up intentionally producing corona sound. After successfully recording the sound data, they have been used in training and test sets of the probabilistic neural network. In this context, we can indicate the main objective for our study; to develop a model to determine exact source voltage level by only analyzing the recorded corona sound data. During the application of algorithmic method, linear prediction coefficients are used. It is shown that reasonable results can be obtained by following the proposed method.Index Terms -Corona sound, sound recognition, wavelet transform, probabilistic neural network.
This study presents measuring the magnitude of voltage applied on a HV line without any physical contact with the line by neural network using corona sound data as input of the network. Corona sound data used in this study are acquired from an experimental set-up when applying 50 Hz AC high voltage at different levels to the line conductor. Recorded sound data of corona and the voltage magnitudes are applied to a neural network (NN). To analyze corona sound, linear prediction coefficients are used. It is shown from the results that the proposed method can be used for the measuring voltage magnitude.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.