Online Monitoring of Converter Station Using an Acoustic Signal Analysis Method Based on The Mobile Microphone Array

An abundance of operational status signals can be found in the acoustic signals produced by power equipment in high-voltage converter stations. For the intelligent development of power grids, the use of acoustic signals for online monitoring of power equipment in converter stations to detect the location of faults has become crucial. A beamforming algorithm based on a mobile microphone array is suggested in this paper for high-voltage converter stations in order to quickly localize target acoustic sources. The algorithm links the movement of the microphone with the location of the sound source in the frequency domain by translating the short-time Fourier variation. As a result, the movement of the array element is one of the variables used in the localization algorithm, allowing the localization of the sound source with a minimal number of microphone array elements. Finally, simulation experiments using the results of field test data are used to show the efficacy and accuracy of the algorithm for locating the fault locations of significant power equipment in high-voltage converter stations.