Performance study of the acoustic detection algorithm for the local discharge model

This paper designs a set of acoustic detection system based on high-performance 80-channel multi-arm spiral microphone array based on the application of acoustic imaging technology in local discharge detection of power equipment. Through the combination of theoretical analysis, simulation and experimental verification, DAMAS2 (CBF), DAMAS2 and OMP-DAMS. The results show that although CBF algorithm can achieve basic discharge position positioning, its spatial resolution is relatively poor; DAMAS2 algorithm has improved resolution, but still has low computational efficiency. In contrast, OMP-DAMAS algorithm performs excellent in terms of resolution, positioning accuracy and calculation efficiency. Especially in the context of complex environment, it can more accurately identify the local discharge position, and the calculation speed is fast, which is suitable for real-time detection system. The research results of this paper provide an effective acoustic imaging algorithm and its practical scheme for the accurate detection of local discharge of power equipment, which has high application value and promotion prospect.