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Inspection robots are widely used in the field of smart grid monitoring insubstations, and partial discharge (PD) is an important sign of the insulationstate of equipments. PD direction of arrival (DOA) algorithms usingconventional beamforming and time difference of arrival (TDOA) requirelarge-scale antenna arrays and high computational complexity, which make themdifficult to implement on inspection robots. To address this problem, a noveldirectional multiple signal classification (Dir-MUSIC) algorithm for PDdirection finding based on signal strength is proposed, and a miniaturizeddirectional spiral antenna circular array is designed in this paper. First, theDir-MUSIC algorithm is derived based on the array manifold characteristics.This method uses strength intensity information rather than the TDOAinformation, which could reduce the computational difficulty and therequirement of array size. Second, the effects of signal-to-noise ratio (SNR)and array manifold error on the performance of the algorithm are discussedthrough simulations in detail. Then according to the positioning requirements,the antenna array and its arrangement are developed, optimized, and simulationresults suggested that the algorithm has reliable direction-finding performancein the form of 6 elements. Finally, the effectiveness of the algorithm istested by using the designed spiral circular array in real scenarios. Theexperimental results show that the PD direction-finding error is 3.39{\deg},which can meet the need for Partial discharge DOA estimation using inspectionrobots in substations.

Dir-MUSIC Algorithm for DOA Estimation of Partial Discharge Based on Signal Strength represented by Antenna Gain Array Manifold