The AGV-based substation operation status inspection and monitoring method

Abstract

The current conventional substation operation status inspection monitoring method mainly constructs the operation status judgment index based on the fusion monitoring information to realize the monitoring of equipment. However, this method may lead to poor monitoring effects due to the lack of effective processing of image data. In this regard, the AGV-based substation operation status inspection and monitoring method is proposed to address this problem. By optimizing the mechanical structure and driving method of the AGV intelligent inspection and handling vehicle, and processing the monitoring image data, we can construct the excitation function by combining a deep neural network to realize the judgment of substation operation status. In the experiment, the proposed method is verified for the monitoring effect. The analysis of the experimental results shows that the proposed method has a lower algorithm recall rate and has a more excellent monitoring effect when the proposed method is used to monitor the substation.