Research on Defect Detection of Electric Energy Metering Box Based on YOLOv5

The manual inspection for the damage state of the electric energy metering box consumes a lot of time, the workload is large, and the data storage is difficult. In order to solve these problems, this paper proposes an automatic detection method for the damage state of the electric energy metering box based on the YOLOv5 algorithm. The actual metering box pictures taken by the operation and maintenance inspectors are used as the training set, LabelImage is used to annotate the data set, and YOLOv5s model is used to train the data set. The experimental results show that the method proposed in this paper can accurately mark the position of the metering box lid and accurately predict its damage state. The average accuracy reaches 98%, which can meet the requirements for the detection accuracy of the power metering box damage state in the operation and maintenance inspection work.

Intelligent Test Platform for Power Metering System Software

In order to meet the requirements of the operation and maintenance personnel for the power metering system software, when updating the software version, they can independently, quickly and effectively control the quality of the software, an intelligent test platform is designed. Based on the platform, the software operation and maintenance personnel can simply select the corresponding records from the test scripts, test cases and automatic test tools in database debugged by the third-party test team, create the test plan, click the execute button, the platform will automatically connect the selected test tool, intelligently generate a set of executable command lines, to complete the functionality or performance test of the software using the selected test script and test case, and to create the reports of software defects, then a software development team repairs the defects and then the personnel performs regression testing until the new version meets the requirements.