Research on Intelligent Fault Diagnosis Method and Model for Power Acquisition Equipment

As the application of power consumption information collection system continues to deepen, the business scope continues to expand, and the functional applications continue to increase, the number of metering and collection equipment accessed by State Grid Corporation's power consumption information collection system is increasing in scale, the operating environment is complex, and the types of faults are varied, which leads to more and more pressure on troubleshooting work. As the requirements of grid operation on the stability and reliability of metering and collection equipment continue to improve, the frequency of data collection and data quality requirements have been further strengthened. The existing abnormality monitoring and diagnostic model can no longer meet the data analysis application requirements of metering device condition detection, collection system efficient operation and maintenance, and equipment quality evaluation. This paper is based on the main station of the power consumption information collection system collection data and anomaly diagnosis function, through further collection of collection anomaly impact factor, combined with remote fault intelligent diagnosis and manual diagnosis, comprehensive collection fault intelligent diagnosis methodology modeling research, to achieve the collection of anomalies intelligent perception, collection fault precision research and judgment, qualitative analysis of equipment faults and early warning and other expected goals, to provide guidance for the first-line staff on-site operation and maintenance, to achieve Reduce the difficulty of operation and maintenance, and improve the quality