An on-line anomaly identifying method for calibration devices in an automatic verification system for electricity smart meters

Calibration devices in an automatic verification system are used to verify the accuracy of electricity smart meters. As time goes by, calibration devices may experience the metering performance degradation, making results of error tests biased. Therefore, it is of great significance to ensure calibration devices have qualified metering performance. Conventionally, their performance could only be manually inspected at regular intervals, while keep unknown during the operation. To address this issue, an on-line anomaly identifying method based on calibration devices' parallel working mode is proposed to check their metering performance in real time. Instead of off-line inspections, a device's metering performance is associated with the corresponding results of error tests, and comparisons among distributions based on results corresponding to different calibration devices would provide evidences to identify the ones having metering performance unqualified without interrupting the verification tasks. In addition, a case study is conducted to prove the validity.

Automated summary

This study introduces an online anomaly identifying method based on calibration devices' parallel working mode to check metering performance in real time, avoiding the shortcomings of traditional manual inspections at regular intervals.