Status evaluation of electric energy metering device (EEMD) based on artificial intelligence technology

Ke Zheng; Mo Zhou; Yongle Zhang

doi:10.1117/12.2662643

16 December 2022 Status evaluation of electric energy metering device (EEMD) based on artificial intelligence technology

Ke Zheng, Mo Zhou, Yongle Zhang

Author Affiliations +

Proceedings Volume 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022); 125006A (2022) https://doi.org/10.1117/12.2662643
Event: 5th International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 2022, Chongqing, China

Abstract

In the context of social development and economic growth, whether it is an electricity supplier or a customer, the requirements for the accuracy and reliability of metering are getting higher and higher in the decision-making process of the electricity meter business. Once a measurement error occurs, it will directly affect the fairness of the trade agreement between the two parties. Therefore, it is very important to study the device state of the electric meter. The main purpose of this paper is to study the state evaluation of electric EEMDs based on artificial intelligence technology. In this paper, a complete state index hierarchy model is established to evaluate the state of the electric EEMD comprehensively and objectively. Finally, simulation tests are carried out on the fault diagnosis and condition assessment software system of electric EEMD in terms of the accuracy of fault diagnosis and condition assessment. The simulation results show that the system can reasonably and effectively diagnose and evaluate the faults and operating states of various electric EEMDs, and has good practical performance.

Citation Download Citation

Ke Zheng, Mo Zhou, and Yongle Zhang "Status evaluation of electric energy metering device (EEMD) based on artificial intelligence technology", Proc. SPIE 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 125006A (16 December 2022); https://doi.org/10.1117/12.2662643

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