Abstract

Intelligent electricity meter represents the development direction of intelligent terminal of energy-saving smart grid end-user in the future. Intelligent electricity meters are widely used in the field, and the development momentum is rapid. In the future, the market demand is more vigorous, and the competition is increasingly fierce. However, in the practical application of electricity meters, faults may occur due to the influence of production enterprises, key components, research and development schemes, quality regulations, age of meters and other factors, even exposed batch quality problems, resulting in measurement disputes and customer complaints. In view of providing power companies and production enterprises with high batch early-warning for intelligent electricity meters to avoid economic losses caused by large-scale failures, based on the statistics of the whole life cycle data of 10 intelligent watt-hour meter manufacturers, this paper analyzes the typical fault types of intelligent watt-hour meter in detail, and obtains the analysis samples and dimensions of the main influencing factors. Based on the analysis method of standard deviation index, the multi-dimensional fault discrete analysis is carried out on the analysis samples, the dimension with the highest dispersion coefficient of fault is mined layer by layer until the smallest element is analyzed, and finally the main influencing factors of fault are obtained. The analysis results are basically consistent with the actual market performance of the production enterprise, which proves the rationality and scientific nature of the set of calculation indexes and discrete analysis method.

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