With the mature of single phase intelligent electric meter automation detection technology, concentrator and shift acquisition terminal also need to implement automated testing. The current domestic reality for some measuring equipment in the production of automated verification or a link in the test, which still have some technical problems. It combined with the necessary human intervention, virtually increased the cost and certain security hidden danger, make the lost of the role of automation and automated verification or testing is true meaning. However, how to realize the automation of collection terminal detection is mainly to solve the problem. For intelligent electricity information collection system construction, the problems arising from the use and application, put forward to realize the automatic acquisition terminal detection scheme, for the domestic intelligent electricity information acquisition terminal test provide beneficial guidance and reference.
To solve the problem of not being able to intuitively lock the cause of defects when processing massive quality inspection datasets with multiple batches, types, and models of measurement terminals, a MapReduce-based Apriori algorithm is proposed. After the MapReduce algorithm model calculation, the processing efficiency of the quality inspection dataset has been significantly improved. Through the multi-node calculation and analysis of the single-phase electricity meter quality inspection dataset and the application of association rule mining, reasonable suggestions were given, which improved the professional value and quality supervision level of the quality inspection business.
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