Data recognition method and system

Abstract

The invention provides a data recognition method and a system. The method comprises the following steps: carrying out data conversion on historical electricity consumption data and line loss data, wherein a converted data result satisfies a data model format, and the data model format is set during establishment of a data model; carrying out comparison and analysis on the converted data result and key parameters in basic archival data, and according to an analysis result, carrying out modification on electricity consumption abnormal data in the historical electricity consumption data so as to obtain historical electricity consumption modification data; adjusting the key parameters, carrying out calculation and analysis on the historical electricity consumption modification data according to first adjusted key parameters, and excavating a household with abnormal electricity consumption corresponding to the electricity consumption abnormal data from the historical electricity consumption modification data according to an analysis result. According to the method and system disclosed by the present invention, by excavating the historical electricity consumption modification data, the data value is discovered from massive data, so that the influence of the interference data is effectively eliminated, and the household with abnormal electricity consumption is truly recognized.

Description

technical field [0001] The present invention relates to the field of information technology, more specifically, to a data identification method and system. Background technique [0002] Abnormal electricity consumption analysis refers to the comprehensive judgment of user electricity consumption behavior based on on-site load information of electricity customers, on-site operating condition information, terminal equipment alarm information, etc., including measurement anomaly analysis and electricity theft prevention analysis. , Internal abnormality of electric energy meter, abnormality of metering cabinet and abnormality of switching value, etc. Electricity theft analysis mainly includes undervoltage method, undercurrent method, phase shifting method and differential method, etc. . [0003] In the prior art, event alarm screening analysis is generally used to identify and analyze abnormal power consumption data. However, with the construction of the acquisition system, the...

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Problems solved by technology

[0003] In the prior art, event alarm screening analysis is generally used to identify and analyze abnormal power consumption data. However, with the construction of the acquisition system, the number of smart meters and acquisition terminals on the site is increasing rapidly. The consequence of massive alarm data is that the screening speed is slow. The real abnormal power consumption data is lost in the massive alarm time information. In fact, it is impossible to judge the abnormal power consumption based on the alarm time, and there is a large amount of interference data, which makes the system unable to identify the real power consumption.

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