Safety monitoring of power industrial control terminals based on data cleaning

Stable and high-quality electric energy is the main driving force for the development of social science, technology, and the national economic leap. The assessment and monitoring of electrical safety rely on the generation, collection and statistics of large amounts of data by the power system. For the possible problems and impurities in these data, this paper uses the 'local Chebyshev theorem' and the 'near data averaging method' for the attribute values. The error is cleaned, and the 'sorting neighbor algorithm' is used to clean the duplicate data, thereby improving the data quality and realizing the accuracy of the safety monitoring of the power grid of the smart grid.