Abstract
In the era of big data, transportation and inspection data of power transmission and transformation equipment are characterized by diversity and richness. Massive data provide data support for state assessment of power transmission and transformation equipment, but at the same time, higher requirements are put forward for traditional data management and data quality model. How to clean the errors and invalid data in the transportation and inspection data, how to effectively repair the missing data, establish the data quality evaluation model, and improve the quality of the transportation and inspection data of the transmission and transformation equipment are of great significance to the equipment status evaluation.. For the acquired data, this paper carries out preliminary cleaning work on the data, and carries out preliminary cleaning on the data through time series analysis and other technologies to ensure the validity, consistency and integrity of the data.
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