Main transformer big data preprocessing method based on big data analysis platform

Data processing is carried out on current, voltage, active power and reactive power, extracted from a dispatching automation system, of a main transformer, and the data processing comprises repeated data detection and processing, abnormal data detection and processing, local outlier detection and processing and data integrity detection and processing. And the problems of noise, abnormity, missing, repetition and the like in current, voltage, active power and reactive power of the operation data of the main transformer can be solved. The data quality is improved through big data preprocessing, standard, continuous and accurate mass data are obtained, and efficiency and accuracy are improved for follow-up main transformer big data mining analysis. Meanwhile, time continuity and priori, namely relevance of moments before and after monitoring data of the main transformer, are considered during missing data complementation, so that calculation is performed in a weight summation mode, the trend of a monitoring curv