In order to assess the substation equipment operation security condition effectively and adapt to the trends of high capacity

high voltage

structure diversification

seal and condition-based maintenance. Based on group difference method of interval matter-element extension principle

cloud model and grey model

two level comprehensive evaluation model transformer based on multi-source information is established to determine the transformer trend prediction of single factor index evaluation and the overall state evaluation of specific solutions.In the two-stage

the top oil temperature

winding hot spot temperature and load capacity calculation are utilized to evaluate comprehensive relative deterioration degree and get the natural mode and accelerate the degradation model of comprehensive evaluation score. In the comprehensive evaluation

statistical models are used to get the bad working condition and the reliability of running state to supplement

load capacity and fault prediction model is established for the first time

to modify the transformer running state. The model overcomes the defects and deficiencies of the traditional state evaluation method

improves the accuracy of the state assessment

and has good guidance for other substation equipment’s condition evaluation processes. The analysis results coincide with the actual situation of the transformer.