With the development of smart grid and the rapid expansion of power grid scale

it is very difficult to grasp the operational state of power equipment timely and accurately.In recent years

the informationization of electric power has reached a high level.Data from condition monitoring system

power production management system

operation dispatching system

and environmental meteorology system are gradually integrated and shared.Big data technologies provide new technical methods and tools for power equipment condition assessment and fault diagnosis.We put forward the connotation

purpose

data characteristics

and basic framework for big data analysis of power equipment condition

in consideration of the status quo of big data technology and data mining analysis in power equipment condition assessment.The key techniques of big data integration

conversion

cleaning

distributed storage and processing

data mining with high efficiency

and data-driven analysis model for power equipment condition assessment are comprehensively elaborated.According to the total demand analysis of power equipment condition assessment

the methods and effects of big data techniques in application scenarios such as condition evaluation

anomaly detection

fault prediction and intelligent diagnosis are summarized and discussed.Finally

the major problems in research and application are proposed

and the development trend of the relative technologies is prospected.