Abstract: Aiming at the problem that the health status of circuit breaker operation cannot be accurately assessed and predicted, a method based on big data analysis of power grid operation monitoring is proposed, which analyzes and evaluates the real-time health risk of circuit breaker, deduces the future health situation, and uses the results to evaluate the operation risk of the power grid. Through Apriori algorithm, the multi-dimensional, multi-source and unstructured data affecting the health status of circuit breakers are analyzed at feature points, and the health status of circuit breakers is comprehensively analyzed and deduced by establishing a familial health risk analysis model, a health risk analysis model for operating life, and a health risk analysis model affected by external factors. Through the analysis of power grid faults that may be caused by circuit breaker defects, the assessment of power grid operation risks is realized. Taking the power grid in a certain region as an example, the results show that based on the big data analysis and deduction of the health status of the circuit breaker and the overall assessment of the power grid risk, the risks existing in the circuit breaker and the power grid and the impact scope of the risks can be found in advance, which is conducive to ensuring the safe and stable operation of the power grid.