The high-voltage circuit breakers generally use hydraulic operating mechanisms in power systems.The mechanical life is the basis for evaluating the reliability and stability of circuit breakers.In this paper

the data-driven method is proposed to establish the mathematical mapping relationship between the degradation process and the characteristic parameters.Realize the mechanical life prediction of the hydraulic operating mechanism of the high voltage circuit breaker.Based on Hadoop+Spark platform and its ecological components

the data is collected and stored in the distributed file system HDFS in Hadoop and the Spark computing framework is used to process the data.Combined with the regression algorithm in the Spark ML machine learning library

the model is trained and verified.From the evaluation results:The RMES of the model of generalized linear regression is 52.96

the R-square coefficient is 0.92

it shows the deviation between the predicted value and the actual value is small

and the fitting effect is better

which is the best compared with other regression algorithm models.Finally

the optimal model and its parameters are obtained.Based on this

the optimal time for maintenance and repair of the high-voltage circuit breaker is determined

which is of great significance for effectively protecting the operational reliability

safety and economy of the high-voltage circuit breaker.