Failure data without exact observed failure time of equipment is referred to as censored data. Aiming at the characteristics of censored failure data of protective equipment under the background of big data,a method for evaluating the operating life of protective equipment considering censored data under the background of big data is proposed. Firstly,based on analyzing failure-data features of protective equipment,the failure data were preprocessed. By combining the expectation-maximization (EM) algorithm with the exponential distribution model and the weibull distribution model,failure model parameters of protective equipment were estimated. Secondly,the estimated parameters are substituted into the failure model to obtain reliability indices,such as the reliability,failure probability density,failure rate,and meantime between failures. Subsequently,through simulation study,the estimation accuracy of model parameters in accidental-failure and aging-failure periods obtained by different methods was comparatively analyzed,and the effectiveness of the proposed method for processing censored data was verified. Finally,taking a certain type of protective equipment as an example to investigate reliability indices,the feasibility of applying this method to plan equipment maintenance cycle is verified.