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The existing reliability evaluation methods of storage systems are difficult to describe its reliability characteristics dynamically, and it is difficult to reflect its relationship with time. To solve this problem, a method combining Z language, continuous-time Markov chain and Bayesian network is proposed. This method abstracts the storage system into two levels, which are divided into two parts, functional unit and storage system as a whole. When evaluating the reliability of functional units, a reliability model based on Z language is established. Since its state transition with respect to time conforms to the properties of the Markov chain, a continuous-time Markov chain is introduced for evaluation. In order to more clearly express the multi-state relationship between the storage system and each functional unit, the functional unit failure rate and The Bayesian network between the overall failure rates of the storage system. The overall reliability of the storage system is calculated based on the Bayesian network, and the key reliability modules are obtained. Finally, through the example analysis and calculation, it is shown that the proposed reliability evaluation method can accurately describe the state transition of the storage system, quantify the reliability of the storage system, and obtain its reliability, which has certain practical value.