Research On DCS Long-term Health Assessment Method Of Nuclear Power Plant

The decentralized control system plays the role of a nerve center in a nuclear power plant and is used to ensure the entire process of electric energy production and operation.To ensure that DCS equipment products meet the requirements of good operation,how to carry out accurate real-time health evaluation and long-term health evaluation of DCS in nuclear power plants has become a hot spot in method research and system development.In view of the above problems,the paper carries out the research on the long-term health evaluation method of DCS modules in nuclear power plants,and evaluates the degree of functional health of the cabinet,and its connotation is not completely consistent in different fields,which refers to the possibility of the system completing the design function at a given point in time in the future,that is,the instantaneous unavailability rate of the future DCS cabinet,which can reflect the aging of DCS equipment.Different nuclear power plants DCS equipment installation and commissioning,operating environment,workload and other factors have certain differences,and the true failure rate generally has a certain deviation from the ideal failure rate given by the manufacturer.At the end of operation and service,most of the equipment enters a period of wear and tear,and the life distribution of the equipment will deviate from the exponential distribution.In view of the above problems,this paper adopts different life distribution types(exponential distribution,Weibull distribution)for different stages of the module life cycle(fault contingency period and loss period)in the cabinet,and adopts different estimation methods(classical estimation method,Bayesian estimation method)according to the size of the available failed module sample size to estimate the parameters of the reliability model.In order to verify the effectiveness of the proposed method,based on the fault records of CPU modules of a power plant,the corresponding failure rate is calculated and the parameters are estimated by using two distribution forms.The K-S test method was used to verify the rationality of the adopted life distribution.There are dozens or even hundreds of DCS cabinets in nuclear power plants,and each cabinet contains dozens of modules,and each module has two or four failure modes(detectable/undetectable,single random/common cause)and two maintenance modes(self-test fault maintenance,regular detection and fault maintenance),and some modules also have more complex primary/standby switching behavior.As a result,manually building a dynamic reliability model of a cabinet is not only laborious,but also error-prone.To solve the above problems,a method is proposed to automatically build the corresponding continuous-time Markov chain(CTMC)model from the cabinet configuration file.The automatic conversion algorithm from cabinet configuration to PRISM script is designed,and the automatic conversion program from cabinet configuration to its dynamic reliability model CTMC is written based on the programming language,so as to realize the automatic reliability modeling and analysis based on the cabinet configuration file.The PRISM-CTMC model generated by the automatic conversion method is compared with the YAMS-BDMP model to verify the effectiveness of the conversion method.This method can provide a reference for long-term health evaluation of cabinet modules.The proposed method has certain theoretical value and high engineering application value for improving the credibility of the actual failure rate and reliable life estimation results of DCS equipment in nuclear power plants and realizing model-based DCS safety and reliability analysis.