A dynamic fault tree quantitative analysis method based on probability model detection

Abstract

The invention discloses a dynamic fault tree quantitative analysis method based on probability model detection, and belongs to the technical field of dynamic fault tree quantitative analysis. The method includes: Firstly, allowing the dynamic fault tree to subjected to formalized description; converting the logic gate into a corresponding continuous time Markov chain model; allowing the connectionrelationships among the logic gates to be in one-to-one correspondence to the CTMC models; combining the continuous time Markov chain and the continuous time Markov chain to automatically generate PRISM codes, defining a CSL attribute specification formula, and inputting the CSL formula and the PRISM codes into a tool to obtain a quantitative analysis result. According to the method, hierarchicaldecomposition and module synchronization of the PRISM are combined; A whole dynamic fault tree is converted into a limited number of modules, a single Markov chain model is automatically converted into PRISM codes through an automatic conversion algorithm, the fault occurrence probability of a top event is automatically verified, and synchronization between the modules and commands is achieved through a synchronization mechanism.

Description

technical field [0001] The invention relates to a dynamic fault tree quantitative analysis method, in particular to a dynamic fault tree quantitative analysis method based on probability model detection, and belongs to the technical field of dynamic fault tree quantitative analysis. Background technique [0002] A dynamic fault tree is generally considered to be a fault tree containing at least one dynamic logic gate, which is developed by combining FTA (fault tree analysis) and Markov (Markov) and adding some elements that can reflect the system behavior dependence of. It expands the traditional static fault tree analysis method to the analysis method of dynamic system performance with sequential correlation, resource sharing and cold and hot spare parts. The dynamic fault tree adds several dynamic logic gates on the basis of the traditional fault tree, such as figure 1 As shown, it mainly includes: priority AND gate, function-related gate, sequence mandatory gate, cold s...

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Problems solved by technology

It has been optimized, and the quantitative calculation method of other dynamic logic gates is also introduced in detail. This method reduces the complexity of the calculation, but at the same time reduces the accuracy of the calculation results

Another method is to convert the dynamic fault tree dynamic logic gate into a Markov chain, and then calculate the state transition probability through the state transition diagram for quantitative calculation; this calculation method is completely based on manual, the calculation process is complicated, and there is no effective tool support.

A commonly used method combined with probabilistic model detection converts static logic gates into corresponding Markov chains, and then performs automatic calculations based on probabilistic model detection PRISM tools, but this method does not study dynamic logic gates that are more complex

Another method combined with probabilistic model detection quantitatively analyzes the dynamic fault tree, and the calculation result is accurate. However, although this method avoids the difficulty of manually calculating the migration probability of the Markov state transition chain, this method converts the entire dynamic fault tree into For a Markov chain model, as the scale of the fault tree increases, the process of converting the entire dynamic fault tree into a complete Markov model will be very complicated, and errors, omissions, etc. will easily occur

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