Quantitative analysis method of dynamic fault tree based on probabilistic model detection

Abstract

The invention discloses a dynamic fault tree quantitative analysis method based on probability model detection, which belongs to the technical field of dynamic fault tree quantitative analysis. First, the dynamic fault tree is formally described, and the logic gate is converted into a corresponding continuous time Markov chain model. And the connection relationship between the logic gates is mapped to the CTMC model one by one, and the PRISM code is automatically generated by combining the continuous time Markov chain and the connection relationship between the continuous time Markov chain, and the CSL attribute specification formula is defined, and the CSL Formula and PRISM code entry tools yield quantitative analysis results. The present invention combines hierarchical decomposition and PRISM module synchronization, converts the entire dynamic fault tree into a limited number of modules, automatically converts a single Markov chain model into a PRISM code through an automatic conversion algorithm, and automatically verifies the fault occurrence of the top event Probability, the synchronization between multiple modules and commands is realized through the 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...

AI Technical Summary

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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