Improved optimizing method for sequential fault diagnosis strategy

Abstract

The invention relates to an ant colony algorithm and related matrix based optimizing method for a sequential fault diagnosis strategy. The method comprises four major steps, namely, encoding and building a model, constructing fitness functions, building a model for the sequential fault diagnosis strategy, and optimizing the model. According to the method, the multi-signal model building technology is carried out to obtain related matrix of representation system faults and test dependency, and the fitness functions, a state transition rule of the ant colony algorithm and an information feedback mechanism are defined to convert the diagnosis strategy optimization into ant colony optimization; three strategies, including dynamic adjusting of permeates, information compressing and adapting of degree of congestion are introduced for improving the rate of convergence and optimization capacity of the ant colony algorithm, and therefore, the precision of the optimal design method of the diagnosis strategy and the robustness of the results are improved. The method is consistent with the principle of the minimum cost, namely, the search cost is minimized on the premise that the fault detection rate and isolation rate are ensured, and the requirement on fault strategy optimization is met.

Description

technical field [0001] The invention belongs to the technical field of testing and fault diagnosis, and relates to a sequential fault diagnosis strategy optimization method based on an ant colony method and a correlation matrix. Background technique [0002] With the improvement of the function and structure complexity of the modern equipment system, problems such as the difficulty of test diagnosis and the increase of test cost have been brought. One of the key points of test scheme design is the design of sequential fault diagnosis strategy, that is, to choose a test execution sequence to improve the accuracy and cost of fault diagnosis. The optimal design of diagnostic strategies is an NP-complete problem in terms of computational complexity. Commonly used AND-OR graph search methods, AO methods, and AO * method, fault tree model method, etc. have problems such as large amount of calculation, local convergence, combination explosion, etc., and it is difficult to adapt to...

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Problems solved by technology

However, these methods have more or less limitations, mainly in: the ability to deal with uncertainty is not high, most of them are static diagnosis strategies, and they cannot use diagnosis experience, etc.

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