Test strategy rapid generation method based on fault decision network

Abstract

The invention discloses a test strategy rapid generation method based on a fault decision network. The test strategy rapid generation method comprises the steps: building a fault dependence matrix andthe fault decision network of a to-be-tested system, generating an optimal test point through a heuristic search algorithm, obtaining an optimal test strategy, and isolating a fault in the network through an optimal search path. Therefore, the heuristic function value is accurately estimated by combining the influence of the dependence information on the generation of the optimal strategy, and the deviation of heuristic function estimation and search strategy decision in application is reduced, and meanwhile, the optimal solution upper limit is set for each search by setting the opportunity cost, so that the search process is controlled, and the purpose of improving the efficiency is achieved.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis, and more specifically relates to a rapid generation method of a test strategy based on a fault decision network. Background technique [0002] With the increasing development of electronic information technology, the internal circuit design of complex equipment is becoming more and more complex. Timely and accurate determination of system status and isolation of internal faults can effectively shorten the development, testing and finalization time of equipment systems. How to design an efficient fault test scheme has become one of the research hotspots in the field of complex equipment system design. [0003] In the existing fault test scheme design method, the sequential test is based on the signal flow diagram given in the preliminary design and the circuit relationship described by the correlation model, and the test sequence test method is given to reduce the cost of the test, which c...

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Problems solved by technology

However, the AO* algorithm and its related improved methods only consider the probability information of the fault and the cost information of each measuring point in the heuristic cost evaluation, and ignore the influence of the fault dependency on the heuristic search, which leads to the failure of the heuristic search. The strategy is limited, which affects the efficiency of algorithm test optimization

[0005] Patent 201910438846.0 combines heuristic search with dynamic programming, and improves the solution efficiency by reducing the number of repeated searches for the optimal solution. However, the setting of the heuristic function in this patent only considers the relationship between test cost and failure probability, and ignores the The impact of relying on information in the heuristic search, so the estimation of the heuristic function may have a large deviation from the real test cost, which in turn affects the solution efficiency of the optimal test strategy

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