关键词: Malek模型, 遗传算法, 系统故障诊断

Abstract: In multi machine system, each node（processor） in the communication process is extremely easy to failure, therefore, it is very important to choose effective diagnosis algorithm for judging system fault set fast and accurately. The traditional PMC model is based on the test results between nodes, and the test results on faulty node testing others are doubtful, that lead to the results of this diagnosis model is relatively unstable. In view of this situation, taking the Malek diagnosis model instead of the traditional PMC model, with the characteristics of genetic algorithm, the complex network is simplified as binary encoding, and the population search direction is determined according to the fitness function value, which can improve the search efficiency. The algorithm is built by designing constraint equation upon the Malek model, putting forward a new adaptation function, and optimizing mutation operator. The experimental results show that the improved algorithm shortens the CPU time that is required to judge the fault set. Besides that, under the fault symptoms, the probability of this algorithm deciding the target fault set is higher, so it is proved that the Malek model is more efficient than the PMC model.

Key words: Malek model, genetic algorithm, system-level diagnosis