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A New Search Algorithm of MBD Based on Spider Web and Its Application in Power Distribution Network Fault Diagnosis

机译:基于蜘蛛网的MBD搜索新算法及其在配电网故障诊断中的应用

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摘要

To reduce the spatial complexity and search time of minimum hitting sets in model-based diagnosis (MBD), a new algorithm for searching minimum hitting sets of MBD is proposed in this paper, which can use the characteristics of minimum hitting sets and the idea of spider prey in biology. We call it cobweb search algorithm. In the algorithm, the generation of visit spiders and search strategy are proposed, and the visit spider that can find the visit path of cobweb to search all minimum hitting sets within a cobweb is constructed. Based on the experiment comparisons, Cobweb search algorithm has better performance than other algorithms of searching minimum hitting sets. As an example, a 14-node power distribution network model is constructed. The diagnosis process with MBD is introduced and analyzed in detail, at the same time the cobweb search algorithm is applied in power distribution network fault diagnosis. The experiment results verify the effectiveness and superiority of the proposed algorithm.
机译:为了减少基于模型的诊断(MBD)中最小命中集的空间复杂度和搜索时间,提出了一种新的MBD最小命中集搜索算法,该算法可以利用最小命中集的特征和思想。生物学中的蜘蛛猎物。我们称其为蜘蛛网搜索算法。该算法提出了访问蜘蛛的产生和搜索策略,构造了可以找到蜘蛛网访问路径以搜索蜘蛛网中所有最小命中集的访问蜘蛛。基于实验比较,Cobweb搜索算法的性能优于其他搜索最小命中集的算法。例如,构建了一个14节点的配电网络模型。介绍并分析了MBD的诊断过程,同时将蛛网搜索算法应用于配电网故障诊断。实验结果证明了该算法的有效性和优越性。

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