Abstract
System-level diagnosis is a crucial subject for maintaining the reliability of interconnected systems. Based on the classical notion of one-step diagnosability, strong and conditional diagnosabilities are proposed to reflect a systems' self-diagnostic capability under more realistic assumptions. Zhu et al. 2014 studied the strong networks, which are n-regular and n - 1-connected, and in which any two nodes share at most n - 3 common neighbours, and then they proved that a t-regular strong network is strongly t-diagnosable if and only if its conditional diagnosability is greater than t. In this paper, a fault identification algorithm is proposed to diagnose strongly t-diagnosable strong networks under the PMC model.
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