Bayesian-Based Efficient Fault Location Algorithm for Power Bottom-Guaranteed Communication Networks

In order to solve the problem of low fault location performance of power bottom-guaranteed communication network under uncertain environment, combined with the characteristics of fault location of power bottom-guaranteed communication network under uncertain environment, the two stages of fault detection and fault location are combined. This paper proposes a Bayesian-based efficient fault location algorithm for power bottom-guaranteed communication networks (BFLA). In the fault detection phase, the probe dependency matrix model is constructed, and a heuristic probe selection algorithm based on vector expansion theory is proposed. The detection result set is obtained by transmitting the probe. In the fault location stage, a Bayesian fault location model is constructed based on the set of detection results to solve the optimal suspected fault set. In the performance analysis part, compared with the existing algorithms, it is verified that the proposed algorithm effectively improves the accuracy of fault diagnosis and reduces the false positive rate.