Guo-Wen Sun1, Gang Xiang2,3, Wei He1,4,*, Kai Tang1, Zi-Yi Wang1, Hai-Long Zhu1
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1157-1177, 2023, DOI:10.32604/cmc.2023.035667
Abstract Wireless sensor networks (WSNs) operate in complex and harsh environments; thus, node faults are inevitable. Therefore, fault diagnosis of the WSNs node is essential. Affected by the harsh working environment of WSNs and wireless data transmission, the data collected by WSNs contain noisy data, leading to unreliable data among the data features extracted during fault diagnosis. To reduce the influence of unreliable data features on fault diagnosis accuracy, this paper proposes a belief rule base (BRB) with a self-adaptive quality factor (BRB-SAQF) fault diagnosis model. First, the data features required for WSN node fault diagnosis are extracted. Second, the quality… More >
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