传感器网络的最优维护决策模型

doi:10.3778/j.issn.1002-8331.2112-0362

摘要/Abstract

摘要： 传感器网络最优维护决策的目标为用户提供最优的维护时机，维护决策的精度直接决定了传感器网络的可靠性。基于置信规则库（belief rule base，BRB）专家系统提出的最优维护决策模型解决两个问题：检测数据不足和复杂的系统机理。模型由健康状态评估和预测两部分组成：基于BRB模型对传感器网络的健康状态进行评估；根据当前的健康评估状态，利用Wiener过程预测传感器网络的健康状态，以获得最优的维护时机。基于Wiener过程的健康状态预测模型中，由专家提供传感器网络健康状态的最小阈值，以确定最佳的维护时机。为验证模型的有效性，进行了原油存储罐无线传感器网络的最优维护决策实验研究。

关键词: 最优维护决策, 专家系统, 置信规则库, Wiener过程, 传感器网络

Abstract: Optimal maintenance decision for a sensor network aims to provide the optimal repair time for users. The accuracy of the optimal maintenance decision method directly determines the reliability of the sensor network. In this paper, a new optimal maintenance decision model based on belief rule base（BRB） expert system is developed to solve two problems：the lack of observation data and complex system mechanism. In the new model, two parts exist：the health state assessment and the health state prediction. First, the health state of the sensor network is estimated by a BRB based health assessment model. Then, based on the current health state, a Wiener process is used to predict the health state of the sensor network, and the optimal maintenance time can be obtained. In the Wiener process-based health state prediction model, the minimum threshold of the health state of the sensor network should be provided by experts to determine the optimal maintenance time. To illustrate the effectiveness of the proposed model, a case study for the wireless sensor network of oil storage tank is conducted.

Key words: optimal maintenance decision, expert system, belief rule base, Wiener process, sensor network

李绍华, 郭禾, 冯晶莹, 贺维. 传感器网络的最优维护决策模型[J]. 计算机工程与应用, 2023, 59(8): 315-321.

LI Shaohua, GUO He, FENG Jingying, HE Wei. Optimal Maintenance Decision Model for Sensor Network[J]. Computer Engineering and Applications, 2023, 59(8): 315-321.

参考文献

[1] REPPA V，POLYCARPOU M M，PANAYIOTOU C G.Distributed sensor fault diagnosis for a network of interconnected cyberphysical systems[J].IEEE Transactions on Cloud Computing，2015，2：11-23.
[2] FENG T H，SHIH N Y，HWANG M S.A safety review on fuzzy-based relay selection in wireless sensor networks[J].International Journal of Network Security，2015，17：712-721.
[3] KRISHNAMACHARI B，IYENGAR S.Distributed Bayesian algorithms for fault-tolerant event region detection in wireless sensor networks[J].IEEE Transactions on Computers，2004，53（3）：241-250.
[4] 李洋，高岭，孙骞，等.基于RSOPNN的无线传感器网络节点故障诊断算法[J].计算机工程与应用，2017，53（9）：111-116.
LI Yang，GAO Ling，SUN Qian，et al.Fault diagnosis of node in WSN based on RSOPNN algorithm[J].Computer Engineering and Applications，2017，53（9）：111-116.
[5] SNOUSSI H，RICHARD C.Distributed Bayesian fault diagnosis of jump Markov systems in wireless sensor networks[J].Internat J Sensor Networks，2007，2：118-127.
[6] OH T，CHOI Y B，RYOO J，et al.Security management in wireless sensor networks for healthcare[J].International Journal of Mobile Communications，2011，9（2）：187-207.
[7] CHANG L L，ZHOU Z J，YOU Y，et al.Belief rule based expert system for classification problems with new rule activation and weight calculation procedures[J].Information Sciences，2016，336：75-91.
[8] CHEN Y W，YANG J B，XU D L，et al.On the inference and approximation properties of belief rule based systems[J].Information Sciences，2013，38：121-135.
[9] LI G L，ZHOU Z J，HU C H，et al.A new safety assessment model for complex system based on the conditional generalized minimum variance and the belief rule base[J].Safety Sciences，2017，93：108-120.
[10] LIU J，YANG J B，RUAN D，et al.Self-tuning of fuzzy belief rule bases for engineering system safety analysis[J].Annals of Operations Research，2008，163（1）：143-168.
[11] LIU H C，LIU L，LIN Q L.Fuzzy failure mode and effects analysis using fuzzy evidential reasoning and belief rule-based methodology[J].IEEE Transactions on Reliability，2013，62（1）：23-36.
[12] KONG G，XU D L，LIU X，et al.Applying a belief rule-base inference methodology to a guideline-based clinical decision support system[J].Expert Systems，2010，26（5）：391-408.
[13] YANG J B，LIU J，WANG J，et al.Belief rule-base inference methodology using the evidential reasoning approach-RIMER[J].IEEE Transactions on Systems，Man，and Cybernetics，Part A：System Humans，2006，36：266-285.
[14] FENG Z，ZHOU Z，HU C，et al.A new belief rule base model with attribute reliability[J].IEEE Transactions on Fuzzy Systems，2019，27（5）：903-916.
[15] FENG Z C，ZHOU Z J，HU C H，et al.A safety assessment model based on belief rule base with new optimization method[J].Reliability Engineering and System Safety，2020，203：107055.
[16] HOSSAIN M S，AHMED F，ANDERSSON K.A belief rule based expert system to assess tuberculosis under uncertainty[J].Journal of Medical Systems，2017，41：42-53.
[17] YANG J B，XU D L.Evidential reasoning rule for evidence combination[J].Artificial Intelligence，2013，205：1-29.
[18] ZHANG B C，HU G Y，ZHOU Z J，et al.Network intrusion detection based on directed acyclic graph and belief rule base[J].ETRI Journal，2017，39（4）：592-604.
[19] ZHOU Z J，HU C H，YANG J B.A model for real-time failure prognosis based on hidden Markov model and belief rule base[J].European Journal of Operational Research，2010，207（1）：269-283.
[20] ZHOU Z J，FENG Z C，HU C H，et al.Aeronautical relay health state assessment model based on belief rule base with attribute reliability[J].Knowledge-Based Systems，2020，197：105869.
[21] ZHOU Z J，HU C H，YANG J B，et al.A sequential learning algorithm for online constructing belief-rule-based systems[J].Expert Systems with Applications，2010，37：1790-1799.
[22] ZHOU Z J，YANG J B，XU D L，et al.Online updating belief-rule-base using the RIMER approach[J].IEEE Transactions on Systems Man Cybernetics，Part A：Systems and Humans，2011，41（6）：1225-1243.
[23] ZHOU Z J，CHANG L L，HU C H，et al.A new BRB-ER-based model for assessing the lives of products using both failure data and expert knowledge[J].IEEE Transactions on Systems，Man and Cybernetics：Systems，2016，46（11）：1529-1543.
[24] ZHOU Z G，LIU F，JIAO L C，et al.A bi-level belief rule based decision support system for diagnosis of lymph node metastasis in gastric cancer[J].Knowledge-Based Systems，2013，54：128-136.
[25] ZHOU Z G，LIU F，LI L L，et al.A cooperative belief rule based decision support system for lymph node metastasis diagnosis in gastric cancer[J].Knowledge-Based Systems，2015，85：62-70.
[26] ZHOU Y.The distribution of limit points of increments of local time of the wiener process[J].Systems Science and Mathematical Sciences，1998，3：210-217.
[27] ZHOU Z，GAO C，XU C，et al.Social big-data-based content dissemination in Internet of vehicles[J].IEEE Transactions on Industrial Informatics，2018，14（2）：768-777.