Health assessment of the wharf based on evidential reasoning rule considering optimal sensor placement. (December 2021)

• Record Type: Journal Article
• Authors: Zhang, Chaoli; Zhou, Zhijie; Hu, Guanyu; Yang, Lihao; Tang, Shuaiwen
• Is Part Of: Measurement. Volume 186(2021)
• Publication Date: 2021-12
• Subjects: Evidential reasoning rule -- Structural health assessment -- Optimal sensor placement -- Discrete integer coding covariance matrix adaptive evolution strategy -- LNG wharf; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2021.110184
• Languages: English
• ISSNs: 0263-2241

Abstract

Abstract: To achieve an accurate structural health assessment, data collected by multiple sensors needs to be fused effectively. When the number of sensors is limited, it is necessary to determine the reasonable position of sensors and adopt the adequate fusion method. Therefore, a structural health assessment method based on evidential reasoning (ER) rule considering the optimal sensor placement (OSP) is proposed in this paper. In particularly, the discrete integer coding covariance matrix adaptive evolution strategy (D-CMAES) algorithm is developed to determine the scheme of OSP based on the finite element modal analysis (FEMA). Furthermore, in order to select adequate sensors whose data will be fused by the ER rule, a strategy for determining the weight of the ER rule is proposed according to the perception probability. The effectiveness of the proposed method is verified by a case study about the health assessment of the LNG wharf in Hainan, China. Highlights: Optimal sensor placement is considered in structural health assessment. The establishment of health assessment model for the LNG wharf. Perception probability is used as evidence weight in the assessment.