Life-Cycle Probabilistic Multi-objective Optimum SHM Planning

Structural Health Monitoring (SHM) is widely utilized to detect potential damage and predict the structural performance of deteriorating structures. Timely damage detection and accurate structural performance prediction are crucial for ensuring structural safety and managing the service life of deteriorating structures. This paper addresses a life-cycle probabilistic multi-objective optimization for SHM planning. The life-cycle probabilistic multi-objective optimum SHM planning can be based on availability, damage detection, reliability, service life, life-cycle cost, and risk. When initial information is insufficient for reliable damage prediction, an availability-based objective is useful for optimum SHM planning. Otherwise, the damage detection delay, maintenance delay, reliability index, service life, life-cycle cost, and risk can be used for optimum SHM planning. They are formulated by integrating damage initiation and propagation, damage detection, and the effects of inspection and maintenance actions on service life, reliability, life-cycle cost, and risk. Approaches to solving the multi-objective optimization efficiently and multi-attribute decision-making to select the most appropriate solution among the Pareto optimal set are presented. Furthermore, an updating process incorporating information from SHM is outlined to enhance the accuracy of SHM planning.