Multi-objective probabilistic optimum monitoring planning considering fatigue damage detection, maintenance, reliability, service life and cost

Effective and efficient service life management is essential for a deteriorating structure to ensure its structural safety and extend its service life. The difficulties encountered in the service life management are due to the uncertainties associated with detecting and identifying structural damages, and assessing and predicting the structural performance. To reduce these uncertainties, continuous long-term structural health monitoring (SHM) can be employed. However, a rational and practical SHM planning is required to simultaneously maximize the accuracy, efficiency, and cost-effectiveness in service life management. This paper proposes a probabilistic optimum SHM planning based on five objectives to be simultaneously optimized: minimizing the expected damage detection delay, minimizing the expected maintenance delay, maximizing the damage detection time-based reliability index, maximizing the expected service life extension, and minimizing the expected life-cycle cost. The formulations of the five objectives are based on the probabilistic fatigue damage assessment. The monitoring plannings associated with both a single- and a multi-objective probabilistic optimization process (MOPOP) are investigated. For efficient decision making in identifying the essential objectives and selecting a well-balanced solution among the Pareto optimal solutions, the degree of conflict among objectives and objective weights are estimated. The novel approach proposed in this paper accounts for the interdependencies among the five objectives considered and demonstrates the role of the optimum SHM planning in service life management of deteriorating structures. The proposed MOPOP SHM planning is applied to the hull structure of a ship subjected to fatigue.