A Probabilistic Model Updating Algorithm for Fatigue Damage Detection in Aluminum Hull Structures

The use of aluminum alloys in the design of naval structures offers the benefit of light-weight ships that can travel at high-speed. However, the use of aluminum poses a number of challenges for the naval engineering community including higher incidence of fatigue-related cracks. Early detection of fatigue induced cracks enhances maintenance of the ships and is critical for preventing the catastrophic failure of the hull. Furthermore, monitoring the integrity of the aluminum hull can provide valuable information for estimating the residual life of hull components. This paper presents a model-based damage detection methodology for fatigue assessment of hulls that are instrumented with a long-term hull monitoring system. At the core of the data driven damage detection approach is a Bayesian model updating algorithm enhanced with systematic enumeration and pruning of candidate solutions. The Bayesian model updating approach significantly reduce the computational effort by systematically narrowing the search space using errors functions constructed using the estimated modal properties associated with the condition of the structure. This study proposes the use of the Bayesian model updating technique to detect damage in an aluminum panel modeled using high-fidelity finite element models. The performance of the proposed damage detection method is tested through simulation of a progressively growing fatigue crack introduced in the vicinity of a welded stiffener element. An experimental study verifies the accuracy of the proposed damage detection method using an aluminum plate excited with a controlled excitation in the laboratory. INTRODUCTION Aluminum alloys are increasingly being used as the choice of material for ship hulls, especially in high-speed vessels, where the relatively light-weight and high corrosion resistance properties of the material is attractive. However, the design and operation of ships with aluminum hulls has been fairly recent in the naval community. Long-term monitoring and evaluation of aluminum hull performance with respect to hull aging and fatigue accumulation (or related damage) is needed. Fatiguerelated damage in aluminum alloys often appear as widespread micro-cracks; this is in contrast to the large-size fatigue cracks of steel alloys that lead to rapid strength deterioration of the system. While steel vessels would need immediate attention upon the initiation of fatigue cracking, high-speed aluminum hulls can remain in operation even after the initiation of microcracks because of the ductile mechanical characteristic of the material. However, close monitoring and evaluation of hull health has the potential to extend the operational life of highspeed aluminum vessels by ensuring micro-cracks do not nucleate into more severe cracks that undermine the hull performance. Frequent inspection of ship hulls can extend the operational life of a ship since the detection of the onset of damage can reduce overall ship life-cycle costs. However, current visual inspections of the entire hull are both costly and labor-intensive. Therefore, the instrumentation of a structural health monitoring (SHM) system coupled with an effective damage detection methodology can reduce the cost of