| A global damage detection and assessment algorithm is developed based on a parameter estimation method using the measured modal response of a structure. Damage is characterized by a reduction in a constitutive property of a parameterized finite-element model of the structure between two discrete time inferences. A parameter group-updating scheme is proposed to localize damage in a structural system taking into account the multiplicity of parameter estimation solutions arising from using spatially sparse and noise-polluted data. A unified approach, based on the random starting point scheme and the optimum sensitivity method, for determining solution clustering is used to find multiple solutions and to assess the sensitivity of parameter estimates to noise. The best solution cluster, indicated by the lowest objective, is used as a basis for group subdivision at each level of the damage localization process. The statistical distribution of the element parameters of the damaged and the associated baseline structure is used to assess the severity of damage at the potential damage sites. The proposed damage detection and assessment procedure is tested with a certain set of simulation case studies using a planar bridge truss and a three-dimensional tower truss as the model problems. |
