Noting that damage occurrence of offshore jacket platforms is concentrated in two structural regions, a new algorithm to detect damages in a structure using partial measurement of vibration in a target-detecting region is proposed. Employing a numerical model of a typical offshore jacket platform, for which pre- and post-damage modal parameters are available for a few lower modes of vibration, the feasibility of the algorithm is tested. Firstly, the validity of the new algorithm using changes in partial mode shapes and its robustness against identification error of baseline structure are examined by utilizing modal parameters obtained from eigenvalue analysis on the model. Secondly, regarding the simulated dynamic responses of the platform under short-crested waves as ambient vibration measurement, modal parameters are identified by employing an ARMA method, then the new algorithm is applied to locate damages simulated in the structure assisted by the statistical treatment for modal parameters. It is demonstrated that the proposed algorithm in connection with the ARMA modal identification and statistical treatment is feasible and robust against identification error of baseline structure.
The field of health monitoring and damage detection has a great potential for applications in offshore structures (Roesset and Yao 1998). In general, offshore platforms in deep water have to face harsh marine environments, withstanding cyclic waves, severe storms, seaquakes and sea-water corrosion. The occurrence of damage in an offshore structure is inevitable during its lifetime. Therefore, aging structures must be inspected at regular intervals in order to detect the initiation and growth of damages that may lead to catastrophic failure. Currently, divers or Remote Operated Vehicles (ROV) are employed for the purpose of visual inspection and local damage detection. However, the process of inspection and local detection for offshore structures, especially in deep water, is much more difficult than for land structures.