Structural health monitoring (SHM) based on vibration measurements in large/complex structures were shown to be promising by researchers. The authors believe that the SHM problem is fundamentally one of statistical pattern recognition. Therefore, the damage detection studies reviewed herein are summarized in the context of a statistical pattern recognition paradigm. This paradigm can be described as a three-part process: (1) Data acquisition and cleansing, (2) Modal parameter identification, (3) Damage identification methods. However, offshore platform structures are very complex, and not easy to excite artificially and they are often suffered from ambient loads that cannot be controlled easily. The thesis focuses on three key issues for structural health monitoring via vibration in real offshore platform structures.
In the first part of review, the offshore platform structure health monitoring system basic principle and the composition are discussed. In the second portion, three important processes of structure health monitoring are summarized (Data acquisition and cleansing, modal parameter identification, damage identification methods), and each method good and bad points is pointed out. Next, Application of damage identification and structural health monitoring to offshore platform are in detail produced, the methods are described in general terms including difficulties associated with their implementation. Finally, current and future-planned applications of this technology to offshore platform are summarized. The paper concludes with a discussion of critical issues for future research on damage identification and structural health monitoring for offshore platform.