Automated modal identification for Structural Health Monitoring: A critical assessment

Advances in dynamic identification procedures and optimization of hardware performances play a relevant role in the development of Structural Health Monitoring in hazardous areas. Several worldwide applications are reported in the literature and several methods able to assess the health state of a structure exist. Some of these techniques aim at tracking changes in structural response directly or indirectly related to the mechanical characteristics (natural frequencies, etc.) during service life and especially after damage due to exceptional loads. One of the most relevant drawbacks of such methods is represented by the need of a user intervention during the structural modal parameter identification processes. This specific aspect does not fully fit requirements of SHM systems, which should be fully automated. In order to overcome this limitation, a number of algorithms have been proposed in recent years. In this paper, after a comprehensive literature review, a critical assessment of the available automated modal identification procedures will be carried out, pointing out advantages and limitations of each method. Finally, the main aspects of an automated FDD-based modal identification algorithm will be described and some sample case studies will be discussed in order to point out its effectiveness. The algorithm has been implemented into a specific software package, named LEONIDA, developed in LabView environment. Some peculiar aspects of software implementation will be shortly reviewed and some issues related to the integration within a fully automated Structural Health Monitoring system will be analyzed.