Unified method for fully automated modal identification and tracking with consideration of sensor deployment. (1st June 2022) - He, Min; Liang, Peng; Zhang, Yang; Yang, Fan; Liu, Jiu-xian
Highlights: Modified Modal Observability Correlation is proposed to distinguish different modes. New spurious mode elimination method is proposed to clear the stabilization diagram. New fully automated modal identification and tracking method is proposed. The proposed method can be used for closely spaced modes with spatial aliasing. Abstract: Automated modal identification and tracking provides the key technique for modal parameters based structural condition evaluation. However, the existing automated modal identification and tracking methods have limitations for situation with very few sensors deployed and require manual intervention. This paper proposes a unified fully automated modal identification and tracking method that can be used for structures with many or very few sensors deployed, for closely spaced modes with severe spatial aliasing and for structures with high flexibility or rigidity. A new index, which is called Modified Modal Observability Correlation, is proposed to estimate the similarity of two modes. New spurious mode elimination method and fully automated mode separation and tracking methods are proposed to realize the automated modal identification and tracking. The feasibility and novelty of the proposed method are validated using in-field monitoring data from a long span suspension bridge with high flexibility and a short span bridge with high rigidity and closely spaced modes. Automated modal identification and tracking for situations with many and very few sensors deployed for the two bridges are conducted, and extreme situation of closely spaced modes with spatial aliasing in mode shape is also considered to prove the novelty of the proposed method. Comparisons with existing mainstream methods are also conducted. The results show that the proposed method yields the right identification and tracking results in all situations, showing novelty in automated modal identification and tracking for structures with closely spaced modes having severe spatial aliasing when only very few sensors are deployed.