A novel methodology for modal parameter identification of arch dam based on multi-level information fusion. (15th January 2023)

• Record Type: Journal Article
• Authors: Wang, Gang; Li, Huokun; Fu, Zhiyong; Huang, Wei; Liu, Bo; Yao, Siyang
• Is Part Of: Mechanical systems and signal processing. Volume 183(2023)
• Publication Date: 2023-01-15
• Subjects: Modal parameter identification -- Information fusion -- Vibration responses -- Ambient vibration -- Arch dam; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2022.109578
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A novel method for modal parameter identification of arch dam based on multi-level information fusion is proposed. The closely spaced and high-frequency modes are accurately identified. The method can significantly improve the identification accuracy and has better applicability. Abstract: Operational modal analysis plays an important role in the structural health monitoring and safety diagnosis of arch dam. However, due to background noise, it is difficult to accurately extract the effective characteristics information of arch dam from the vibration responses whose amplitudes are too small under ambient vibration, and the deviation caused by traditional identification methods will directly affect the estimation accuracy for structural modal parameters. Therefore, a novel methodology for modal parameter identification of arch dam based on multi-level information fusion is proposed in this paper. The proposed method is based on multi-sensor data-level fusion to identify the structural natural frequency and damping ratio, which greatly preserves and extracts structural modal properties in the vibration responses. Meanwhile, structural mode shapes are identified based on dynamic feature-level fusion, which significantly improves the identification accuracy. The effectiveness and feasibility of the proposed method are verified by the modal results of digital signals and simulated signals in the 7-DOF system. Prototype engineering case shows that the closely spaced and high-frequency modes can be decomposed and identified by the proposed method, and this method has a higher identification accuracy, which can provide a new idea for modal parameter identification of arch dam.