Two-step online identification of in-service cable-inertial mass damper systems under nonstationary wind excitations. (15th March 2023)

• Record Type: Journal Article
• Authors: Yang, Xiongjun; Lei, Ying; Liu, Lijun; Zhu, Hongping; Shen, Wenai
• Is Part Of: Mechanical systems and signal processing. Volume 187(2023)
• Publication Date: 2023-03-15
• Subjects: Online parametric identification -- Inertial mass damper -- Nonstationary wind load -- Energy spectrum transmissibility -- Modified directional bat algorithm; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2022.109940
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A novel output-only online parametric identification is proposed for in-service cable-IMD systems under nonstationary wind loads. The first step of this method is to identify modal parameters of cable-IMD systems and the second step is to estimate system physical parameters. A novel energy spectrum transmissibility approach is proposed for system modal parameter identification under the nonstationary excitation. The energy spectrum transmissibility approach is combined with covariance-driven stochastic subspace identification to eliminate spurious modes. Abstract: Recently developed inertial mass dampers (IMDs) exhibit superior performances in vibration attenuation of stay cables due to the introduction of large inertial masses. However, physical parameters of in-service IMD systems tend to vary with operation time and inappropriate parameters would affect vibration mitigation effect. So far, very few researches have been conducted on the online parametric identification of in-service dampers using on-site monitoring data and such evaluation is essential for performances of dampers. To solve such a problem, a novel method is proposed in this paper for online parametric identification of in-service cable-IMD systems under nonstationary wind loads. The identification is a two-step and output-only approach. In the first step, an energy spectrum transmissibility (EST) approach is developed to detect system poles under nonstationary excitation and identification results are not influenced by inputs. By combining covariance-driven stochastic subspace identification (SSI-COV) method with the developed EST approach, spurious modes in SSI-COV estimation are eliminated to obtain reliable modal parameter identification results. In the second step, the errors between the identified modal parameters (i.e., frequencies and damping ratios) and the estimated modal parameters through complex modal analysis are used to construct objective function, and the modified directional bat algorithm (MDBA) recently developed by the authors is utilized to estimate the physical parameters of cable and IMD by minimizing the objective function. Online parametric identification results of a numerical cable-IMD system model under nonstationary wind loads using limited accelerometers demonstrate the effectiveness of the proposed method.