Identification (biology)

Physics

Frame (networking)

Finite element method

Modal analysis using FEM

Polymer chemistry

Mathematics

Structural engineering

Biology

Modal analysis

Operating system

Algorithm

Statistics

Filter (signal processing)

Engineering

Autoregressive model

Artificial intelligence

Vibration

Acoustics

Hilbert–Huang transform

Chemistry

Wavelet transform

Modal testing

Operational Modal Analysis

Computer science

Mode (computer interface)

Botany

Modal

Ambient vibration

Computer vision

Normal mode

Wavelet

Telecommunications

Structural Control and Health Monitoring

This paper proposes an improved Empirical Wavelet Transform (EWT) approach for structural operational modal identification based on measured dynamic responses of structures under ambient vibrations. Two steps are involved in the improved EWT approach. In the first step, the standardized autoregressive power spectrum of the measured response is calculated to define the boundaries of frequency components for the subsequent EWT analysis. The second step is to decompose the measured response into a number of Intrinsic Mode Functions (IMFs) by using EWT. When the Intrinsic Mode Functions are obtained, structural modal information such as natural frequencies, mode shapes, and damping ratios can be identified by using Hilbert transform and Random Decrement Technique. In numerical studies, a simulated signal is used to investigate the effectiveness of the proposed approach. Operational modal identification based on the proposed approach and procedure is conducted to identify the modal parameters of a simulated spatial frame structure under the ambient excitations. The proposed approach is further used for operational modal identification of a seven-storey shear type steel frame structure in the laboratory and a real footbridge under ambient vibrations to verify the accuracy and performance. The modal identification results from both numerical simulations and experimental validations demonstrate that the proposed approach can effectively and accurately decompose the vibration responses and identify the structural modal parameters under operational conditions.

Operational modal identification of structures based on improved empirical wavelet transform