Abstract
Stay cables are one of the most critical structural components in modern cable-stayed bridges and the cable tension plays an important role in the construction, control and monitoring of cable-stayed bridges. We propose a time domain and a time–frequency domain approaches for modal parameter identification of stay cables using output-only measurements. The time domain approach uses the subspace algorithm which is improved with a new modal coherence indicator. The time–frequency approach uses the wavelet transform of signals which is improved with a new analyzing wavelet. The wavelet transform is applied to the free response of ambient vibration which is obtained using the random decrement technique. Two experiments of stay cables are presented. The first experiment concerns a stay cable in laboratory where the external load is applied through an impact hammer and the vibratory signals are acquired through four accelerometers. The second experiment concerns the Jinma cable-stayed bridge that connects Guangzhou and Zhaoqing in China. It is a single tower, double row cable-stayed bridge supported by 112 stay cables. Ambient vibration of each stay cable is carried out using accelerometers. From output-only measurements, the modal parameters of stay cables are extracted. Once the eigenfrequencies and the damping coefficients are obtained, the cable forces and the Scruton number are derived. In a continuous monitoring and modal analysis process, the tension forces and Scruton numbers could be used to assess the health of stay cables in cable-stayed bridges.
Highlights
Background and definitionsThere are several time–frequency representations such as the Short Time Fourier Transform (STFT), the Wigner–VileDistribution (WVD) and the Wavelet Transform (WT)
We propose in this work a time domain and a time–frequency domain procedures to extract the modal parameters of vibrating systems from output-only measurements
Modal parameter identification of stay cables in a cable-stayed bridge is a typical class of structural modal analysis and it is of practical significance to develop methods for identifying modal parameters with only measured response data
Summary
Known as Operational Modal Analysis (OMA), named as ambient or natural excitation or output-only modal analysis. Correlation functions or covariance matrices between output responses are used to obtain state space matrices and extract modal parameters. We propose in this work a time domain and a time–frequency domain procedures to extract the modal parameters of vibrating systems from output-only measurements. The first procedure is based on subspace algorithms, which use covariance matrices between output signals and are able to give estimates of high precision They are constructed on the observability and controllability properties of linear time invarying systems and need linear algebra operations, such as the singular value decomposition (SVD) or QR factorization to filter noises, to estimate the state space matrices and the model order.
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