Search

• A Ramanujan subspace projection (RSP) method is proposed for harmonic removal. • The RSP method can extract weak harmonic components and is robust to noise. • The RSP method is computationally efficient. • Combining RSP and SSI achieves modal identification under harmonic excitation. • Experimental and field test data confirm the effectiveness of the proposed method. The presence of deterministic harmonic excitation, such as that induced by rotating machinery, violates the classical operational modal analysis (OMA) assumption that the system output is strictly ergodic. This paper proves that the presence of harmonic excitation has no effect on the identification of structural modes except in the case where some of the harmonic excitation frequencies are close to the structural frequencies. Therefore, the harmonic component must be removed from the mixed random and harmonic system output before further processing. This paper proposes a Ramanujan subspace projection (RSP) method for harmonic removal, which is realized by projecting the raw system output onto the complex conjugate division (CCD) of the Ramanujan subspace. The novelty of this study is that it reveals the relationship between the frequencies defined in the period and frequency domains, allowing the RSP method to directly extract the harmonic component from the specific CCD without any frequency domain analysis. In addition, an energy indicator is proposed to select the underlying CCDs with the most robust harmonic feature. Using the indicator, one only needs to project the raw system output onto a subset of the CCDs rather than all of them, thereby significantly reducing the computational effort. After removing the harmonic components from the raw output, the remainder can be fed into the covariance-driven stochastic subspace identification (Cov-SSI) method for OMA. The numerical, experimental and field test results show that the proposed RSP method is not only resistant to random noise but also capable of precisely extracting the weak harmonic component from the raw output with less computation. Furthermore, the modal parameters of the structures subjected to mixed random and harmonic excitation can be accurately identified by combining the Cov-SSI and RSP methods. [ABSTRACT FROM AUTHOR]

This paper introduces a novel indirect bridge modal identification framework for extracting higher-mode bridge modal parameters. The method involves processing the vehicle response using a newly proposed iterative vehicle response demodulation technique, which separates multi-component vehicle responses while preserving the physical meaning of variables. This property is crucial for ensuring accurate and robust modal identification from vehicle responses. The feasibility of this approach is initially tested through the analysis of vehicle responses generated by numerical simulations. This analysis includes a detailed parametric study and discussions on various bridge conditions and types. Subsequently, the same methodology is applied to an experimental bridge, where structural modal parameters are extracted from the measured responses of a passing instrumented vehicle. The key contributions of this study include the development of the iterative vehicle response demodulation formulation and the ability of this method to identify modal parameters using fewer processing steps compared to conventional indirect identification methods. Results from both numerical simulations and experimental tests demonstrate that the iterative demodulation method can effectively extract higher-mode bridge modal parameters, validating the proposed framework's effectiveness. • A novel iterative vehicle response demodulation technique for bridge scanning method. • Method derivations showing significant interpretability in physical terms. • A comprehensive parametric study on roughness, damping, and vehicle properties. • Experiments validating the effectiveness of this algorithm in practical applications. [ABSTRACT FROM AUTHOR]

Traditional bridge health monitoring is both expensive and time-consuming because of the need for installing a large quantity of sensors on the bridge. The indirect monitoring method as a feasible alternative has become popular over the last decade, as useful information can be gathered from moving vehicles installed with sensors by considering vehicle-bridge interaction. This paper describes an indirect time-varying modal parameter identification method for bridges under a moving test vehicle. A novel reference-driven S-transform is proposed for the parametric modal identification of time-varying structural systems with non-stationary characteristics based on a multisensory arrangement, comprising a fixed reference sensor installed on the bridge and another movable sensor installed on a moving test vehicle. By the phase-preservation property of S-transform and the multisensory time-frequency analysis, the proposed iterative reference-driven S-transform can be used to extract the time-varying modal parameters of the vehicle-bridge system when the vehicle moves on the bridge. Based on the coherence between measurements from the sensors mounted on the bridge and vehicle, one can track the time-varying characteristics by combining the spatial and time-frequency information obtained by the multisensory array. The efficiency of the proposed reference-driven S-transform method is validated by numerical simulations and laboratory experiments using a simply supported beam with a moving vehicle. The effects of the vehicle property, driving speed, road roughness and measurement noise are discussed. The numerical and experimental results have demonstrated that the proposed method is useful for time-varying parameter extraction with a multisensory system. This will be useful to structural condition monitoring of bridges. [ABSTRACT FROM AUTHOR]