Search Results (6)

Vehicular bridges accumulate damage over time due to overloads and material degradation. Non-visible structural damage in such large structures poses a serious risk, as small defects in critical elements can rapidly grow, potentially leading to catastrophic failure. Therefore, implementing simple yet effective methods for damage identification within a structural health monitoring (SHM) system is crucial for ensuring bridge reliability. This study presents a systematic comparative analysis of multiple damage detection algorithms, including six different fractal dimensions (FDs), the homogeneity index (HI), and the Shannon entropy index (SEI). These methods are applied to a high-fidelity finite element method (FEM) model of the Rio Papaloapan Bridge (RPB), a cable-stayed structure, to detect and localize two different types of damage (deck and cable failures) with varying severities and positions. To enhance practical applicability, realistic conditions are simulated by introducing noise to the vibration signals collected from both the undamaged and damaged bridge scenarios while a moving load, simulating a vehicle, is crossing. The results indicate that the HI and SEI not only detected and localized all damage scenarios but also effectively distinguished between different levels of severity, making them highly promising for SHM applications. Additionally, two of the six FD algorithms successfully identified all damage cases with minimal variation from the healthy condition, demonstrating their potential utility. The findings presented in this study are consistent with previous experimental and real-world bridge assessments, reinforcing their validity for real-life applications. Full article

Cross-bonded cables improve transmission efficiency by optimizing the grounding method. However, due to the complexity of their grounding system, they are prone to multiple types of defects, making defect state identification more challenging. Additionally, accurately locating sheath damage defects becomes more difficult in cases of high transition resistance. To address these issues, this paper constructs a distributed parameter circuit model for cross-bonded cables and proposes a particle swarm optimization support vector machine (PSO-SVM) defect classification model based on the sheath voltage and current phase angle and amplitude characteristics. This model effectively classifies 25 types of grounding system states. Furthermore, for two types of defects—open joints and sheath damage short circuits—this paper proposes an accurate segment-based location method based on fault impedance characteristics, using zero-crossing problems to achieve efficient localization. The results show that the distributed parameter circuit model for cross-bonded cables is feasible for simulating electrical quantities, as confirmed by both simulation and real-world applications. The defect classification model achieves an accuracy of over 97%. Under low transition resistance, the defect localization accuracy exceeds 95.4%, and the localization performance is significantly improved under high transition resistance. Additionally, the defect localization method is more sensitive to variations in cable segment length and grounding resistance impedance but less affected by fluctuations in core voltage and current. Full article

Environmental concerns and economic constraints have led to increasing installations of mixed conductor circuits comprising underground cables (UGCs) and overhead transmission lines (OHLs). Faults on the OHL sections of such circuits are usually temporary, while there is a higher probability that faults on UGC sections are permanent. To maintain power system reliability and security, auto-reclose (AR) schemes are typically implemented to minimize outage duration after temporary OHL faults while blocking AR for UGC faults to prevent equipment damage. AR of a hybrid UCG–OHL transmission line, therefore, requires effective identification of the faulty section. However, the different electrical characteristics of UGC and OHL sections present significant challenges to existing protection and fault location methods. This paper presents a selective AR scheme for mixed conductor circuits based on the evaluation of differential currents in multiple defined protection zones, using distributed current transformer (CT) measurements provided by passive optical sensing. Case studies are conducted with a number of different UGC–OHL configurations, and the results demonstrate that the proposed scheme can accurately identify the faulty section, enabling effective selective AR of a comprehensive range of mixed conductor circuit topologies. The proposed scheme is also more cost effective, with reduced hardware requirements compared to conventional solutions. This paper thereby validates the optimal solution for mixed circuit protection as described in CIGRE Working Group B5.23 report 587. Full article

A new damaged cable identification method using the basis vector matrix (BVM) is proposed to identify multiple damaged cables in cable-stayed bridges. The relationships between the cable tension stiffness and the girder bending strain of the cable-stayed bridge are established using a force method. The difference between the maximum bending strains of the bridges with intact and damaged cables is used to obtain the damage index vectors (DIXVs). Then, BVM is obtained by the normalized DIXV. Finally, the damage indicator vector (DIV) is obtained by DIXV and BVM to identify the damaged cables. The damage indicator is substituted into the damage severity function to identify the corresponding damage severity. A field cable-stayed bridge is used to verify the proposed method. The three-dimensional finite element model is established using ANSYS, and the model is validated using the field measurements. The validated model is used to simulate the strain response of the bridge with different damage scenarios subject to a moving vehicle load, including one, two, three, and four damaged cables with damage severity of 10%, 20%, and 30%, respectively. The noise effect is also discussed. The results show that the BVM method has good anti-noise capability and robustness. Full article

Deriving critical parametric information from recorded signals for system identification is critical in structural health monitoring and damage detection, while the time-varying nature of most signals often requires significant processing efforts due to structural nonlinearity. In this study, synchro-squeezed adaptive wavelet transform-based optimized multiple analytical mode decomposition (SSAWT-oMAMD) is proposed. The SSAWT algorithm acts as the preprocessing algorithm for clear signal component separation, high temporal and frequency resolution, and accurate time–frequency representation. Optimized MAMD is then utilized for signal denoising, decomposition, and identification, with the help of AWT for bisecting frequency determination. The SSAWT-oMAMD is first verified by the analytical model of two Duffing systems, where clear separation of the two signals is presented and identification of complex time-varying stiffness is achieved with errors less than 2.9%. The algorithm is then applied to system identification of a cable-stayed bridge model subjected to earthquake loading. Based on both numerical and experimental results, the proposed method is effective in identifying the structural state and viscous damping coefficient. Full article

Cables are the main load-bearing structural components of long-span bridges, such as suspension bridges and cable-stayed bridges. When relative slip occurs among the wires in a cable, the local bending stiffness of the cable will significantly decrease, and the cable enters a local interlayer slip damage state. The decrease in the local bending stiffness caused by the local interlayer slip damage to the cable is symmetric or approximately symmetric for multiple elements at both the fixed end and the external load position. An eigenpair sensitivity identification method is introduced in this study to identify the interlayer slip damage to the cable. First, an eigenparameter sensitivity calculation formula is deduced. Second, the cable is discretized as a mass-spring-damping structural system considering stiffness and damping, and the magnitude of the cable interlayer slip damage is simulated based on the degree of stiffness reduction. The Tikhonov regularization method is introduced to solve the damage identification equation of the inverse problem, and artificial white noise is introduced to evaluate the robustness of the method to noise. Numerical examples of stayed cables are investigated to illustrate the efficiency and accuracy of the method proposed in this study. Full article