Search Results (6)

Cables are vital load-bearing components of cable-stayed bridges. Surface defects can lead to internal corrosion and fracturing, significantly impacting the stability of the bridge structure. The detection of surface defects from bridge cable images faces numerous challenges, including shadow disturbances due to uneven lighting and difficulties in addressing multiscale defect features. To address these challenges, this paper proposes a novel and cost-effective deep learning segmentation network, named Trans-DCN, to detect defects in the surface of the bridge cable. The network leverages an efficient Transformer-based encoder and integrates multiscale features to overcome the limitations associated with local feature inadequacy. The decoder implements an atrous Deformable Convolution (DCN) pyramid and dynamically fuses low-level feature information to perceive the complex distribution of defects. The effectiveness of Trans-DCN is evaluated by comparing it with state-of-the-art segmentation baseline models using a dataset comprising cable bridge defect images. Experimental results demonstrate that our network outperforms the state-of-the-art network SegFormer, achieving a 27.1% reduction in GFLOPs, a 1.2% increase in mean Intersection over Union, and a 1.5% increase in the F1 score. Ablation experiments confirmed the effectiveness of each module within our network, further substantiating the significant validity and advantages of Trans-DCN in the task of bridge cable defect segmentation. The network proposed in this paper provides an effective solution for downstream cable bridge image analysis. Full article

To address the incomplete image data collection of close-to-ground structures, such as bridge piers and local features like the suspension cables in bridges, obtained from single unmanned aerial vehicle (UAV) oblique photography and the difficulty in acquiring point cloud data for the top structures of bridges using single terrestrial laser scanners (TLSs), as well as the lack of textural information in TLS point clouds, this study aims to establish a high-precision, complete, and realistic bridge model by integrating UAV image data and TLS point cloud data. Using a particular large-scale dual-track bridge as a case study, the methodology involves aerial surveys using a DJI Phantom 4 RTK for comprehensive image capture. We obtain 564 images circling the bridge arches, 508 images for orthorectification, and 491 images of close-range side views. Subsequently, all images, POS data, and ground control point information are imported into Context Capture 2023 software for aerial triangulation and multi-view image dense matching to generate dense point clouds of the bridge. Additionally, ground LiDAR scanning, involving the placement of six scanning stations both on and beneath the bridge, was conducted and the point cloud data from each station are registered in Trimble Business Center 5.5.2 software based on identical feature points. Noise point clouds are then removed using statistical filtering techniques. The integration of UAV image point clouds with TLS point clouds is achieved using the iterative closest point (ICP) algorithm, followed by the creation of a TIN model and texture mapping using Context Capture 2023 software. The effectiveness of the integrated modeling is verified by comparing the geometric accuracy and completeness of the images with those obtained from a single UAV image-based model. The integrated model is used to generate cross-sectional profiles of the dual-track bridge, with detailed annotations of boundary dimensions. Structural inspections reveal honeycomb surfaces and seepage in the bridge piers, as well as painted rust and cracks in the arch ribs. The geometric accuracy of the integrated model in the X, Y, and Z directions is 1.2 cm, 0.8 cm, and 0.9 cm, respectively, while the overall 3D model accuracy is 1.70 cm. This method provides technical reference for the reconstruction of three-dimensional point cloud bridge models. Through 3D reconstruction, railway operators can better monitor and assess the condition of bridge structures, promptly identifying potential defects and damages, thus enabling the adoption of necessary maintenance and repair measures to ensure the structural safety of the bridges. Full article

The application of Nb microalloying to high-carbon pearlite bridge cable wire rod steel has always been controversial, especially in the actual production process, which will be affected by the cooling rate, holding temperature and final bonding temperature. In this paper, the experimental characterization, finite element simulation and phase diagram calculation of the test steel were carried out, then the microstructure and properties of different parts of Nb microalloying of bridge cable wire rods were compared and analyzed. The phase transition interval of pearlite during the water-cooling process of bridge cable wire rods is increased due to the refinement of austenite grains, and the significant increase in the end temperature of the phase transition makes the average interlamellar spacing of pearlite increase. The cooling rate of different parts of bridge cable wire rods simulated by Abaqus has little difference. At the same time, Nb microalloying effectively increases the proportion of low-angle grain boundaries, so that the overall average misorientation representing the surface defects is reduced. This helps to reduce the surface energy and increase the stability of the microstructure. Combined with the mechanical properties of microtensile rods, it is found that the grain refinement effect of Nb is greater than that of coarsening interlamellar spacing during hot rolling deformation in actual production, which makes the tensile strength at the 1/4 section increase significantly. The overall tensile strength and area shrinkage of the steel wire have also been effectively improved. Full article

In order to study the effect of initial defects on fatigue crack propagation law, a test method to identify fatigue crack propagation rate and path based on load waveform variation was presented, and a new test device was designed to apply fatigue pulsation loads to multiple wires for bridge cables simultaneously in this paper. To simplify the corrosion defect formation process, a machine-cut notch was used to describe the initial defect on the steel wire surface. Firstly, fatigue crack propagation tests were conducted on the surface notched steel wire specimens. By using crack front marking technique, the “beach-like patterns” visible to the naked eyes on the cross sections of the steel wires were formed, and the process of fatigue crack propagation can be tracked and reproduced. Then Autodesk Computer Aided Design (AutoCAD) software was used to describe the morphology of “beach-like patterns” and accurately measure the depth and width of cracks. Finally, the influence of initial defect morphology on fatigue crack propagation rate was investigated according to the relationship between fatigue cracks depth and cyclic loading numbers. The results show that the test device designed in this paper can effectively realize the synchronous fatigue crack propagation test of multiple wires, and significantly shorten the fatigue test period. By observing and analyzing the change of load waveform, the moment of fatigue crack propagation can be directly and accurately determined. The larger the depth, the smaller the width and the sharper the morphology of initial defect, the faster the crack propagation rate and the shorter the life of notched wire specimens under the combined action of fatigue loads and corrosive medium. Full article

The durability problem in high-strength steel wire used for bridge cable is becoming more and more severe due to chlorine salt erosion, with the primary corrosion morphology of steel wire surfaces being pit corrosion. To simplify the pitting formation process, a machine-cut notch was used to represent a corrosion pit caused by electrochemical non-uniformity, and then the fatigue performance and corrosion fatigue performance of steel wire with initial defects were studied experimentally. A new type of test device was designed to carry out synchronous pulsating fatigue loading on multiple wires. A series of S-N curves of steel wire with initial defects under various loading conditions was obtained, and the effects of the concentration and pH value of the corrosive solution, and the shape and dimension of the initial defect on the fatigue corrosion performance of steel wire for bridge cables were investigated. The results show that the test device designed in this paper can effectively perform the life test under the combined action of corrosive medium and fatigue load, and can considerably shorten the duration of the fatigue test. Under the combined action of corrosive medium and fatigue load, the life of steel wire with an initial defect is significantly lower than that without consideration of the corrosion effect. The corrosion fatigue performance of steel wire decreases with the increase of acidity of the corrosive solution, rather than the increase of solution concentration. The life of steel wire with a narrow deep notch is much lower than that with a wide shallow notch. The stress concentration leads to a sharp reduction in wire life. Full article

A numerical simulation method is presented in this paper to study the damage evolution and failure process of high-strength steel wires with pre-corrosion defects in cable-stayed bridges under fatigue loads. This method was based on the mechanism of crack nucleation accelerated by corrosion pits, in which cellular automata (CA) and finite element (FE) simulation methods were used. First, based on the continuum damage mechanics (CDM) theory, a fatigue damage model suitable for steel wire with pre-corroded defects was established to describe the evolution process of the microscopic damage of steel wires, and a user-defined material subroutine (UMAT) was written using formula translator (FORTRAN) language. Then, in MATLAB, the shape and position of random pitting defects on the steel wire surface were generated using 3D CA technology. Afterwards, a pitting defect model was successively inputted into AutoCAD, Rhino and ABAQUS software to obtain the FE model of steel wire with initial pitting defects or initial damage. Finally, the life-and-death element method and the UMAT program were used to simulate the fatigue damage evolution process of the steel wire with initial defects in ABAQUS software, and the fatigue life of the steel wire was obtained. The results show that the proposed strategy and algorithm can effectively describe the fatigue damage evolution process of the steel wire with initial pitting defects under the action of a fatigue load, and the simulated fatigue life is in good agreement with the experimental results. The obtained stress-life (S-N) curves of the steel wire with different corrosion degrees show that the influence of pit corrosion on fatigue life is much greater than that of the mass loss caused by corrosion. By comparing the irregular pit model with regular pit models, it can be found that the irregular shape angle is the main reason for the smaller fatigue life and the larger stress concentration in the irregular pit model than in the regular pit model. Full article