Bridge cables, which serve as critical load-bearing components in cable-supported bridges, are highly susceptible to broken wires caused by corrosion and fatigue. Accurate quantitative evaluation of this type of damage is essential to ensure structural safety. This study presents a novel quantitative evaluation method for identifying the number of broken wires by employing the magnetic flux leakage (MFL) signal in three-dimensional (3D) space. The method first acquires the 3D spatial magnetic leakage field and generates 3D arrays of MFL signals for computational analysis. It then extracts two categories of features. The first is the global feature, defined as the L1 norm distance (L1D) between the measured 3D spatial MFL signal and the defect-free reference signal. The second is the local feature, consisting of multi-scale waveform features organized as a feature array. The multi-scale waveform feature arrays are compressed using Multilinear Principal Component Analysis (MPCA) to reduce computational redundancy. The compressed feature arrays are then introduced into the Elastic Net-Constrained Regression (ENCR) model to predict defect width. The number of broken wires is ultimately calculated as the ratio of the total L1D value to the L1D value corresponding to the predicted width of a single wire. For a given broken wire width, the L1D demonstrates linear superposition with respect to the number of broken wires, with goodness-of-fit values exceeding 0.999, enabling proportional quantification. Validation through simulations and experiments on PES7-127 cables (127 wires of 7 mm diameter) confirms the method's effectiveness. The simulations achieved 100 % accuracy in counting broken wires across varying widths and distributions, while experimental results verified 100 % quantification accuracy (within a tolerance of +/- 1 wire) for defects involving <= 4 broken wires. This performance is obtained using a training dataset of only 30 samples. This study provides a practical and efficient approach for bridge cable assessment.

As a critical load-bearing component in many infrastructures, the tension status of steel strand serves as a key indicator for infrastructure safety assessment. This study focuses on estimating the tension of steel strands and proposes a multi-feature fusion approach based on Pulsed Eddy Current (PEC) testing. Firstly, the mechanism of PEC-based tension estimating for steel strand is analysed in detail, and PEC experiments on steel strand under different tension are carried out. The response of the PEC signals to tension is consistent with the results of the theoretical analysis. Subsequently, five features are extracted from the PEC signals for estimating the tension of steel strand, and their characteristics and performance in tension estimation are analysed. Finally, based on these features, a Principal Component Analysis (PCA)-based method for multi-feature fusion is developed to improve the accuracy of tension estimation. Compared with the features without using fusion method, the performance in tension estimation of the significant principal component with fusion feature has been significantly enhanced. The Root Mean Square Error (RMSE) of the estimation results with multi-feature fusion is 0.73% of Full Scale (FS), and the maximum is 1.41% FS.

中国是草莓生产和消费大国,但采摘收获方式仍主要依赖人工进行.针对地垄式草莓人工采摘劳动强度大、效率低以及市场上现有采摘装备结构复杂、价格昂贵等问题,设计一款小型地垄式草莓采摘装备.设备集草莓识别、采摘、传输、收集功能于一体,由行走装置、采摘装置、适应调节装置、收集存储装置和控制电路部分构成.经样机收获性能验证试验,小型地垄式草莓采摘装备能够有效辅助人工开展采摘作业,提高劳动效率,创造经济价值.

Corrosion of steel wires in cables is a frequent occurrence and is a major factor affecting the durability and safety of cables. Magnetostrictive guided waves have been employed to detect steel wire corrosion. However, due to the complexity of the geometry of the corrosion area, it is difficult to interpret the magnetostrictive guided wave testing signals. Hence, extracting features from testing signals to characterize the corrosion condition is a great challenge. This study proposes a topological feature for corrosion characterization of steel wire, which is extracted from the two-dimensional point cloud with optimal geometry structure of the testing signal based on persistent homology theory. Corrosion experiments were carried out on 30 galvanized steel wires. The experimental results indicate that the topological feature increases roughly linearly with the corrosion depth. Furthermore, compared to other features obtained from the time domain, frequency domain, and joint time–frequency domain, this topological feature can reflect the progression of corrosion more accurately.

A detail-enhanced multi-exposure image fusion method was proposed to address the problem of low weights obtained in the light and dark regions in the sequence image,resulting in the loss of details in the bright and dark regions of the fused image.Wavelet decomposition was conducted on the sequence image and the fused image based on the weight map.This process involved extracting the low-frequency components from the fused image and the high-frequency components from the edge regions,and they were fused with the high-frequency components from the non-edge regions of the sequence image.Finally,the detail-enhanced fused image was obtained through wavelet inverse transform.Experimentally,nine sets of classical multi-exposure image sequences were selected for comparison with nine multi-exposure image fusion algorithms in terms of subjective comparison and objective evaluation,respectively.The results demonstrated that the proposed method,which combined the spatial and frequency domain image fusion methods,could effectively solve the problem of detail loss in the bright and dark areas of fused images,while avoiding the problem of ringing phenomenon often encountered in frequency domain image fusion methods.The fused images were realistic,natural,and exhibited vibrant colors.The mean image information entropy value and the mean image gradient value of the fused images obtained through the proposed method were 7.6555 and 7.0273,respectively,ranking first and second among the ten multi-exposure image fusion algorithms.Considering both subjective and objective evaluation results,the proposed method outperformed the nine comparative methods.

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Multi-wire cables are widely used in suspension bridges and cable-stayed bridges as primary load bearing structural elements. Broken Wires in cables can lead to catastrophic accidents such as bridge collapse. Magnetostrictive guided wave testing technology has been employed to detect the broken wire defects in multi-wire cables, and the defect size is estimated by analyzing the defect echo signals. However, there are many studies on the guided wave testing for the seven-wire steel strands but fewer for the bridge cables which have a large number of wires. Moreover, the relationship between the guided wave testing signal features and the defect size of multi-wire structures is imprecise, which means the defect size estimated by the features may deviate significantly from the real defect size. In this paper, large-scale topological features are extracted by using persistent homology from the dynamical reconstruction topology of the guided wave testing signals to characterize broken wire defects in the bridge cable. The broken wire experiments were performed on a 61-wire cable. The experimental results show a good linear relationship (the goodness of fit 0.9946) between the large-scale topological features and the number of broken wires in the cable. It indicates that it is feasible to extract topological features from the topological domain of the testing signals to characterize the broken wire defects of bridge cables.

为实现桥梁缆索表面损伤的准确识别,提出了一种基于改进YOLO V4模型的图像识别方法.利用缆索爬行机器人采集桥梁缆索表面图像,筛选缆索表面出现损伤的图像作为数据集,并采用数据增强方法对其扩充.在原始的YOLO V4模型结构中引入注意力机制模块,以提升网络的特征提取能力.实验结果表明,改进的YOLO V4模型具有良好的泛化能力,可有效识别桥梁缆索表面损伤,平均精度为93.57％,相较于SSD模型、Faster R-CNN模型和原始YOLO V4模型,平均精度分别高出24.57％、29.93％和6.10％.

Vision surveillance is an effective way to detect the water accumulation and corrosion in bridge cable anchorage zone. Duo to the closed dark environment and the high reflectivity of metal surfaces in the zone, the acquired images are partially too bright or too dark. It is adverse for vision surveillance. To solve this problem, we propose to capture multi-exposure images to improve the image quality of the anchorage zone by image fusion. Seven multi-exposure image fusion algorithms are tested in the experiments. Both subjective evaluation and objective evaluation show that all the fusion algorithms can effectively improve the image quality of the anchorage zone. Among the seven algorithms, MEF-OSSI is superior to the others, and it is recommended in the engineering application.

考虑采用照相设备获取图像检测桥梁外观病害存在有效图片获取难、海量图片分析工作量大的问题,提出一种结合图像预处理技术的无人机外观病害探测方法.结合测距传感,预先设置自动拍摄距离与频率,精确定位病害位置,有效拼接图像,提高桥梁等复杂部件外观病害探测的准确性,通过工程应用,验证了该探测方法的有效性.

As the most critical member, the service status of the cable system plays a crucial role in the longevity of cable-supported bridges. As bridges advance in age, their cable system is undergoing a process of accelerated deterioration. Hence the need for safety evaluation of cables is getting more urgent. At present, cable maintenance mainly relies on the manual inspection by engineers, which features low efficiency, high costs and risk, and potential non-inspection zone. In this context, we studied the fusion technologies between sensors and cables, and developed a maintenance management platform, which can collect data of cable corrosion, temperature and humidity, as well as water accumulation, etc. The intelligent cable products have been tested in outdoor environment since April 2020, and have been successfully applied in several bridges.

钢丝腐蚀退化是桥梁拉索承载能力下降的主要原因,定期腐蚀检测对拉索的寿命非常重要.为模拟拉索实际腐蚀过程和检测思路,选取制造完好的平行钢丝拉索截段倾斜摆放,在不剥开拉索外护套HDPE的条件下,设计一套均匀滴加NaCl溶液吊瓶装置,通过小孔滴加NaCl溶液进行98 d加速腐蚀,使用磁致伸缩导波检测仪器定期跟踪采集拉索腐蚀区域和端部信号.分析对比腐蚀前后信号发现,腐蚀区域反射系数逐渐增大,导波能量在腐蚀钢丝中逐渐衰减,端部回波信号逐渐减小.拉索腐蚀试验的导波信号特性规律能为实桥在役拉索腐蚀检测提供数据依据和可靠支撑.

为研究内置式橡胶阻尼器对钢绞线斜拉索的减振效果,文章通过长168.25 m的拉索减振试验,对内置式橡胶阻尼器的减振性能进行研究分析.试验结果表明:在拉索长2％的位置安装内置式阻尼器后,一阶和二阶平均振动对数衰减率为1.53％和1.57％,对拉索的振动具有抑制作用;通过梁端和塔端阻尼器减振效果的线性叠加,结合外护套双螺旋线气动措施,可满足主跨在300 m以下钢绞线斜拉桥的拉索振动控制需求.

High-strength steel wire is the basic unit of the cable, and the status of the wire directly determines the cable carrying capacity. Based on the study of the wire broken detection signal by using magnetostrictive guided wave testing, 150 steel wires were classified by artificial accelerated corrosion method. 30 steel wires are used as a group on a special bracket and regularly pour dilute hydrochloric acid to accelerate corrosion. According to the depth of corrosive pits, the corrosion of steel wire was divided into five grades. The signal characteristics of steel wire before and after corrosion were tested by using magnetostrictive waveguide nondestructive testing instrument. The above experiments show that perfect wire background signal reflection coefficient is below 2%(97% probability). So the detection signal can be sensitive to feedback the wire corrosion or not. However, it is difficult to evaluate corrosion degree grading by pits depth or weight loss. The non-destructive testing signal by using magnetostrictive guided wave is very complicated because of the size of pits, shape, orientation, surface distribution, weight loss and other factors. In conclusion, the research ideas and conclusions on the corrosion grading of steel wire and the non-destructive testing of magnetostrictive guided wave have a good effect on the corrosion evaluation of steel wire and its cable.

在拉索体系中设置减振器,是斜拉索振动控制的主要措施之一.本文总结桥梁拉索振动的控制目标,通过实索减振试验对剪切式高阻尼橡胶减振器的性能进行研究分析.试验结果表明,在安装剪切式高阻尼橡胶减振器后,拉索的一阶、二阶和三阶振动对数衰减率分别为4.19％、3.68％和3.43％.可见,该减振器具有较好的减振效果,适用于长度小于250m的钢丝或钢绞线拉索的振动控制.

在钢丝缺陷检测的基础上对拉索断丝磁致伸缩导波检测信号特性进行研究,通过对平行钢丝拉索制作断丝缺陷,详细分析研究不同断丝数量下导波检测信号的特性,得到缺陷回波反射系数与拉索缺陷截面损失率(即断丝根数)的关系,即断丝根数越多缺陷回波信号幅值越大,可对拉索金属承载面积进行检测,避免出现重大损失,为钢丝拉索的损伤磁致伸缩导波无损检测的工程实际应用提供了数据基础.

为满足国内外桥梁工程规范对拉索振动控制的要求,在拉索体系中设置减振器是斜拉索振动控制的主要措施之一.论文通过实索减振试验,对高阻尼橡胶减振器、剪切式高阻尼橡胶减振器和永磁式磁流变减振器三种实用的拉索减振器进行了研究,试验结果表明这三种减振器性能均能满足相关国际规范要求,高阻尼橡胶减振器一阶振动对数衰减率为1.62％适用于80 m以下的桥梁拉索减振,剪切式高阻尼橡胶减振器一阶振动对数衰减率为4.19％适用于250 m以下的桥梁拉索减振,永磁式磁流变减振器一阶振动对数衰减率为7.79％适用于大跨径桥梁拉索减振.

This Paper treats the crank mechanism of diesel engine S195 as prototype.By means of Pro/ E,tasks such as 3D modeling,virtual assembly and virtual prototype are executed.All these work provide a foundation for dynamic simulation using ADAMS and finite element analyses using ANSYS.