Study on Fracture Delay of High-Strength Bolts in Road Bridge Maintenance

In the maintenance work of highway and bridge engineering structures,the fracture delay of high-strength bolts is a content that needs to be focused on and researched.Based on this,the paper analyzes the fracture delay of high-strength bolts in highway bridge maintenance,including an overview of the fundamental research on fracture delay and related specific studies.It is hoped that this study can provide scientific reference for the reasonable maintenance of high-strength bolts,so as to ensure the overall maintenance effect of highway bridge projects.

Deformation-softening behaviors of high-strength and high-toughness steels used for rock bolts

In deep ground engineering,the use of high-strength and high-toughness steels for rock bolt can significantly improve its energy absorption capacity.However,the mechanisms and effects of rock loading conditions on this kind of high energy-absorbing steel for rock bolt remain immature.In this study,taking Muzhailing highway tunnel as the background,physically based crystal plasticity simulations were performed to understand the effect of rock loading rate and pretension on the deformation behaviors of twinning induced plasticity(TWIP)steel used for rock bolt.The material physical connecting to the underlying microscopic mechanisms of dislocation glide and deformation twinning were incorporated in numerical modeling.The rock loading conditions were mimicked by the real-time field monitoring data of the NPR bolt/cable equipment installed on the tunnel surrounding rock surface.The results indicate that the bolt rod exhibits pronounced deformation-softening behavior with decrease of the loading rate.There is also a sound deformation-relaxation phenomenon induced by the dramatic decrease of loading rate after pre-tensioning.The high pretension(>600 MPa or 224 k N)can help bolt rod steel resist deformation-softening behavior,especially at low loading rate(<10~(-1)MPa/s or 10~(-2)kN/s).The loading rate was found to be a significant factor affecting deformation-softening behavior while the pretension was found to be the major parameter accounting for the deformation-relaxation scenario.The results provide the theoretical basis and technical support for practical applications.

Numerical Model Research on Rotational Performance of Beam-Column High-Strength Bolt Extension End-Plate Connection Node

The high-strength bolted end plate connection is widely used in the construction industry with its green environmental protection and excellent seismic performance. The joints of the joints are semi-rigid, the force performance is extremely complicated, and the experimental research cost is relatively high, and the cycle is very long. Therefore, the establishment of an efficient numerical model is of great significance for evaluating the force performance of high-strength bolt end plates. In this paper, the influence of different material models on the rotation performance of the joint is studied by numerical simulation, and the bending moment-rotation curve is obtained. The numerical simulation and the experimental results are in good agreement, so as to provide a reference for the design and application of this kind of joint.

Influence of anchorage length and pretension on the working resistance of rock bolt based on its tensile characteristics

In coal mining roadway support design,the working resistance of the rock bolt is the key factor affecting its maximum support load.Effective improvement of the working resistance is of great significance to roadway support.Based on the rock bolt’s tensile characteristics and the mining roadway surrounding rock deformation,a mechanical model for calculating the working resistance of the rock bolt was established and solved.Taking the mining roadway of the 17102(3)working face at the Panji No.3 Coal Mine of China as a research site,with a quadrilateral section roadway,the influence of pretension and anchorage length on the working resistance of high-strength and ordinary rock bolts in the middle and corner of the roadway is studied.The results show that when the bolt is in the elastic stage,increasing the pretension and anchorage length can effectively improve the working resistance.When the bolt is in the yield and strain-strengthening stages,increasing the pretension and anchorage length cannot effectively improve the working resistance.The influence of pretension and anchorage length on the ordinary and high-strength bolts is similar.The ordinary bolt’s working resistance is approximately 25 kN less than that of the high-strength bolt.When pretension and anchorage length are considered separately,the best pretensions of the high-strength bolt in the middle of the roadway side and the roadway corner are 41.55 and 104.26 kN,respectively,and the best anchorage lengths are 1.54 and 2.12 m,respectively.The best anchorage length of the ordinary bolt is the same as that of the high-strength bolt,and the best pretension for the ordinary bolt in the middle of the roadway side and at the roadway corner is 33.51 and 85.12 kN,respectively.The research results can provide a theoretical basis for supporting the design of quadrilateral mining roadways.

基于图知识推理的输电线路缺销螺栓识别方法

针对输电线路缺销螺栓识别任务中存在的视觉不可分与样本不平衡问题,提出了基于图知识推理的输电线路缺销螺栓识别方法。首先通过知识表达模块学习到各类螺栓有判别力特征的类别表示;然后深入挖掘螺栓数据集中螺栓种类之间的相关性,提取出标签共现信息;最后将类别表示作为输入特征,以静态图和动态图的相关概率矩阵表征标签共现信息,通过知识推理模块完成图知识的传播与增强,从而实现缺销螺栓的识别。在实验阶段,将所选取的3类金具上的6种螺栓作为实验对象。对比实验结果表明,本文方法对缺销螺栓的识别效果优于其他方法,较原始模型提升了9.13%的准确率。消融实验结果表明,本文所提取的螺栓类别表示、静态图及动态图信息均能够提升缺销螺栓的识别效果。

基于改进YOLOv7-tiny算法的输电线路螺栓缺销检测

为提高无人机对架空输电线路巡检的效率和线路中螺栓缺销的检测精度,提出了改进的你只看一次第7微小版(you only look once version 7-tiny,YOLOv7-tiny)输电线路螺栓缺销检测算法。该算法采用高效的分布移位卷积(distribution shifting convolution,DSConv)来替换YOLOv7-tiny网络中的3×3卷积,以提高模型的计算速度并降低计算复杂度;在模型的检测头部分,添加了高效解耦头结构,以提高模型的准确度和稳定性;并采用明智的交并比(wise intersection over union,WIoU)损失函数来提高正样本的权重,使模型更加关注缺销螺栓目标,以减少正负样本不平衡带来的噪声干扰。实验结果表明,改进YOLOv7-tiny算法对输电线路螺栓缺销检测的平均精度均值达到90.6%,检测速度达到143.0帧/s,同时实现了检测的高速度和高精度。该算法在无人机输电线路巡检中具有一定的优势。

Hydrogen-induced delayed fracture of Cu-containing high-strength bolt steel

The hydrogen-induced delayed fracture(HIDF)behavior of a 1300-MPa-grade high-strength bolt steel 42CrMoV containing 0.42 wt.%Cu was investigated by constant load tensile test in a pH 3.5 Walpole solution.It is shown that the addition of Cu is beneficial to enhance the HIDF resistance by~13%.The observation of the fracture surface revealed that the area fraction of brittle crack initiation zone decreased remarkably for the Cu-added steel.Both the corrosion pit depth and the corrosion rate of the Cu-added steel in the Walpole solution are notably decreased,which is primarily because of the formation of a Cu-rich protective compact rust layer and slightly higher corrosion potential.As a result,the absorbed hydrogen content in that solution was also decreased by~21%.It is concluded that the improvement in the HIDF resistance of the tested steel is primarily due to the increase in corrosion resistance and resultant decrease in the absorbed diffusible hydrogen content in the acidic condition.

An ultra-thin bolt tension sensor and online monitoring system:For application in hydropower plant unit

The condition of bolted connections significantly affects the structural safety.However,conventional bolt tension sensors fail to provide precise measurements due to their bulky size or inadequate stability.This study employs the piezoresistive effect of crystalline silicon material to fabricate an ultrathin sensor.The sensor exhibits a linear relationship between pressure and voltage,an exceptional stability at varying temperatures,and a superior resistance to corrosion,making it adaptable and user-friendly for applications of high-strength bolt tension monitoring.A monitoring system,incorporating the proposed sensor,has also been developed.This system provides real-time display of bolt tension and enables the assessment of sensor and structural conditions,including bolt loosening or component failure.The efficacy of the proposed sensor and monitoring system was validated through a project carried out at the Xiluodu Hydropower Plant.According to the results,the sensor and online monitoring system effectively gauged and proficiently conveyed and stored bolt tension data.In addition,correlations were created between bolt tensions and essential unit parameters,such as water head,active power,and pressures at vital points,facilitating anomaly detection and early warning.

某核电厂循环水泵基础口环固定螺栓断裂、缺失原因分析及处理方案制定

某核电厂循环水泵频繁出现基础口环固定螺栓断裂、缺失缺陷。为避免因螺栓断裂、缺失导致口环窜动进而引起循环水泵不可用,特对此缺陷进行原因分析,确定螺栓为疲劳断裂,断裂后经水流冲刷后丢失,并根据其原因及现场状况制定处理方案。

基于改进YOLOv5算法的地铁车辆转向架螺栓缺失检测

目前,地铁车辆的检修主要依赖于人工检测,不仅效率低,而且可能因漏检等原因造成严重的行车安全事故。因此提出了一种基于改进YOLOv5算法的地铁车辆转向架螺栓缺失检测算法。首先,在YOLOv5算法的骨干网络和特征提取网络中添加Ghost模块,轻量化网络结构,提升检测效率和速度;其次,采用改进的YOLOv5算法对螺栓进行定位训练,并插入CBAM注意力模块,增加网络对目标的关注度,从而获得良好的螺栓定位检测模型;最后通过模板匹配的方法,对比网络检测结果与正常转向架螺栓数量及分布,获得缺失螺栓数目与位置信息。实验结果显示,改进后的YOLOv5网络模型检测精度提升3.9%,模型参数量减少了近1/2,检测速度提升9 fps,螺栓缺失检测准确率为86.2%。因此,文中提出的改进YOLOv5算法的地铁车辆转向架螺栓检测模型满足螺栓缺失定位的检测任务要求,取得了良好的应用效果。

螺栓缺失对摩擦型高强螺栓传力性能的影响

针对钢桁梁桥摩擦型高强螺栓接头出现的螺栓缺失问题,采用ANSYS软件对其进行了有限元分析,通过试验结果与数值计算结果的对比对有限元模型进行了校正,针对不同的螺栓缺失工况,对螺栓缺失对各排螺栓传力比、拼接板应力和芯板应力的影响进行了分析。结果表明:螺栓缺失对高强螺栓接头传力比和拼接板应力造成的影响分别局限在2倍和1倍螺栓间距范围之内,但会造成剩余螺栓传力比增加,当第1排螺栓全部缺失后,第2排螺栓的传力比可增大3.5倍以上;在螺栓缺失处,拼接板应力明显减小,最多可减小50%,但未缺失处应力没有明显改变;随着螺栓缺失数量增加,传力性能下降,芯板应力沿轴向和横向均有所增加,但变化不大,在4%以内。

基于DBSCAN-FPN的输电线路螺栓缺销检测方法

螺栓作为输电线路上数量最大的紧固件,其缺陷检测是输电线路巡检工作中的一项重要内容。针对螺栓缺销为小目标,其定位困难、特征难提取的问题,提出一种基于DBSCAN算法与FPN模型相结合的螺栓缺销检测方法。首先,利用FPN模型定位螺栓缺销目标区域,同时基于DBSCAN聚类算法对具有相同形态结构的区域进行聚类;然后,改进FPN模型:基于螺栓先验知识,利用卷积网络实现自底向上的特征提取,采用双线性插值方法将特征的高层语义信息自顶向下地传递到各个层级,通过卷积滤波方法横向加强高层语义特征与高分辨率特征的融合信息,获得更优化的螺栓缺销特征表达;利用改进FPN模型实现螺栓缺销的初步检测;最后,采用DBSCAN聚类算法对初步检测结果进行误检甄别,实现了螺栓缺销的精确检测。实验结果表明,DBSCAN-FPN在自建数据集上的检测精度达到76.23%,检测效果优于FPN、RFCN和Faster R-CNN。所提方法可以有效提高螺栓缺销检测精度,对输电线路运维有实际意义。

摩擦型高强螺栓传力性能及缺失的非线性分析

针对钢桁梁桥摩擦型高强螺栓连接出现的螺栓缺失问题,利用ANSYS软件,采用壳单元模拟连接板件,弹簧单元模拟接触面相互作用,对摩擦型高强螺栓连接进行了设计状态和螺栓缺失状态下的非线性有限元分析。结果表明:摩擦型高强螺栓连接发生滑移后,外荷载与螺栓所传剪力之间呈现非线性关系;在无滑移状态,各螺栓所传剪力沿外力方向和其垂直方向均为外侧大,中间小,滑移后趋向均匀;随螺栓缺失个数的增加,螺栓群初始滑移荷载、极限滑移荷载和缺失排螺栓传力比均减小,无滑移和局部滑移时相邻排增大最明显,全面滑移后其余各排则同等增大。因此,在高强螺栓连接的设计中,应对螺栓群受力是否进入非线性进行判断,以确定各排螺栓的实际传力比。

基于卷积神经网络的铁路桥梁高强螺栓缺失图像识别方法

为及时发现铁路桥梁高强螺栓偶发的延迟断裂并补充新螺栓,降低铁路桥梁连接失效风险,开展基于卷积神经网络的桥梁高强螺栓缺失图像识别方法研究。该识别方法的主网络由5个卷积层、5个最大值池化层和2个全连接层的卷积神经网络组成。提出在主网络上附加通道和空间混合注意力子网络,分别对不同输入图像的高层不同通道语义特征和不同区域赋予不同权重,提高图像的特征和区域敏感性,进而提高网络的识别准确率。通过随机裁剪、翻转、颜色变化、仿射变换增强和数据均衡操作,增加训练数据的多样性和改善数据的不平衡性。基于真实场景螺栓缺失场景识别结果表明,识别方法的准确率达到94.9%,比常见识别方法提高了4.9%。

基于改进PCL模型的输电线路缺销螺栓弱监督检测方法

销子缺失是输电线路中常见的螺栓缺陷,及时检测出缺销螺栓对输电线路的安全运行至关重要。基于全监督检测模型的螺栓缺陷检测需要目标级标注,目标级标注会消耗大量的人力物力,为减少这种消耗,提出一种基于改进PCL(proposal cluster learning)模型的输电线路缺销螺栓弱监督检测方法,仅利用图像级标注实现缺销螺栓检测。引入通道注意力机制,生成加权特征图,突出目标区域特征,有效地挖掘出螺栓的位置信息;采用加权交叉熵损失函数,控制正负样本对损失值的贡献,增大困难样本的损失比重,提高模型对螺栓目标的关注程度和识别能力;融合全监督的多任务学习思想,使模型能随着迭代次数的增加修正预先得到的边界框。实验结果表明,在测试集上,相比于基础模型,改进后的模型缺销螺栓的AP(average precision)值提升了25.6%,mAP(mean average precision)值提升了25.4%,最终验证了本文方法的鲁棒性。

铁路货车制动梁螺栓丢失故障自动识别方法

在铁路货车故障检测中,由于传统的人工故障检测存在诸多问题,而且效率低,所以迫切需要能够自动识别故障的检测系统。对此,许多铁路公司都推出针对铁路货车运行故障的检测系统。这些系统能够降低人为因素的干扰,提高故障的检测效率和准确率。但是这些系统都还处于人机结合的阶段,为了推动铁路故障检测系统向"机控"的模式转变,基于TFDS标准,并通过机器视觉,自主设计一套制动梁螺栓丢失故障的检测系统,该系统针对货车底部固定制动梁上的三个不同位置的螺栓进行自动定位,并判断螺栓是否丢失。实验结果显示,该系统能够准确定位出螺栓所在位置,并识别出螺栓是否丢失。

Seismic behavior and mechanism analysis of innovative precast shear wall involving vertical joints

To study the seismic performance and load-transferring mechanism of an innovative precast shear wall(IPSW) involving vertical joints, an experimental investigation and theoretical analysis were successively conducted on two test walls. The test results confirm the feasibility of the novel joints as well as the favorable seismic performance of the walls, even though certain optimization measures should be taken to improve the ductility. The load-transferring mechanism subsequently is theoretically investigated based on the experimental study. The theoretical results show the load-transferring route of the novel joints is concise and definite. During the elastic stage, the vertical shear stress in the connecting steel frame(CSF) distributes uniformly; and each high-strength bolt(HSB)primarily delivers vertical shear force. However, the stress in the CSF redistributes when the walls develop into the elastic-plastic stage. At the ultimate state, the vertical shear stress and horizontal normal stress in the CSF distribute linearly; and the HSBs at both ends of the CSF transfer the maximum shear forces.

基于Faster R-CNN级联的输电塔螺栓缺失检测

螺栓缺失样本数据量过小,直接检测螺栓缺失效果不理想;由于输电塔所处地理环境复杂,数据采集时无人机拍摄角度、距离等因素各异,螺栓影像背景复杂,信噪比低,检测效果较差;螺栓作为小目标物,受限于尺寸,特征表达能力弱,一直是目标检测中的难题。针对上述问题,提出基于深度卷积神经网络Faster R-CNN级联的输电塔螺栓缺失检测方法。首先,根据输电塔上螺栓所在部件的特征及规律性,定位所有包含螺栓的部件并生成影像,降低螺栓背景的影响,提高信噪比;其次,对部件影像进行正常螺栓定位,得到检测结果;最后,基于各类部件上正常螺栓的分布,对同类部件上所有正常螺栓检测结果进行最近点迭代算法(iterative closest point,ICP)配准,定位螺栓缺失位置。实验结果表明,与不采用级联的检测方法相比,基于级联的检测方法对螺栓缺失的检测精度提升了7.5%,检测时间基本持平,可提高无人机巡检中螺栓缺失检测的效率,降低巡检成本,适用于电力巡检。

基于深度学习的螺栓缺失快速检测

输电塔螺栓在输电线路中起着重要的连接和固定作用,由于长期暴露于户外,容易出现螺栓缺失等缺陷造成安全隐患,影响输电线路的安全和稳定,因此需要对螺栓进行定期巡检。由于输电塔所处地理环境复杂以及数据采集时拍摄角度、光照等因素的影响,螺栓背景复杂,信噪比低,同时螺栓属于小目标,使得传统目标检测网络对于这种特征的提取不敏感;对于传统的单阶段和两阶段目标检测网络而言,训练时间久,成本较高;此外,传统的检测方法将正常螺栓与螺栓缺失的检测割裂开,容易忽略掉两者在空间上存在的联系;为解决上述问题,本文提出一种基于深度学习的螺栓缺失快速检测方法,基于改进的YOLOv4目标检测网络,在分别检测正常螺栓和螺栓缺失的基础上,对两者检测结果通过区域生长方式进行融合,判断是否在同一部件上,有效提高了检测速度和精度,适用于电力巡检工作。

基于注意力机制的输电线路缺销螺栓弱监督检测方法

输电线路中螺栓起到连接部件的作用,受野外环境影响销子容易脱落,及时检测出缺销螺栓能保证输电线路安全运行。为减少全监督检测模型中对目标级标注的依赖,文章提出一种基于注意力机制的输电线路缺销螺栓弱监督检测方法,仅利用图像级标注实现缺销螺栓检测。螺栓目标具有占比小的特点,本文方法在主网络中引入了卷积块注意模块(Convolutional Block Attention Module,CBAM),可以抑制无用特征,提取螺栓精细特征,加强螺栓目标区域联系,提高检测螺栓的能力。最终,通过实验验证了注意力机制对输电线路缺销螺栓检测的有效性。