我国城市地下停车场发展现状及修建技术研究

目前,"停车难、乱停车"现象不断加剧,严重影响了城市环境与交通秩序,而通过挖潜、改造、新建等方式大力推进城市地下停车场建设无疑是解决"停车难、乱停车"现象最为有效的办法。本文主要通过对国内外城市地下停车场建设典型案例进行调研,系统分析我国地下停车场建设管理、规划设计及施工方面存在的问题,提出停车场的规划与设计方案、运营模式和投融资模式的建设意见,为我国解决城市交通拥堵和城市地下停车场的综合规划与建设提供参考。     

水利工程中金属焊缝缺陷的超声检测方法比较研究

为研究基于超声的无损探伤方法在水利工程金属结构焊缝缺陷识别中的应用,利用常规超声检测技术、超声相控阵技术、衍射时差法(Time of Flight Diffraction, TOFD)超声检测技术对水利工程金属结构焊接试块缺陷进行识别,分析了各种缺陷在超声无损探伤技术中的特征显示。研究结果表明:常规超声检测技术、TOFD检测技术均能对各种缺陷实现信号显示,超声相控阵检测技术对气孔和横向裂纹的显示不够明显,但对其它缺陷的检出效果较为明显;常规超声检测技术对操作人员的要求较高,对缺陷的定性困难,精度不高;TOFD检测结果中气孔和横向裂纹的显示呈现出一种特殊的弧形,有一定高度的内部裂纹和未熔合的信号由上下尖端衍射波组成,根部未焊透上下尖端信号不够明显;相控阵检测结果直观,可以较精确地测量缺陷的埋藏深度、自身高度、长度等,但在扫查点状缺陷或者与超声声束平行的裂纹缺陷时,检出率极低。     

Comparison and analysis of Acoustography with other NDE techniques for foreign object inclusion detection in graphite epoxy composites

This paper presents the use of a novel through-transmission ultrasonic (TTU) Acoustography non-destructive evaluation (NDE) method to detect foreign object inclusion (FOI) defects in graphite epoxy composite laminates. The study employed three different composite test standards with varied size FOI defects embedded at varying depth within the composite laminates. For validation, Acoustography results were directly compared with conventional immersion TTU testing and infrared thermography (IRT) methods. From results obtained, it was demonstrated that the Signal-to-Noise Ratio (SNR) measurements for Acoustography were more than 6:1 and were in good correlation with immersion TTU and IRT results. The defect sizing ability of TTU Acoustography for FOI defects in graphite epoxy composite laminates were also in strong correlation with immersion TTU and IRT techniques. Finally, for the three laboratory systems employed in this study, typical panel TTU Acoustography inspection time was just about three minutes to scan a 300 mm × 300 mm (11.8″ × 11.8″) area, which was more than three times faster compared to IRT and sixty times faster to conventional immersion TTU C-Scan techniques. This is a very significant finding for the reason that Acoustography is being developed as a faster, more efficient, and affordable alternative to traditional ultrasonic inspection systems for composite manufacturing quality control and quality assurance (QC/QA) and field maintenance of composite structure applications.     

基于模板匹配的啤酒箱印刷质量检测方案

目的快速且精准地检测啤酒箱常见的印刷缺陷。方法以啤酒箱面纸为检测目标,通过提取模板图像中形状和灰度值信息构建差异模型的模板匹配方法,对啤酒箱印刷中常见的缺陷特征进行检测,根据检测结果判断印刷质量是否合格,并通过检测验证实验对质量检测方案的效果进行评估。结果通过对所采集的500张图像进行检测实验并统计结果,该方法的平均准确率达到96.18%,漏检率小于0.9%,误判率为3.08%,平均检测耗时低于10 ms。结论使用该方法对啤酒箱面纸这类胶印制品进行质量检测的效果优秀且稳定,可以对细小划痕等高精度要求的缺陷进行精准检测,而且检测速度也快于其他方法。     

地铁列车车钩钩头法兰磁粉聚集原因分析

某地铁列车车钩钩头法兰部位在磁粉探伤过程中发现磁粉聚集现象,通过对磁粉聚集区域切片进行剖面宏观分析、硬度测试、化学成分分析、金相检验、扫描电镜分析以及能谱分析,对磁粉聚集原因进行了分析。结果表明:钧头法兰磁粉聚集区域存在焊接特征,且焊缝中存在气孔、夹渣等焊接缺陷,靠近焊接熔合线的热影响区存在疏松铸造缺陷;在磁粉探伤时,这些缺陷位置会形成漏磁场,使磁粉在漏磁场处聚集,从而形成磁粉聚集。     

Chemical and mineralogical alterations of concrete subjected to chemical attacks in complex underground tunnel environments during 20–36 years

This paper investigates the chemical and mineralogical alterations of concrete in underground tunnel structures built from 1980 to 1996, located on the China's east seashore. The underground water around the tunnels had once been treated to be not or little aggressive. However, the complex environments in the tunnels had increased the aggressiveness of certain ingredients, thus causing chemical attacks. The chlorides in the leakage underground water cause chloride attack, and the NaCl crystallizations on the surface of the C50 pre-cast concrete segments induce a deeper chloride contamination. When the concrete suffers flowing leakage water, calcium leaching also occurs, leading to decalcification and magnesium incorporation. Under this circumstance, C50 pre-cast concrete shows a higher resistance compared with C30 cast-in-place concrete, mainly due to the low water to binder ratio. Within the C30 cast-in-place concrete facing concentrated leakage water and NaCl crystallizations, a strong magnesium chloride attack is observed. Besides the materials factors, the environmental factors, including the high concentrations of both chloride and magnesium ions, the removal timing of calcium ion, and the water saturation, are believed to take responsibility for the magnesium chloride attack.     

爆破疏通下水管道的研究与实践

交通干道下水道道管被铸铁窨井盖板卡堵,几年来采用了多种手段的均未疏通,采用外敷药包定向爆破技术一炮疏通了堵塞,确保了砼下水[管道和市区交通安全,节省了大量奖金,该定向爆破的药量确定,药包结构及安全防护方面可供类似的工程参考。     

Improved synthetic aperture focusing technique by Hilbert-Huang transform for imaging defects inside a concrete structure

A useful nondestructive testing tool for civil engineering should immediately reveal defects inside concrete structures at the construction sites. To date, there are few effective methods to image defects inside concrete structures. In this paper, a new nondestructive testing method using elastic waves for imaging possible defects inside concrete is developed. This method integrates the point-source/point receiver scheme with the synthetic aperture focusing technique (SAFT) to increase functioning depth and enhance received signals. To improve image quality, received signals are processed by Hilbert-Huang transform (HHT) to get time-frequency curves for the SAFT process. Compared with conventional SAFT method processing with time-amplitude signals, this new method is capable of providing a better image of defects not only in the numerical simulation but also in the experimental result. The image can reveal the number of defects and their locations and front-end profiles. The results shown in this paper indicate that this new elastic-wave-based method exhibits high capability in imaging the defects of in situ concrete structures.     

储罐底板缺陷自动定位与可视化方法研究

针对储罐底板漏磁检测的实际需要,研究了根据异常数据点进行缺陷自动定位、定量描述及可视化的基本方法.通过定义扫描、板块和储罐底板的特征参数,基于图形几何变换建立了缺陷定位的数学模型,运用窗口自动生长算法实现了缺陷分布区域的有效识别.实践证明,储罐底板漏磁检测系统能根据所添加板块和扫描的特征参数,自动绘制储罐底板上缺陷的整体分布图并提供直观的可视化检测报告,克服了现有检测系统的不足,提高了储罐底板漏磁检测系统的检测效率、可靠性和实用性.     

Review of magnetic methods for nondestructive evaluation (Part 2)

This paper gives a guideline to the literature of magnetic methods for nondestructive evaluation of materials for flaws and defects. This is a sequel to an earlier paper which described magnetic methods for nondestructive evaluation of stress, plastic deformation and microstructure. The present paper discusses magnetic particle inspection, magnetic flux leakage, leakage field calculations and eddy current inspection, including the remote field electromagnetic inspection method. An extensive survey of recent publications in the field is given.     

室内与实海环境中防污漆铜离子渗出率测试结果相关性对比分析

铜离子渗出率作为评估含铜防污漆防污性能的主要指标,其测试方法是否准确与高效对于筛选和评价防污漆配方具有重要意义。试验通过自制室内防污漆渗出率测试装置,对比分析了在实海环境和室内模拟环境条件下,防污漆铜离子渗出率的变化规律,比较了两种试验方法的关联性与差异性。结果表明,两种试验方法测试的铜离子渗出率曲线变化趋势及最终结果基本一致,室内模拟环境方法更快捷、准确、方便。     

Use of infrared thermography for quantitative non-destructive evaluation in FRP strengthened bridge systems

The increasing use of fiber reinforced polymer (FRP) composites as externally bonded reinforcement for strengthening of concrete structures has created a need for the development and implementation of rapid methods of field level non-destructive evaluation (NDE) both for quality assurance during installation of the material and also for long-term monitoring of in-field performance. These methods must provide inspectors with the ability not only to inspect FRP strengthened structures for defects, but also should provide the means to quantify the shape, size and severity of the defect for continued monitoring and comparison. Infrared (IR) thermography, which uses data from temperature differentials to detect and characterize defects and anomalies, presents a potentially efficient technique for non-contact, real-time inspection and quantitative data interpretation. In this research a three-girder two bay reinforced concrete bridge deck segment was loaded under field representative loading conditions and the girders and slabs were sequentially strengthened with FRP composites to study the effect of FRP strengthening at systems level. The two slabs were strengthened with two different composite systems, prefabricated strips and field impregnated fabric laminates. The appearance and progression of damage in the FRP systems and at the FRP–concrete interface with an increase in the level of loading was quantitatively monitored using IR thermography. Based on the thermal intensity, the damage could be classified into types such as interlaminar debonding inside the composite or composite–concrete interface debonding. Also based on the magnitude of the thermal intensity, the severity of the damage could be quantitatively monitored. The results were also correlated to the visual observations of crack patterns and failure mechanisms as well as to strain and displacement data measured during the test.     

Handbook of Mathematical Functions with Formulas

Nondestructive evaluation is used widely in many engineering and industrial areas to detect defects or flaws such as cracks inside parts or structures during manufacturing or for products that need to be inspected while in service. The commonly used standard statistical model for such data is a simple empirical linear regression between the (possibly transformed) signal response variables and the (possibly transformed) explanatory variable(s) such as defect size. For some applications, such a simple empirical approach is inadequate. An important alternative approach is to use knowledge of the physics of the inspection process to provide information about the underlying relationship between the response and the explanatory variable or variables. Use of such knowledge can greatly increase the power and accuracy of the statistical analysis and enable, when needed, limited extrapolation outside the range of the observed explanatory variables. This article describes a set of physical model-assisted analyses to study the capability of two different ultrasonic testing inspection methods to detect synthetic hard alpha inclusion defects in titanium forging disks. Supplementary materials for this article are available online.     

Non-contact imaging for surface-opening cracks in concrete with air-coupled sensors

Rapid and accurate non-destructive evaluation (NDE) techniques are needed to assess the in-place condition of concrete structures. However the time and effort required to perform NDE tests using conventional surface-mounted contact sensors hinder rapid evaluation of large full-scale structures. The suitability of surface waves and non-contact sensing techniques to detect the presence of concrete defects is examined here. First, the ability to detect leaky surface waves in concrete with air-coupled sensors is demonstrated. Surface waves in a concrete slab specimen are generated by an electrically-controlled impact source. Next, the data and signal processing needed to improve leaky surface wave data, with respect to eventual application to velocity and attenuation images, are demonstrated. Finally velocity and wave attenuation data collected from a concrete slab specimen that exhibits surface cracking are presented. Test results show that the proposed energy ratio (attenuation) criterion is more sensitive to existence of cracks than the velocity criterion.     

钢管漏磁在线检测技术的研究

介绍了钢管漏磁检测的基本原理，对钢管在线漏磁检测系统进行总体设计。分析了漏磁场理论模型和讨论了影响缺陷漏磁信号的一些因素及补偿方法，针对该系统的特点设计了高速数据采集板，借助Windows系统平台，在所研制硬件的基础上，采用多线编程和虚拟设备驱动技术编制了数据采集、分析、状态显示、实时控制等面向对象、多功能模块化的软件，详细叙述了漏磁信号数据分析的方法和过程。这种系统具有检测速度快、数据吞吐量大、效率高、钢管缺陷分辨率高等特点。     

异跨框架式地铁地下车站结构抗震性能水平与评价方法研究

针对现有异跨地铁地下车站结构抗震分析方法缺乏合理性能评价指标的问题。考虑土体与结构混凝土的材料非线性和接触非线性,建立了土-异跨地铁车站静动耦合整体时域有限元数值模型,通过在基岩处输入不同强度等级和类型的地震动,研究了异跨地铁车站结构的侧向变形规律与地震损伤特性,揭示了该车站结构的地震损伤破坏演化过程,建立了基于层间位移角与损伤破坏状态的异跨框架式地下车站结构抗震性能水平评价方法与物理特征描述。所建议的抗震性能评价方法能初步应用于异跨框架式地下结构的抗震性能水平分析。     

基于Kano模型的红色乡村旅游服务设计研究

目的 通过Kano模型结合服务设计相关方法,分析红色乡村旅游服务痛点与游客需求类型,并对各个需求进行重要程度排序,为改善红色乡村旅游服务质量与游客体验提供参考。方法 利用用户旅程图、桌面调研、问卷、亲和图的方式收集游客需求再进行分类整理,设计并发放Kano问卷,分析统计各项需求的属性类别,并通过Better-Worse四象限散点图计算各个需求的敏感度。结果 在交通方面,游客对市区往返景区的固定班车、停车位充足的停车场有强烈需求,同时希望能够获得通往景区的交通信息;在景区信息方面,游客最希望能够了解景区项目信息,并进行线上购票;在基础设施、服务方面,游客对控制游客数量、路线规划、基础设施和专业导游有强烈需求,其次希望景区周边有民宿旅馆,以及提供物品寄送回家服务;在游览内容方面,游客最希望感受到红色文化精神内涵、品尝到当地特色美食,同时对民俗文化特色、文创纪念品、创意性的讲解、展览等有较大期待。结论 Kano模型能够科学有效地分析红色乡村旅游的游客需求类型和各个需求的重要程度,并指导红色乡村旅游的服务设计与规划,从而提升其服务系统质量。     

飞机表面涂层干剥落工艺研究

为解决某新型飞机表面旧油漆难以清除的问题,采用正交试验法对该型飞机旧油漆涂层干剥落的工艺参数进行优化.根据对脱漆率等指标的测试,确定了最佳工艺参数:气体压力0.5MPa,气体流量3 m3/min,喷射距离20 mm,移动速度40 mm/s.采用上述参数对该飞机表面油漆进行清除,脱漆率为99.8%,脱漆速度可达10 m2/h,达到了满意的脱漆效果.     

Simulation and Experiments of Airborne Zero-Group-Velocity Lamb Waves in Concrete Plate

The impact-echo (IE) test method has been widely used to determine the thickness of a plate and to locate delaminations in reinforced-concrete structures. It was later realized that the IE mode is related to the Zero-Group-Velocity S1 Lamb mode (S₁ZGV). An efficient inspection of a structure using rapid, noncontact, air-coupled sensing technology is of great interest. The objective of this research is to investigate the effectiveness of air-coupled sensing to detect the ZGV Lamb mode signals. Numerical simulation and experimental verification were performed to study the in-air ZGV vibration responses induced by a point impact applied on a concrete plate. Two concrete plates, one without delamination and one with delamination, were tested and simulated. For each plate, the simulation results agreed well with the experimental results, and both methods estimated the plate thickness precisely. The numerical simulations also visualized the pressure field in the air and are helpful for interpretation of the experimental results. The numerical and experimental results suggest that the air-coupled sensing technology can serve as an effective and rapid inspection tool for large concrete structures.     

Deep Learning Based Underground Sewer Defect Classification Using a Modified RegNet

The sewer system plays an important role in protecting rainfall and treating urban wastewater. Due to the harsh internal environment and complex structure of the sewer, it is difficult to monitor the sewer system. Researchers are developing different methods, such as the Internet of Things and Artificial Intelligence, to monitor and detect the faults in the sewer system. Deep learning is a promising artificial intelligence technology that can effectively identify and classify different sewer system defects. However, the existing deep learning based solution does not provide high accuracy prediction and the defect class considered for classification is very small, which can affect the robustness of the model in the constraint environment. As a result, this paper proposes a sewer condition monitoring framework based on deep learning, which can effectively detect and evaluate defects in sewer pipelines with high accuracy. We also introduce a large dataset of sewer defects with 20 different defect classes found in the sewer pipeline. This study modified the original RegNet model by modifying the squeeze excitation (SE) block and adding the dropout layer and Leaky Rectified Linear Units (LeakyReLU) activation function in the Block structure of RegNet model. This study explored different deep learning methods such as RegNet, ResNet50, very deep convolutional networks (VGG), and GoogleNet to train on the sewer defect dataset. The experimental results indicate that the proposed system framework based on the modified-RegNet (RegNet+) model achieves the highest accuracy of 99.5 compared with the commonly used deep learning models. The proposed model provides a robust deep learning model that can effectively classify 20 different sewer defects and be utilized in real-world sewer condition monitoring applications.