Voids beneath concrete slabs represent a critical yet often concealed defect that can precipitate rapid slab failure, posing substantial safety hazards. Conventional void detection methodologies predominantly rely on human interpretation of Ground-Penetrating Radar (GPR) data. However, accurately identifying voids at the centimeter (cm) level remains challenging due to the nonlinear evolution of voids and the non-unique nature of void features. Herein, this study proposes an innovative data-driven framework for cm-level void morphology and location detection, testing and repair in real-world cement pavement applications through the integration of GPR and deep learning techniques. Only GPR data are used as input for the automated void detection, obviating the need for destructive core sampling or excavation while providing precise grouting repair parameters. Through comprehensive numerical simulations and field experiments, we have enhanced the analysis of GPR responses to cm-scale voids, enabling more accurate detection. Furthermore, a specially designed deep learning architecture is developed to effectively capture and analyze non-unique void features from extensive field data. The methodology was validated through field tests employing an 800 MHz GPR system on core samples, demonstrating its practical feasibility. The results demonstrate a remarkable 1500 % improvement in detection speed compared to manual processing, with a mere 4.3 % volume error for a 25 cm void, and 93.8 % AP (average precision), meeting practical engineering requirements. This technological advancement offers significant improvements in void detection, reduces maintenance expenditures and extends pavement lifespan, and enhances overall traffic safety, representing a substantial contribution to intelligent infrastructure maintenance systems and measurement science.

To understand the pollution characteristics and sources of heavy metals in the soil of the lower reaches of the Jinling River, 41 samples of surface soil in the lower reaches of the Jinling River were collected, and the contents of eight heavy metals （Cr, Mn, Ni, Cu, Zn, As, Cd, and Pb） were determined by high-precision X-ray fluorescence spectrometer （HDXRF）. Correlation analysis and positive matrix factorization model （PMF） were used to analyze the sources of heavy metals in the soil. The potential ecological risk assessment model based on source was used to analyze the potential ecological risk under different pollution sources, and the influencing factors of ecological risk of each pollution source were analyzed by means of geographical detector. The results showed that： ① The average values of eight heavy metal elements in soil were lower than the risk screening values of soil pollution but higher than the soil background values of Shaanxi Province. The spatial variability of Zn, Cd, and Pb was large, which was mainly affected by human activities. ② The heavy metals in the soil of the study area were mainly from industrial sources, traffic sources, natural sources, and agricultural-industrial mixed sources, and the contribution rates of each pollution source were 16.51%, 23.68%, 51.08%, and 8.73%, respectively. Based on the source-based potential ecological risk assessment, the potential ecological risk index （RI） of industrial sources, traffic sources, natural sources, and agricultural-industrial mixed sources were 34.11, 85.03, 16.76, and 21.19, respectively. Cd was the priority control element, and traffic sources were the priority control sources. ③ The distance from key enterprises, the distance from highway, sand content, and land use type were the main influencing factors of the industrial source, traffic source, natural source, and agricultural-industrial mixed sources, respectively. The results of this study can provide scientific basis for environmental management and pollution control of heavy metals in soil.

Ground-penetrating radar (GPR) is effective in detecting voids in airport runways. However, accurate automated void detection remains challenging due to multi-scale void heterogeneity and inevitable clutter from embedded infrastructures. To address this issue, this study proposes a novel framework integrating Block-Matching and 3D filtering (BM3D) for clutter suppression with a specialized AIL-YOLO model to detect multi-scale runway voids from 3D GPR data. Large-scale field survey was conducted at 12 airports to obtain real-world data using 3D GPR. Optimized BM3D algorithm was employed to effectively suppress clutter from GPR images. On this basis, AIL-YOLO model was proposed to enhance multi-scale feature extraction and suppress background interference. Experimental results show that the proposed method achieves 94.6 % accuracy at 31.6 FPS-surpassing state-ofthe-art models. Our automated detection method demonstrates a 40-fold improvement in detection speed over manual interpretation methods. The methodology is validated through field tests of core samples, confirming its practical feasibility. Our method provides an automated solution for monitoring the defect areas and can be integrated with Automated Guided Vehicle (AGV) mounting a 3D GPR system to enhance operational safety of airport runways.

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To address the problem of low efficiency and potential safety hazards in the cleaning of highway tunnel cameras at height, this study proposes a high-pressure water jet method to clean the lens surfaces of the cameras, and designs a cleaning device with six-degree freedom. The composition of the contaminants is analyzed using the Fourier transform infrared spectrometer（FTIR） based on the contaminants on the surface of the tunnel cameras. To achieve a good combination of parameters for the cleaning process, 70 camera samples are collected in the tunnels around the Yuhua Palace in Shaanxi Province, and a cleaning parameters optimization test is carried out through the single factor variable method. Then, the images are processed through the method of "graying + sharpening + binarization", so as to investigate the impact of the cleaning pressure（0.5～2 MPa）, the cleaning spacing（0.3～1.5 m）, and cleaning time（0.2～2 s） on the cleaning efficiency. The test results show that the main components of the contaminants on the shell surface of the tunnel cameras are carbon black and PAHs, while those on the lens surface are mainly particulate fugitive dust.The better combination of parameters for the cleaning process is as follows: cleaning pressure 0.5 MPa, cleaning spacing 1 m, and cleaning time 0.4 s（clean twice with an interval of 0.2 s）. In this combination of parameters, the cleaning efficiency is over 99%.

The dimension of the void area in pavement is crucial to its structural safety. However, there is no effective method to measure its geometric parameters. To address this issue, a void size extraction algorithm based on the continuous wavelet transform (CWT) method was proposed using ground-penetrating radar (GPR) signal. Firstly, the finite-difference time-domain (FDTD) method was used to investigate the GPR response of void areas with different shapes, sizes, and depths. Next, the GPR signal was processed using the CWT method, and a 3D image based on the CWT result was used to visualize the void area. Based on the differences between the void and normal pavement in the time and frequency domains, the signal with maximum energy from the CWT time-frequency result was extracted and combined to reconstruct the new B-scan image, where void areas have energy concentration phenomenon. Based on this, width and depth of void detection algorithm was proposed to recognize the void area. Finally, the detection algorithm was verified both in numerical model and physical lab model. The results indicated that the CWT time-frequency energy spectrum can be used to enhance the void feature, and the 3D CWT image can clearly visualize the void area with a highlighted energy area. After fully testing and validating in numerical and lab models, our proposed method achieved high accuracy in void width and depth detection, providing a precise method for estimating void dimension in pavement. This method can guide DOT departments to carry out pre-maintenance, thereby ensuring pavement safety.

To explore the impact of heavy metals in pollutant emissions from a coal-fired power plant on the soil environment of surrounding farmland, 31 farmland soil sampling sites were set up with the chimney of the power plant as the center using the radiation ring method. The contents of 10 heavy metals in the soil were determined using inductively coupled plasma mass spectrometry(ICP-MS). The characteristics and potential ecological risks of heavy metals in the soil were analyzed. The spatial differentiation and pollution characteristics of heavy metals were investigated based on geostatistical spatial interpolation and an AERMOD diffusion model, and the source analysis of heavy metals was conducted using a PMF receptor model. The results showed that:① the mean contents of the heavy metals ω(Pb), ω(Mn), ω(Zn), ω(Cr), ω(Ni), ω(Cu), ω(As), ω(Co), ω(Hg), and ω(Cd) in farmland around coal-fired power plants were 414.46, 286.38, 155.22, 69.54, 55.77, 53.48, 31.73, 19.86, 0.78, and 0.71 mg·kg-1, respectively. The contents of Hg, Pb, Cd, As, Zn, and Cu all exceeded the background values of Shaanxi Province by 26, 19.36, 7.88, 2.83, 2.23, 2.49, 1.87, 1.11, and 1.93 times, respectively. ② The mean value of the potential ecological risk index(RI) of heavy metals in the soil around the coal-fired power plant was 714.53, indicating a strong ecological risk level, and there were high-value rich areas near the Qianhe railway station and the oil and gas company. The single potential ecological risk index(Ei) of the Hg element was 520.92, which was at a very strong ecological risk level. ③ The main sources of heavy metals in the soil around the coal-fired power plant were dust removal sources from coal burning(32.16%), industrial and agricultural activities(19.78%), natural sources(26.25%), and traffic sources(21.81%). The high heavy metal content in the soil was distributed in the range of 1-2 km from the power plant, whereas the heavy metal content was low in the range of 1 km from the power plant, increasing gradually in the range of 1-2 km and then decreasing gradually when it was greater than 2 km. The spatial differentiation and enrichment characteristics of heavy metals in farmland around the power plant obtained in this study can provide theoretical and data support for soil pollution control.

针对普通比例阀放大器响应慢而无法实现负载敏感液压系统冲击的问题,提出用车载PLC的快速性响应PWM口直接驱动实现主阀快速响应,研究负载敏感液压系统的冲击特性.以A10VSO28DFR泵和M4-12阀构建的负载敏感液压系统为对象,采用上下位机通信方式实现冲击试验的控制和参数采集.上位机以LabVIEW为软件平台,通过NI9223板卡采集液压系统的压力和流量参数,通过PEAKUSB/CAN卡实现液压系统的功能控制,并用队列消息机制、全局变量和多线程编程方式,设计了液压系统参数采集系统和CAN总线通信系统.下位机采用Hersmor G16控制器设计了液压阀控制系统,接收上位机的控制指令,实现主阀的定时关闭和开口大小的控制.在液压试验台架上进行冲击特性试验,结果表明:设计的测控系统能以10 ms为时间基准控制主阀关闭速度和开口大小,采用队列的方式可正确采集冲击特性曲线,设计的测控系统可满足负载敏感液压系统的冲击特性试验要求;通过台架验证了消除多余流量的冲击特性削减方法的有效性,提高了系统稳定性.提出的车载PLC驱动液压阀的液压台架测控方案,可为液压测控平台和液压系统性能研究提供参考.

标准养护条件下,以0％、30％、60％与100％铁尾矿替代石英砂制备活性粉末混凝土(RPC),为探究高温对其性能的影响,进行了200、400、600与800℃高温后铁尾矿RPC强度试验、阻尼试验、X射线衍射(XRD)试验和扫描电镜(SEM)试验,分析了温度与铁尾矿掺量对RPC表观特征、质量损失、抗压与抗折强度、阻尼性能以及微观结构的影响.结果表明,随着温度升高,铁尾矿RPC质量损失率增大,抗压与抗折强度降低,阻尼比提高,CH峰强度降低,砂浆基体由完整变得松散并且孔隙率与微裂纹数量提高;随着铁尾矿取代率的增加,RPC表观裂纹增多,质量损失率增大,抗压与抗折强度降低,阻尼比提高.

为研究湿喷机的智能控制方法,以某湿喷机机械臂装置为研究对象,采用Creo建立机械臂的机械模型,导入到Automation Studio,与利用Automation Studio平台构建的液压模型与电气控制模型关联,构建湿喷机样机的机电液联合仿真模型.在Automation Studio中进行功能试验,结果表明:联合仿真模型中湿喷机的工作装置功能正确,液压系统可有效反馈负载变化,电气系统可实现工作装置的动作,验证了该仿真模型的正确性.

In order to realize the automatic calibration of fiber optic hydrophone with wide frequency, the principle of heterodyne method is studied in this paper. And combined with the standing wave field and free field calibration methods, a fiber optic hydrophone phase-shifted sensitivity calibration device is developed, which realizes the accurate calibration of the fiber optic hydrophone in the frequency range of 20 Hz to 50 kHz. The measurement uncertainty of the calibration device is 1.5 dB (k = 2).

为保证高速公路山岭隧道施工质量和施工安全性并解决长大隧道工期受限的问题,拟采用机械化施工与光面爆破法相结合实现安全、质量可靠的隧道施工.针对隧道施工中钻爆法存在的隐患问题,以郑西高速伏牛山特长公路隧道施工作业为研究对象,研究以三臂凿岩台车为主的机械化施工工法,提出适合不同围岩情况的凿岩台车施工技术和爆破安全控制技术.结果表明,与传统的人工钻爆法相比,采用凿岩台车进行机械化施工,提高了钻孔的精度和施工人员安全性,还有效降低了施工经济成本,并形成了一套机械化安全可靠、质量可控、经济适用的开挖施工工法,有利于三臂凿岩台车在长大隧道中断面围岩机械化开挖施工中的应用与推广.

Due to various human activities, soil quality under different land use patterns is deteriorating all over the world. This deterioration is very complex in the river irrigation area and is caused by multi-point and non-point source pollution and seasonal variation. Therefore, the characteristics and sources of soil metal pollution in river irrigation area of Baoji city were analyzed. The contents of 8 metals were given by ICP-MS, in the soil samples. Statistical methods, geo-accumulation index ( I geo ) and potential ecological risk index ( RI ) were conducted to evaluate the spatial distribution features, sources and ecological risks of metal contamination from the study area soil. Principal component analysis and cluster analysis were used to analyze the pollution sources of metal. The analysis showed that Cd is the most polluted, and human activities represented a great impact on the contents of Zn, Ni, Cu and Cd in soil, Cd post moderate-strong pollution and strong risk, Cd has a maximum Igeo value of 3.17. All rivers were at risk of moderate pollution levels in study . Among them, some rivers had even reached strong pollution level. Pollution caused by human activities was the most significant pollution source of metal in the research area soil.

针对公路养护设备种类多、数量大和分属地散乱造成设备管理和维护困难的问题,提出用GPRS DTU模块互联养护设备和构建信息化管理系统的方法来管理养护设备.针对养护设备通信协议多的问题,设计了基于模板匹配的多协议解析模块,解析和采集设备作业参数;利用云平台技术、B/S架构和SQL Sever数据库构建了信息化管理系统,并以高速公路用绿篱机为对象,进行了功能试验.结果表明,设计的养护设备信息化管理系统功能正确,能实现绿篱机作业参数的监控和管理,并可统计分析出设备的养护路段、作业效率以及设备分布,这为公路养护设备的智能化管理提供了参数依据.

Human-multi-robot collaboration is becoming more and more common in intelligent manufacturing. Optimal assembly scheduling of such systems plays a critical role in their production efficiency. Existing approaches mostly consider humans as agents with assumed or known capabilities, which leads to suboptimal performance in realistic applications where human capabilities usually change. In addition, most robot adaptation focuses on human-single-robot interaction and the adaptation in human-multi-robot interaction with changing human capability still remains challenging due to the complexity of the heterogeneous multi-agent interactions. This paper proposes a real-time adaptive assembly scheduling approach for human-multi-robot collaboration by modeling and incorporating changing human capability. A genetic algorithm is also designed to derive implementable solutions for the formulated adaptive assembly scheduling problem. The proposed approaches are validated through different simulated human-multi-robot assembly tasks and the results demonstrate the effectiveness and advantages of the proposed approaches.

The invention provides an excavator and a coal mining system. The excavator comprises a base, a rotating table, a first rod body, a second rod body, a grab bucket, a connecting rod assembly and a driving assembly, wherein the rotating table is arranged on the base in a way of being capable of horizontally rotating; the back end of the first rod body is arranged on the rotating table in a way of being capable of vertically rotating; the back end of the second rod body is connected with the front end of the first rod body in a way of being capable of vertically rotating; the grab bucket is connected with the front end of the second rod body in a way of being capable of vertically rotating; a breaking hammer is arranged on the grab bucket; the connecting rod assembly is connected between thegrab bucket and the front end of the second rod body; the driving assembly comprises a first driving element, a second driving element and a third driving element; the first driving element is arranged between the rotating table and the front side of the first rod body; the second driving element is arranged between the back side of the first rod body and the back end of the second rod body; and the third driving element is arranged between the back side of the second rod body and the connecting rod assembly.

为提高机电专业本科生的实践能力和创新能力,文章提出知识、能力、素质三位一体的复合型创新人才培养模式.以社会需求为导向,以能力培养为中心,以提高综合素质和创新能力为目的,修订机电专业人才培养方案,并通过互联网+的虚拟仿真实验和校企联合的工程实践试验,实施"知识传授和技能训练并重,强化创新能力综合实训"的培养体系,为工程机械领域培养机电专业复合型创新人才.

针对管道内部缺陷检测困难的问题,以Φ100～Φ120 mm管道为对象、电感传感器和视觉传感器为管内涂层缺陷检测传感器,基于主从控制方式设计了前后驱动的螺旋式管道检测机器人.针对机器人远程操控和数据传送的问题,提出了基于无线网桥和WLAN的远程通信方案和通信协议,采用C/S架构设计了机器人的远程测控系统,并在样机上进行功能试验.结果表明基于WLAN的方案可实现管道检测机器人的远程测控功能,采用视觉和电感传感器可有效检测涂层缺陷,涂层厚度检测偏差小于±3.2％,符合普通防腐等级偏差小于±5％的要求.该研究为管道机器人的远程防腐检测提供一种新方法.