A hardening load transfer function for rock bolts and its calibration using distributed fiber optic sensing

Confinement of rock bolts by the surrounding rock formation has long been recognized as a positive contributor to the pull-out behavior,yet only a few experimental works and analytical models have been reported,most of which are based on the global rock bolt response evaluated in pull-out tests.This paper presents a laboratory experimental setup aiming to capture the rock formation effect,while using distributed fiber optic sensing to quantify the effect of the confinement and the reinforcement pull-out behavior on a more local level.It is shown that the behavior along the sample itself varies,with certain points exhibiting stress drops with crack formation.Some edge effects related to the kinematic freedom of the grout to dilate are also observed.Regardless,it was found that the mid-level response is quite similar to the average response along the sample.The ability to characterize the variation of the response along the sample is one of the many advantages high-resolution fiber optic sensing allows in such investigations.The paper also offers a plasticity-based hardening load transfer function,representing a"slice"of the anchor.The paper describes in detail the development of the model and the calibration/determination of its parameters.The suggested model captures well the coupled behavior in which the pull-out process leads to an increase in the confining stress due to dilative behavior.

EXPERIMENTAL STUDY OF LOAD SENSING SYSTEM WITH LONG PIPES

A test platform is established as per the practical working condition ofelevating platform fire truck. The influences of pipes and load on dynamic characteristics ofload-sensing system are studied by series of step response experiments. Experimental results showthat the feedback pipe makes the most important influence on the dynamic response speed ofload-sensing system. Its internal diameter should be optimized for given length of pipe. On theother hand, the stability of load-sensing pump is improved as the length of input pipe increases ina certain range. The influence of input pipe on the dynamic response speed is caused mainly by thepressure-wave travel time in the input pipe.

Room temperature NO_2 gas sensing of Au-loaded tungsten oxide nanowires/porous silicon hybrid structure

In this work, we report an enhanced nitrogen dioxide（NO_2） gas sensor based on tungsten oxide（WO_3）nanowires/porous silicon（PS） decorated with gold（Au） nanoparticles. Au-loaded WO_3 nanowires with diameters of 10 nm–25 nm and lengths of 300 nm–500 nm are fabricated by the sputtering method on a porous silicon substrate. The high-resolution transmission electron microscopy（HRTEM） micrographs show that Au nanoparticles are uniformly distributed on the surfaces of WO_3 nanowires. The effect of the Au nanoparticles on the NO_2-sensing performance of WO_3 nanowires/porous silicon is investigated over a low concentration range of 0.2 ppm–5 ppm of NO_2 at room temperature（25℃）. It is found that the 10-？ Au-loaded WO_3 nanowires/porous silicon-based sensor possesses the highest gas response characteristic. The underlying mechanism of the enhanced sensing properties of the Au-loaded WO_3 nanowires/porous silicon is also discussed.

A Multi-mode Electronic Load Sensing Control Scheme with Power Limitation and Pressure Cut-off for Mobile Machinery

In mobile machinery,hydro-mechanical pumps are increasingly replaced by electronically controlled pumps to improve the automation level,but diversified control functions(e.g.,power limitation and pressure cut-off)are integrated into the electronic controller only from the pump level,leading to the potential instability of the overall system.To solve this problem,a multi-mode electrohydraulic load sensing(MELS)control scheme is proposed especially considering the switching stability from the system level,which includes four working modes of flow control,load sensing,power limitation,and pressure control.Depending on the actual working requirements,the switching rules for the different modes and the switching direction(i.e.,the modes can be switched bilaterally or unilaterally)are defined.The priority of different modes is also defined,from high to low:pressure control,power limitation,load sensing,and flow control.When multiple switching rules are satisfied at the same time,the system switches to the control mode with the highest priority.In addition,the switching stability between flow control and pressure control modes is analyzed,and the controller parameters that guarantee the switching stability are obtained.A comparative study is carried out based on a test rig with a 2-ton hydraulic excavator.The results show that the MELS controller can achieve the control functions of proper flow supplement,power limitation,and pressure cut-off,which has good stability performance when switching between different control modes.This research proposes the MELS control method that realizes the stability of multi-mode switching of the hydraulic system of mobile machinery under different working conditions.

Relationship between Vegetation Index and Forest Surface Fuel Load in UAV Multispectral Remote Sensing

[Objectives]To explore the relationship between vegetation index and forest surface fuel load.[Methods]UAV multispectral remote sensing was used to obtain large-scale forest images and obtain structural data of forest surface fuel load.This experimental area was located in Gaoming District,Foshan City,Guangdong Province.The average surface fuel load of the experimental area was as high as 39.33 t/ha,and the forest surface fuel load of Pinus elliottii was the highest.[Results]The normalized difference vegetation index(NDVI)and enhanced vegetation index(EVI)had a moderately strong correlation with the forest surface fuel load.The regression model of NDVI(X)and forest surface fuel load(Y)was established:Y=-5.9354X+8.4663,and the regression model of EVI(X)and forest surface fuel load(Y)was established:Y=-5.8485X+6.7271.The study also found that the linear relationship between NDVI and surface fuel load was more significant.[Conclusions]Both NDVI and EVI have moderately strong correlations with forest surface fuel load.NDVI is moderately or strongly correlated with the surface fuel load of Pinus massoniana forest,shrub grassland,broad-leaf forest and bamboo forest,while EVI is only strongly correlated with surface fuel load of broad-leaf forest and bamboo forest.It is expected that the relationship between other vegetation indices and forest surface fuel load can be obtained by the method in this study,so as to find a more universal vegetation index for calculating surface fuel load.

Modeling load distribution for rural photovoltaic grid areas using image recognition

Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”objectives.However,rural power grids often lack digitalization;thus,the load distribution within these areas is not fully known.This hinders the calculation of the available PV capacity and deduction of node voltages.This study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid areas.First,houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 model.The distribution of the houses is then used to estimate the load distribution in the grid area.Next,equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution lines.Finally,by calculating the connectivity matrix of the nodes,a minimum spanning tree is extracted,the topology of the network is constructed,and the node parameters of the load-distribution model are calculated.The proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid areas.The results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters,thereby offering vital support for determining PV access capability.

Feasibility study on buoyancy-weight ratios of a submerged floating tunnel prototype subjected to hydrodynamic loads

The research progress of a novel traffic solution,a submerged floating tunnel（SFT）,is reviewed in terms of a study approach and loading scenario.Among existing publications,the buoyancy-weight ratio（BWR） is usually predefined.However,BWR is a critical structural parameter that tremendously affects the dynamic behaviour of not only the tunnel tube itself but also the cable system.In the context of a SFT prototype（SFTP） project in Qiandao Lake（Zhejiang Province,China）,the importance of BWR is illustrated by finite element analysis and subsequently,an optimized BWR is proposed within a reasonable range in the present study.In the numerical model,structural damping is identified to be of importance.Rayleigh damping and the corresponding Rayleigh coefficients are attained through a sensitivity study,which shows that the adopted damping ratios are fairly suitable for SFTP.Lastly,the human sense of security is considered by quantifying the comfort index,which helps further optimize BWR in the SFTP structural parameter design.

从释意理论看电影《你好,李焕英》幽默元素字幕的翻译策略

字幕翻译是观众了解非母语影视的主要手段,优秀的字幕翻译也成为海外观众更好地了解中国电影和中国文化的重要途径。字幕翻译同口译不乏相通之处,因此源于口语实践研究、倡导脱离源语言外壳束缚的释意理论,不仅指出了译者在字幕翻译过程中应了解的原则和方向,也启发译者跳出具体翻译策略的限制,根据具体情况灵活采取合适的翻译策略,对于电影字幕翻译具有实际的指导意义。华语喜剧电影中的幽默元素体现了中国浓厚鲜明的民族文化特色,是译者较难处理的部分。电影《你好,李焕英》在翻译诸如双关语、特色方言、富有时代感的流行语和富含中国文化特色的话语这些包含幽默元素的字幕时采取了替换、归化、异化、减译等不同翻译策略。

温度和湿度对P-CNT自感知混凝土压敏性的影响

为研究温度与湿度对自感知混凝土(SSC)感知性能的影响,通过低温等离子体改性处理技术对碳纳米管(CNT)进行官能团嫁接,使其在水性体系下获得较好的分散性,并将改性后的CNT(P-CNT)加入混凝土中制备P-CNT/SSC传感器,通过改变含水率与温度条件研究P-CNT/SSC传感器的极化效应与循环加载下的自感知性能。试验结果表明:过高或过低的含水率均不利于SSC的感知性能,其中变化最为明显的是饱水状态下的P-CNT/SSC传感器,其应力敏感系数下降89.8%,并且压敏曲线极不稳定;在变温试验中,P-CNT/SSC传感器的电阻率与温度之间呈现负相关性,高温和低温下的应力敏感系数相较于常温组试件,分别下降了约35.66%和44.53%,并且压敏曲线整体出现了上移或下滑的趋势;P-CNT/SSC传感器在工程应用中的最佳测试环境为常温、自然含水率。

掘进机器人行驶状态嵌入式传感系统研究

针对掘进机器人履带行驶结构作业处于高冲击、碰撞、高湿度和复杂煤岩底质等空间受限环境、受到的外部动载荷通常无法直接测量或测量比较复杂问题,提出了一种可实时监测掘进机器人履带动载荷的嵌入式传感系统无线监测方法。设计了适用于掘进机器人的特种履带行驶结构,搭建基体-夹板-无线采集模块等组成的多层复合封装防护结构,在封闭环境下对嵌入式传感系统进行无线传输特性及行驶状态下的动应力分布研究,并进行传感系统封装集成的测试精度标定试验。将嵌入式传感系统随机替换履带链环中的一块山型减振垫,对掘进机器人行驶状态周期循环的履带载荷历程进行监测测试。结果表明,该嵌入式传感系统在不改变履带链环整体受力的前提下,能实时采集履带行驶结构的动载荷并无线传输给上位机,动载荷时间历程数据完备、稳定可靠,解决了井下极端工况下掘进机器人履带行驶结构动载荷获取难题。

重型拖拉机负载敏感电液提升系统研究现状

主要介绍了负载敏感电液提升系统在农业领域中对于重型拖拉机的重要作用。首先,详细阐述了负载敏感电液比例阀和电液提升系统的原理和功能,然后从电液比例技术、插装阀技术和控制技术等方面对国内外研究现状进行了分析。接着,概述了该领域的主要进展和最新研究成果,并指出了存在的问题。最后,提出了未来重型拖拉机负载敏感系统研究的重点和发展方向,这将有助于学者更好地了解该领域并推动行业技术进步。

多工况车辆荷载下嵌入式压电传感路面结构动态响应分析

嵌入式智能装置与路面结构在车辆荷载作用下的动态响应对其服役性能和使用寿命意义突出。为此,采用1/4车辆振动模型,构建车辆动荷载作用下的嵌入式压电系统-路面结构有限元模型。基于足尺加速加载试验路段实测应变数据和文献振动数据,对有限元模型的响应结果进行了验证;进一步考虑了不同车辆轴载、车速和路面平整度等工况下,嵌入式路面结构的动态响应变化和压电系统的电压峰值输出。结果表明,路面结构的竖向加速度峰值、嵌入式压电系统的输出峰值随着车辆荷载的增加而增加,线性度良好;超载带来的横向应变峰值变化和竖向应变拉压交替峰峰值变化,需重点考虑;行驶速度对路面的振动和应变响应影响明显,均不为单调变化;随着路面等级从A级降为C级,路面各结构层平均竖向加速度从-10×10^(-3) g增加到-39×10^(-3) g,其中深度200 mm以内的三向振动增幅最为明显。该研究为嵌入式压电系统的实际应用和布置优化提供了支撑,也为智能道路的长期服役性能分析提供了依据。

基于压缩感知的纵向联邦学习园区负荷预测方法

随着园区负荷预测的重要性日益凸显,为满足电网公司和用电企业之间的数据安全和隐私保护需求,文章提出了一种基于压缩感知的纵向联邦学习园区负荷预测方法。该方法利用压缩感知技术对梯度进行降维压缩,有效减少了传输的数据量。实验结果显示,相较于传统的联邦学习方法,文章的方法在保持模型准确率的同时显著降低了通信消耗。此外,该方法还有效保护了数据的隐私性,为电网公司和用电企业提供了更安全的合作环境。

基于元件原理解析的掘进机液压系统故障诊断

当前矿用掘进机已向智能化和掘锚探一体化方向发展,使得其液压系统更加复杂。针对掘进机液压系统中关键元件结构原理复杂、故障机理分析专业性强、故障排查与处理难度大、效率低等问题,阐述了关键、复杂元件的功能特征,分析了其结构与工作原理。在此基础上总结了掘进机液压系统典型故障现象与特征,详细分析了故障的诱因及处理方法,提出了故障预防的措施,可为掘进机液压系统设计、使用、维护者在系统优化、故障高效判断及排除方面提供参考。

Multi-parameter load sensing pump model simulation and flow rate characteristics research

Load sensing pumps have been widely used in diverse hydraulic systems.Studies show that structural parameters have undeniable impacts on the characteristics and efficiency of the load sensing pump.The main purpose of this article is to study the influence of load sensing pump structure parameters on flow characteristics.In the present study,a nonlinear multi-parameter model is proposed for this type of pump.In this model,different parameters,including spool clearance,spool covering amount,internal leakage are considered to reflect the displacement adjustment process of the load sensing pump.Moreover,a frequency sweep method is proposed to analyze the frequency domain of the nonlinear mathematical model.An experiment rig was built to study the influence of key structural parameters on the dynamic follow-up characteristics of the pump flow.The obtained results show that the diameter of the orifice d can significantly affect the working characteristics of the pump.It is found that a large diameter of the orifice d can improve the phase following ability of the system,while a small diameter of the orifice d can reduce the bypass flow rate and increase the amplitude following ability.This paper provides a new consideration to study the dynamic follow-up characteristics of the load sensing pump.

红外遥感相机多负载制冷控制器的设计与实现

制冷控制器是红外遥感相机的重要部组件,其温控精度直接影响着相机成像质量。随着控温性能指标要求越来越高,相机部组件的制冷需求也越来越多,多功能、高性能、低重量、少成本的新型制冷控制器的研制变得越来越迫切。针对这些问题,本文设计集中型多负载红外遥感相机制冷控制器,采用电路模块复用与测控温分离的方法实现多负载控制。硬件上,在传统制冷控制器的基础上进行模块复用小型化设计,实现由“单电源、单主控、多驱动”组成的集中型硬件产品;提出“控制器+测温盒”的测控温分离方法,就近采集温度数据以保证测温精度,从而提高控温精度。软件上,配合硬件方案完成软件架构设计、测控温匹配设计、多负载驱动独立设计、温度数据可靠性设计。以此设计方案为基础,“一带三”制冷控制器的实验数据显示,该设计满足测控温匹配、驱动独立、精密控温的功能性能要求,同时±8mK的制冷控温精度完全满足了高质量成像要求,该方案可行。

压缩感知在非侵入式负荷监测中的应用展望

随着压缩感知(compressed sensing,CS)在智能电网中的应用不断深入,其在非侵入式负荷监测(non-intrusive load monitoring,NILM)领域的研究表现出滞后性。为此,在分析NILM中的CS应用必要性后,该文针对CS在NILM中的应用研究进行展望和探索。首先,对CS原理与NILM流程进行融合分析,提出压缩感知在非侵入式负荷监测中的3种应用模式;然后,针对3种应用模式的具体流程,展望各应用模式的研究方向和适用场景。在此基础上,从CS要素和负荷分析两个方面,重点探讨CS在NILM中应用所需解决的关键技术,设计适应NILM的测量矩阵、稀疏基和重构算法等CS要素的改进思路,提出在CS框架下事件探测、负荷分解、负荷识别、特征提取等负荷分析方法的实现思路。该文所做工作旨在探索CS在NILM中的应用,以期为后续研究提供指导。

Remote condition monitoring of rail tracks using distributed acoustic sensing(DAS):A deep CNN-LSTM-SW based model

Railroad condition monitoring is paramount due to frequent passage through densely populated regions.This significance arises from the potential consequences of accidents such as train derailments,hazardous materials leaks,or collisions which may have far-reaching impacts on communities and the surrounding areas.As a solution to this issue,the use of distributed acoustic sensing(DAS)-fiber optic cables along railroads provides a feasible tool for monitoring the health of these extended infrastructures.Nevertheless,analyzing DAS data to assess railroad health or detect potential damage is a challenging task.Due to the large amount of data generated by DAS,as well as the unstructured patterns and substantial noise present,traditional analysis methods are ineffective in interpreting this data.This paper introduces a novel approach that harnesses the power of deep learning through a combination of CNNs and LSTMs,augmented by sliding window techniques(CNN-LSTM-SW),to advance the state-of-the-art in the railroad condition monitoring system.As well as it presents the potential for DAS and fiber optic sensing technologies to revolutionize the proposed CNN-LSTM-SW model to detect conditions along the rail track networks.Extracting insights from the data of High tonnage load(HTL)-a 4.16 km fiber optic and DAS setup,we were able to distinguish train position,normal condition,and abnormal conditions along the railroad.Notably,our investigation demonstrated that the proposed approaches could serve as efficient techniques for processing DAS signals and detecting the condition of railroad infrastructures at any remote distance with DAS-Fiber optic cable setup.Moreover,in terms of pinpointing the train's position,the CNN-LSTM architecture showcased an impressive 97%detection rate.Applying a sliding window,the CNN-LSTM labeled data,the remaining 3%of misclassified labels have been improved dramatically by predicting the exact locations of each type of condition.Altogether,these proposed models exhibit promising potential for accurately identifying various railroad conditions,including anomalies and discrepancies that warrant thorough exploration.

中职实习护生压力负荷与职业获益感的现状及相关性研究

目的调查中职护生实习期间压力负荷和职业获益感现状,并分析两者间的相关性,为护生职业教育和心理健康教育提供依据,为临床输送合格的护理人才提供保障。方法采用量表对江西省某中职卫校护生进行调查。结果护生压力负荷中的事件负荷、个性脆弱与职业获益感呈负相关关系,其中个性脆弱与职业获益感的相关性更强。结论中职护生职业获益感处于中等偏上水平,仍需进一步提升。学校和医院要注重实习期课程设计,可在护生临床实习前,磨砺护生坚韧抗压的品质,以提高护生心理素质,稳定护士队伍,降低转行率和离职率。

基于小波变换的光纤轴载信号降噪方法研究

随着道路交通基础设施进入更加注重养护和管理的新阶段,精确掌握车辆轴载参数,对交通基础设施的设计、管养以及安全具有重大意义。现以光纤传感技术采集到的轴载信号为研究对象,旨在通过小波变换的方法来提升轴载信号降噪效果,优化信号分析的准确性。基于实验室采集的轴载信号来构建仿真信号,并通过定量对比,分析不同小波基和分解层数对降噪性能的影响,识别出最优的降噪参数组合。结果表明,8阶Symlets小波基结合5层分解层数在降噪处理中的性能最优,显著提高了信噪比,并有效降低了均方误差。该研究成果为实际光纤轴载信号的降噪处理提供了理论依据和实践指导,对智能交通水平提升和道路科学养护管理具有积极的推动作用。