无线收发芯片nRF401在施工升降机控制系统中的应用

nRF401为单片无线收发芯片，施工升降机是高层建筑施工必备的运输设备之一，施工升降机自动控制系统包括楼层呼叫信号系统和吊笼主控系统。利用nRF401芯片很好地解决了施工升降机楼层呼叫信号系统与吊笼主控系统之间的信号传输及两吊笼主控系统之间运输协调．提高了施工升降机的运输效率。     

基于物联网的施工升降机监测系统设计

针对施工升降机监测系统监测效率低,监测参数不准确的问题,设计了一种基于物联网的施工升降机监测系统.利用物联网的三层架构实现数据采集、处理和传输功能;通过设置阈值实现施工升降机预警功能.同时使用九轴加速度传感器来获取加速度、速度和高度的实时状态,并运用楼层高度监测原理对传感器进行校准,以提高数据采集的准确性和实时性.实验...     

基于MMA7455的施工升降机安全控制系统的设计

针对当前施工升降机自动化程度低、安全管理弱的问题,设计了一种施工升降机自动化的远程安全控制系统。该系统由重量传感器采集重量信号,经加速度传感器校正后监测吊笼负载情况并报警。同时通过无线模块接收各楼层分机发送的呼叫信号,系统根据同向优先、就近优先的原则及吊笼载荷情况综合判断施工升降机起升运行,并利用GPRS模块进行远程监测报警。通过现场试验可知,该远程安全控制系统能有效提高运输效率和避免误报警情况,具有稳定性好、管理方便等特点。     

基于插值算法的升降机自动平层控制器设计

为将施工升降机由手动平层模式改造为自动平层模式,设计了一种基于传统的接触器控制电路的自动平层控制器。该控制器接收到驾驶人员通过按键输入的目标楼层指令后,比较目标楼层与吊笼当前所在楼层高度,接通相应继电器以驱动吊笼运行。此外,通过销轴式重力传感器实时采集吊笼的重力数据,并运用拉格朗日插值算法预算当前吊笼重力下的制动距离。通过增量编码器,循环检测吊笼至目标楼层实际距离。当实际距离与预算制动距离相差小于1 mm时,及时切断继电器便可使吊笼准确停靠到目标楼层。此外,由液晶显示屏显示吊笼的实时位置、运行方向、重力、制动距离以及平层误差等信息,实现友好的人机交互。经施工现场验证,自动平层控制器运行可靠、准确度高,能够满足使用要求。     

基于指纹识别的施工升降机安全监控系统设计

针对施工升降机在安全监控方面存在的问题,以及嵌入式系统中程序存储空间小需要对指纹算法进行改进与简化,提出了一种新的基于三角形面片的快速匹配算法识别的嵌入式施工升降机安全监控系统设计方法,使用新的指纹匹配的算法,减少了基准三角形对选取的时间,提高了指纹匹配的速度,以及使用STM32F103处理器和FPS200指纹传感器构建算法的嵌入式系统,成功实现了嵌入式施工升降机的安全监控的功能;指纹识别的准确率达到95%以上,具有很强的实用价值。     

人-机-环境中的在线安全监控策略研究

为了解决建筑工地的施工升降机监管普遍存在的无法有效监管到位的问题,建立了人-机-环境的施工升降机安全监控模型,提出了一种基于生物特征识别技术实现实名制管理和安装、使用、维保一体化监管的安全监管策略.设计和开发了在线安全监控系统,应用物联网和互联网技术,建立大数据管理平台,实现了信息化的施工升降机的安全监管策略.实际应用表明,该监控策略实现了对施工升降机的全方位安全监管,提高了施工升降机系统的安全性和可靠性.     

施工升降机防坠安全器嵌入式检测系统设计

作为施工升降机最重要的安全部件,防坠安全器的定期检测尤为重要。基于Android平台设计了SAJ30/40型齿轮渐进式防坠安全器嵌入式检测系统,分别采用角度传感器和速度传感器测量防坠安全器锥毂旋转角度和升降机实时运行速度,通过上位机分析软件进行数据处理,输出防坠安全器的制动距离和动作速度。现场试验架法检测实验结果表明,检测系统能够准确测量防坠安全器制动距离等检测参数,制动距离的测量精度为±1 mm。     

基于PLC电梯控制系统设计

电梯是高层建筑不可缺少的运输工具.用于垂直运送乘客和货物,传统的电梯控制系统主要采用继电器—接触器进行控制,其缺点是触点多,故障率高,可靠性差,维修工作量大等,而采用PLC组成的控制系统可以很好地解决上述问题,使电梯运行更加安全、方便、舒适,目前PLC在电梯行业已得到广泛应用.在层数和控制功能较少的场合,采用PLC控制较为方便.本设计主要利用欧姆龙系统完成.主要介绍了PLC的优点、PLC的工作原理和PLC控制电梯的软、硬件设计.通过PLC对电梯系统的控制来实现电梯的基本功能.具体要求为:根据轿厢所处位置及乘员欲达楼层,判定轿厢运行方向,保证轿厢平层时减速.将轿厢停在选定的楼层上;同时,根据楼层的呼叫,顺路停车,自动开关门;另外在轿厢内外均要有信号灯显示电梯运行方向及楼层数.     

专家语音通知系统中多队列多线程机制的实现

为了保证评标工作的公平性,提高专家呼叫的效率,基于多队列多线程技术,设计并实现了专家抽取与自动语音通知系统。系统采用模拟语音卡编程技术、多线程多队列机制实现专家呼叫的自动化、并发性。提出了抽取客户端与呼叫服务器的架构模式,并以此展开介绍了系统结构和发送接收请求的具体设计实现。文中的工作解决了人工呼叫容易泄密的问题,保障了相关工作规范高效地进行。系统已投入实际使用,运行良好。     

顺德人民医院网络设计实践

顺德人民医院共有五栋大楼,每栋楼之间有二根多模光纤接到楼层的交换机,楼层交换机再接二层交换机或集线器,实现了多模光纤上行达到1000M,有效解决了旧系统所造成的工作高峰期网络运行慢等弊端。同时,所有的布线整理后,解决了网线不规范的问题。 新的网络结构的完成,能够解决各部门的工作站数据交换越来越频繁的问题,特别是医嘱、病历、检验、图像等数据量都很大,处理高峰期,门诊收费、医嘱录入、病历书写、检验检查等都对响应速度要求甚高。该网络还实现了7×24小时的不间断运行。     

Thermal image-based hand gesture recognition for worker-robot collaboration in the construction industry: A feasible study

Worker-robot collaboration (WRC) is a promising solution for complex construction tasks, which can integrate the robots’ advantages in strength and accuracy with human ability in intuitive decision-making and adaptability. A new imperative objective for real-world WRC is to design a user-friendly interface to support safe and efficient worker-robot interactions. Vision-based hand gesture is a simple but effective solution. However, existing methods mainly depend on 3-channel RGB images captured by visible cameras, which are prone to be affected by on-site environmental disturbances, such as poor illumination, fog, and dust. Moreover, previous networks strive for high accuracy, neglecting computational efficiency (e.g., model size and latency) when implementing the network on resource-constrained devices like mobile construction robots. Against this backdrop, this research presented a feasibility study to investigate whether hand signals can be detected from thermal images and designed a lightweight network that has fewer parameters and obtains lower latency without compromising accuracy. Experimental results indicated that thermal images were robust to different lighting conditions, and the proposed model achieved a high classification accuracy (97.54 %) with 1.8 M parameters. The comparative study demonstrated the superiority of our model to other advanced lightweight models, illustrating the feasibility of the developed method in supporting safe WRC applications by recognizing workers’ hand signals.     

加权算法下短波地空信道质量排序及性能评估

综合LQA和预测两种模型下航线信道质量排序的特点,通过对航线信噪比进行统计分析,得出了LQA的时效性分布模型,并以此作为修订LQA信道质量排序的修正因子,结合长期预测模型,给出了加权算法下的信道质量排序方案,根据ALE工作模式,确立了性能评估准则,构造了建链成功率和平均建链时间的理论模型;经仿真验证,加权算法下确立的信道排序与实际信道质量排序相似度高,其一次建链成功率优于LQA模型和预测模型,航线各点平均建链时间短,为航线ALE呼叫建链时信道排序提供了理论依据。     

A new monocular vision measurement method to estimate 3D positions of objects on floor

A new visual measurement method is proposed to estimate three-dimensional (3D) position of the object on the floor based on a single camera. The camera fixed on a robot is in an inclined position with respect to the floor. A measurement model with the camera’s extrinsic parameters such as the height and pitch angle is described. Single image of a chessboard pattern placed on the floor is enough to calibrate the camera’s extrinsic parameters after the camera’s intrinsic parameters are calibrated. Then the position of object on the floor can be computed with the measurement model. Furthermore, the height of object can be calculated with the paired-points in the vertical line sharing the same position on the floor. Compared to the conventional method used to estimate the positions on the plane, this method can obtain the 3D positions. The indoor experiment testifies the accuracy and validity of the proposed method.     

解析Visual Basic过程调用中参数传递方式

过程调用作为Visual Basic程序设计的难点及重点之一,初学者对其中不同参数传递方式很难理解和掌握。为此提出了过程调用结合内存管理的新教学方法,将内存概念引入过程调用,通过分析计算机内存管理和Visual Basic程序运行的相互关系,对过程间不同参数的传递方式进行了解析,将抽象的过程执行步骤以直观的内存管理图示表现出来,帮助学生理解Visual Basic过程调用中的参数传递方式。该方法在教学实践中取得了良好的效果。     

Automatic path generation for group dance performance using a genetic algorithm

Designing dancers’ paths in choreography, or a floor pattern, is one of the most highly creative tasks of choreographers. Aiming to assist this task, this paper presents a novel system that automatically generates a number of floor patterns for multiple dancers given a choreographer’s high-level feature inputs. The proposed floor pattern model represents locomotor movements of dancers on stage. Through a dance literature survey, four major features, i.e., time, space, symmetry, and entropy, were selected as feature inputs and mathematically modeled. Our system uses a multi-objective genetic algorithm to achieve desired floor patterns given input features. It iterates from random floor patterns to the ones that satisfy users’ preferences while exploring the space of floor pattern with selection, mutation, crossover methods that are developed to fit the genotype of our system. User tests confirmed that our system generates a wide range of floor patterns according to user-specified input conditions. In addition, an actual dance piece was choreographed with the proposed method, which validated the usefulness of the proposed system. The proposed system is the first that automatically generates floor patterns for multiple dancers.

     

基于OpenGL的反舰导弹弹道视景仿真

针对导弹仿真系统开发中建模复杂且重复度高的问题,采用OpenGL库建立复杂模型的方法绘制了导弹飞行仿真所需的场景图像,建立了可用于导出模型的动态链接库,在对反舰导弹弹道特点进行认真分析的基础上,基于弹道规划原理,在VC环境下开发了可满足实际性能要求的弹道可视化仿真系统平台。对系统提供了真实的三维场景,可将弹道仿真节点计算出来的弹道数据以三维可视化技术展示出来。实验证明系统灵活通用,可提供完整的视景演示,为有效规划导弹弹道提供了有效支持。     

Calling communities analysis and identification using machine learning techniques

The analysis of social communities related logs has recently received considerable attention for its importance in shedding light on social concerns by identifying different groups, and hence helps in resolving issues like predicting terrorist groups. In the customer analysis domain, identifying calling communities can be used for determining a particular customer’s value according to the general pattern behavior of the community that the customer belongs to; this helps the effective targeted marketing design, which is significantly important for increasing profitability. In telecommunication industry, machine learning techniques have been applied to the Call Detail Record (CDR) for predicting customer behavior such as churn prediction. In this paper, we pursue identifying the calling communities and demonstrate how cluster analysis can be used to effectively identify communities using information derived from the CDR data. We use the information extracted from the cluster analysis to identify customer calling patterns. Customers calling patterns are then given to a classification algorithm to generate a classifier model for predicting the calling communities of a customer. We apply different machine learning techniques to build classifier models and compare them in terms of classification accuracy and computational performance. The reported test results demonstrate the applicability and effectiveness of the proposed approach.     

Comparison of the ParTrack mud/cuttings release model with field data

The oil industry promotes the development of numerical models for prediction of impacts from their discharges to sea. A model for the simulation of the spreading and deposition of drilling mud and cuttings on the sea floor as well as the spreading of chemicals (and small-sized particles) in the water column has been developed. The simulation is based on a Lagrangian ‘particle’ approach, which means that the properties of the discharge are represented by moving ‘particles’ in the model domain. The initialization of the particles is based on the output from an Eulerian near field underwater plume model. In addition, the model applies external current fields for the horizontal advection of the particles.This paper presents a comparison between simulated and measured concentrations of barium (barite) in surface contaminated sediment in the vicinity of an oil production field. As a part of the regular surveillance of oil production sites on the Norwegian Continental Shelf, the barium content in surface sediments is measured. These data might therefore serve as an opportunity for comparing simulation results with measured depositions of barium (barite) on the sea floor.The paper explains details in the comparison made between the measured barium concentrations in the sediment and the simulated deposition on the sea floor from the drilling of three exploration wells and 18 production wells off the west coast of Norway.     

基于RS232C协议的并发帧碰撞模型与呼叫策略研究

RS232C协议的主从通讯模式，限制了分布式控制系统（DCS）中的控制中心对来自现场终端的随机事件自的实时响应能力，降低了整个DCS系统的系统扩展能力和系统可靠性．研究了RS232C协议接口电气特性和DCS系统网络的工作特性，分析了基于RS232C协议的并发呼叫帧发生碰撞的机理，并研究了由并发碰撞引起的帧错误类型．引入了泊松流以描述系统中的多主呼叫过程，建立了基于RS232C串行通讯协议的并发帧碰撞模型．呼叫帧格式、传输速率和呼叫密度共同决定了发生帧碰撞的概率．平均呼叫密度小于10次／秒时，发生帧碰撞的概率小于0．01％，并可以被多主呼叫策略所标识，连续两次呼叫失败的概率小于0．0001％，表明：基于RS232C的多主呼叫协议是可行的．为即插拔多主RS232C通讯协议设计提供了理论依据．     

“What do you want for dinner?” – need anticipation and the design of proactive technologies for the home

This paper examines ‘the routine shop’ as part of a project that is exploring automation and autonomy in the Internet of Things. In particular we explicate the ‘work’ involved in anticipating need using an ethnomethodological analysis that makes visible the mundane, ‘seen but unnoticed’ methodologies that household members accountably employ to organise list construction and accomplish calculation on the shop floor. We discuss and reflect on the challenges members’ methodologies pose for proactive systems that seek to support domestic grocery shopping, including the challenges of sensing, learning and predicting, and gearing autonomous agents into social practice within the home.