液态产品销售系统的开发与应用

随着计算机技术的高速发展 ,计算机己在工业监控领域得到广泛应用。ＤＣＳ系统 (集散系统 )是以计算机为核心 ,综合运用了计算机技术、通讯技术、控制技术等高科技技术 ,实现工业生产过程的监视与控制。由于ＤＣＳ系统具有系统可靠性、应用灵活性、自由性、实时性、智能性、开放性等特点 ,所以其在工业控制领域己得到广泛应用 ,己成为当今计算机监控系统的主流。因此 ,我厂决定对原液态产品销售系统进行改造 ,用质量流量计和ＤＣＳ装置取代原销售系统 ,对液态产品的销售实现自动装车。1　系统组成整个销售系统由 2台操作站 (1台用于销售控制…     

需求电视(下)——结构,系统和应用

14.节目选择计算机 本VOD系统的每台节目选择计算机可支持6000用户。多路节目选择计算机容许多个6000用户系统添加到VOD系统中。每台节目选择计算机有多达6000个19.2kbit/secs接口空间(有30个通讯卡,每块印刷电路板有200     

温度试验设备群控系统的设计和研究

文章设计了一个多台温度试验设备的群控系统,该系统选用串口通讯端口,采用一条双绞线电缆作总线,并通过编写软件控制程序,实现对多台温度实验设备的温度量准确控制,对该研究的成果做了总结,并对群控系统的发展提出了展望。     

通信网关在FES Micro Ⅲ与DeltaV系统通讯中的应用

本文描述丘东处理厂两台19MXB-16MX的FES两级螺杆式丙烷制冷机压缩机的Micro Ⅲ控制盘通过安装设置ComMENT Gateway通信网关,实现了Micro Ⅲ与DeltaV系统通讯,提高机组运行水平,加强机组监控,使机组安全平稳运行。     

利用计算机实现汽车衡的自动计量管理

电子汽车衡在各工矿企业大量应用 ,但大多是人工计量 ,统计的工作量也很大。由司磅工手工填写磅单 ,手工统计汇总 ,工作效率低。为杜绝人为因素对称重计量的影响 ,我们决定利用计算机实现汽车衡的自动计量管理。一、系统硬件及软件现在电子汽车衡的称重显示仪表一般都具有RS- 2 32标准接口输出 ,该系统就是利用RS- 2 32串行口与称重仪表进行通讯。该系统硬件十分简单 ,它是由一台IPC - 5 0 0工业控制计算机和一台KX -1 2 2 1打印机组成 ,计算机通过RS2 32串行口与称重仪表联接 ,来采集仪表的称量值。本着通用性强、维护方便、扩充容易…     

基于LabVIEW的变频器监测控制系统设计

为了实现对化学反应中循环系统的自动化控制,设计了变频器监测控制系统。系统以LabVIEW为软件开发平台,基于队列消息处理器模式优化程序结构,利用LabVIEW中的VISA控制技术及串口实现了计算机与多台变频器在主从模式下的通讯。系统通过程序设计改善了循环系统的控制效率、准确性、安全性及可操作性,为由程序驱动的实验提供了技术储备。     

TES-1333R太阳能表用作光功率传感器的方法

通过详细分析1333R型太阳能表与厂家附带的计算机程序间的串口通讯规律,利用一台单片机代替计算机与之通讯,并将接收的测量信息由DA芯片转换为模拟量输出,成功的将这台太阳能表用作光功率传感器。     

串行通讯在远距离数据测量与监控中应用的研究

RS232-C是一个串行通讯的标准协议,被广泛地应用在工业生产的各个方面,本文简要介绍了它的工作原理。并在此基础上,利用VB6.0 ActiveX控件的MSComm通信控件,实现了Windows 2000下单台PC上位机与多台下位机(智能仪表)间的串行通讯,以及对现场智能仪表的集中控制和计量数据的自动采集。     

基于·Net的消息通讯技术研究

按照发送者和接受者所处的位置关系，基于Windows系统的消息通讯可以分为进程内通讯和进程间通讯。进程内通讯采用发布，订阅方式进行通讯是比较合理的一种通讯方式，进程间通讯可以采用多种方式，优选了简单易用并且实用的系统消息WM_COPYDATA方式，将两种通讯方式在．NET平台下进行集成和封装，以公用组件的方式应用于系统之中，既满足了系统的消息通讯，而且做到了模块之间的独立和通讯的独立。     

3G移动通信基站监控系统的设计

近年来，通讯系统的技术飞速发展，尤其是移动通讯系统，由之前的2G时代迅速过渡到了如今的3G时代。其实，促使通讯系统快速发展的最大动力就是广泛的客户。因为客户在通讯过程中对通讯的需求越来越大，对通讯的质量和速度都十分的渴求，所以促使了通讯系统现如今飞度发展的局面。     

基于光学小波变换的机器人视觉传感器设计

针对视觉系统处理速度慢的问题,利用光电信息技术设计出基于光学小波变换的机器人视觉传感器。该传感器用4 f光学处理系统实现光学小波变换滤波,以计算机编程加载滤波器,因此兼有光学信息处理的二维、高速、并行和大容量的优点,以及计算机控制灵活的优点。图像特征提取仿真实验结果表明:效果理想,处理速度快,方案可行。     

磷光体光纤温度检测系统的研究

叙述了磷光体的发光机理以及磷光余辉与温关系。通过对磷光体温敏元件与光纤组成的温度传感器的实验研究，提出了一种用单片机控制的实时采集检测系统。     

灵敏度自动设定的色标检测传感器

色标检测方法从原理上分为色度学方法和光度学方法两种。根据光度学色标、底色色差检 测原理,设计了灵敏度自动设定的色标检测传感器,该传感器由同轴光学系统和单片机构成,软件主要包括光源色自动选择判别算法,灵敏度自动设定算法及灵敏度设定点动态修正算法。实际应用表明该传感器给使用带来方便,且提高了动态检测可靠性。     

Digital thermometer circuit for silicon diode sensors

Silicon diode thermometers are now available commercially which conform closely to a specified, albeit non-linear characteristic. An inexpensive circuit has been developed which allows temperatures to be measured with a resolution of 0.01 K between 1.5 and 25 K, and 0.1 K between 25 and 375 K, and with an accuracy that in most applications will be limited by the calibration accuracy of the diode used. The design is based on a standard integrating analog to digital converter. A microprocessor is not required; precise linearization is achieved by means of a look-up table held in an EPROM. The circuit includes a simple digital interface for transferring data to a computer.     

Data-driven probabilistic quantification and assessment of the prediction error model in damage detection applications

Advances in computer hardware and sensor technologies have led to a surge in the use of data-driven modeling and machine learning for structural engineering applications, with Structural Health Monitoring (SHM) being one of them. Despite considerable interest, it remains a research topic due to the difficulty in accurately quantifying aleatoric and epistemic uncertainty in SHM systems. Sources of uncertainty are related to operational and environmental variability, as well as measurement noise and the model prediction error associated with the data used to train damage identification algorithms. In this work, the authors aim to explicitly quantify the statistical structure of model prediction error and assess its influence on the detection performance of strain-based SHM architectures under the existence of aleatoric variability. A structural beam, subjected to probabilistic static loading is used as the reference structure and strain measurements as the damage-sensitive features. Model prediction error is quantified explicitly using robust statistical tools through available laboratory observations and synthetic (Finite Element) data. Monte Carlo simulations enabled the forward propagation of uncertainty to the feature space to generate training data for three binary detectors (Likelihood Ratio Test, Quadratic Discriminant Analysis and Mahalanobis Distance), based on statistical pattern recognition. Detection performance was compared between the explicitly quantified prediction model error and the commonly assumed white Gaussian noise model, showcasing the influence of systematic error (bias) and correlation on the robustness of an SHM system using real-world data.     

A Cost-Efficient Environment Monitoring Robotic Vehicle for Smart Industries

Environmental monitoring is essential for accessing and avoiding the undesirable situations in industries along with ensuring the safety of workers. Moreover, inspecting and monitoring of environmental parameters by humans lead to various health concerns, which in turn brings to the requirement of monitoring the environment by robotics. In this paper, we have designed and implemented a cost-efficient robotic vehicle for the computation of various environmental parameters such as temperature, radiation, smoke, and pressure with the help of sensors. Furthermore, the robotic vehicle is designed in such a way that it can be dually controlled by using the remote control along with the distant computer. In addition, contrary to the existing researches, the GSM modules are used to achieve the two-way long distance communication between the robotic vehicle and the distant computer. On the distant computer, the above-mentioned environmental parameters can be monitored along with controlling the robotic vehicle with the help of Graphical User Interface (GUI). In order to fulfill the given tasks, we have proposed two algorithms implemented at the robotic vehicle and the distant computer respectively in this paper. The final results validate the proposed algorithms where the above-mentioned environmental parameters can be monitored along with the smooth-running operation of the robotic vehicle.     

光纤传感器系统中激光光强波动的特性及其补偿技术

本文针对He-He激光器的光强波动问题提出了一种新方法。在该方法中,光源输出的变化并没有得到抑制或控制,但可以消除它对测量结果的影响。结合和使用分光技术与微机技术,并建立了一相应系统。该系统结构简单可靠,它用于微位移和粗糙度测量系统中,获得了满意的效果和较高的精度。     

MEMS传感器在动态测试中的应用

本文在简单介绍了ＭＥＭＳ传感器的基础上，重点介绍了在ＭＥＭＳ传感器构成的测量系统，及其在高过载低量程测量中的应用。     

Novel Linear,Piezoresistive, Auxetic Sensors Coated by AAA Battery Active Carbons with Supreme Sensitivity for Human Body Movement Detection

Herein, a novel strategy for creating low-cost, sustainable, piezoresistive auxetic sensors using the active carbon in consumed AAA batteries, promoting a circular economy, is presented. An auxetic structure with a fixed Poisson's ratio during the strain is designed for sensing. The sensor substrate is silicone RTV2, and the sensing element is the active carbon in AAA batteries chopped to microscale particles using an ultrasonic wave. The sensor mold is designed using Solidworks software and produced using a computer numerical control device and EdgeCam2014 software. The coating process is performed by spraying the prepared particles on the molded auxetic structure and putting the coated auxetic structure under ultraviolet ray to prepare the final sensor. Sensitivity tests are performed, and the results show that the proposed sensor has a better sensitivity of about 1000% and 410% than the previous mixed and layered composite auxetic counterparts. The proposed sensor has linear sensitivity during the strain (estimated with a line with a slope of 0.64) while previous ones have a nonlinear performance (estimated at least with two lines). The sustainable sensor is implemented to detect the movements of the human body, including the movements of the wrist, finger, elbow, and forearm.     

Battery-Free,Wireless, Cuff-Type,Multimodal Physical Sensor for Continuous Temperature and Strain Monitoring of Nerve

Peripheral nerve injuries cause various disabilities related to loss of motor and sensory functions. The treatment of these injuries typically requires surgical operations for improving functional recovery of the nerve. However, capabilities for continuous nerve monitoring remain a challenge. Herein, a battery-free, wireless, cuff-type, implantable, multimodal physical sensing platform for continuous in vivo monitoring of temperature and strain from the injured nerve is introduced. The thin, soft temperature, and strain sensors wrapped around the nerve exhibit good sensitivity, excellent stability, high linearity, and minimum hysteresis in relevant ranges. In particular, the strain sensor integrated with circuits for temperature compensation provides reliable, accurate strain monitoring with negligible temperature dependence. The system enables power harvesting and data communication to wireless, multiple implanted devices wrapped around the nerve. Experimental evaluations, verified by numerical simulations, with animal tests, demonstrate the feasibility and stability of the sensor system, which has great potential for continuous in vivo nerve monitoring from an early stage to complete regeneration.