Automatic Generation Method of Geological Cross-Sections in Dredging Engineering Based on 3D Solid NURBS Models

An automatic generation method of geological cross-sections in dredging engineering based on 3D geological solid models is presented.The 3D geological models are built applying the non-uniform rational B-splines(NURBS) technique,and a 2D profile can be calculated and generated automatically through Boolean operation to meet the demands of dredging projects.Moreover,an automatic marking method for geological attributes is put forward based on database technology,and the geological attributes include the profile name,scale,horizontal and vertical relative coordinates,geological lithology,and 2D standard lithology legend.At the same time,the automatic marking method can also provide an interactive mode for geological engineers to edit and modify the profile in the modeling system.Practical engineering applications show that the automatic generation method is a simple,flexible,fast and precise visual graphics rendering process that can create 2D standard profiles automatically and efficiently.This method also provides a convenient support tool for geological engineering digital analysis.

Preliminary Study on the Differences between Automatic-observed and Manual-observed Wind Speed and Its Correction

Comparing and analyzing the difference between automatic-observed and manual-observed wind speed based on the wind speed parallel observations in two methods, we find that many elements can influence the difference between automatic-observed and manual-observed wind speed, including the levels of speed wind, observation instruments and different regions. According to these elements, correction has been conducted, and find that the correction according to the level of wind speed has the best correction effect.

Automatic Recognition Method for Optical Measuring Instruments Based on Machine Vision

Based on a comprehensive study of various algorithms, the automatic recognition of traditional ocular optical measuring instruments is realized. Taking a universal tools microscope(UTM) lens view image as an example, a 2-layer automatic recognition model for data reading is established after adopting a series of pre-processing algorithms. This model is an optimal combination of the correlation-based template matching method and a concurrent back propagation(BP) neural network. Multiple complementary feature extraction is used in generating the eigenvectors of the concurrent network. In order to improve fault-tolerance capacity, rotation invariant features based on Zernike moments are extracted from digit characters and a 4-dimensional group of the outline features is also obtained. Moreover, the operating time and reading accuracy can be adjusted dy-namically by setting the threshold value. The experimental result indicates that the newly developed algorithm has optimal recognition precision and working speed. The average reading ratio can achieve 97.23%. The recognition method can automatically obtain the results of optical measuring instruments rapidly and stably without modifying their original structure, which meets the application requirements.

A Method for Modeling the Virtual Instrument Automatic Test System Based on the Petri Net

Virtual instrument is playing the important role in automatic test system. This paper introduces a composition of a virtual instrument automatic test system and takes the VXIbus based a test software platform which is developed by CAT lab of the UESTC as an example. Then a method to model this system based on Petri net is proposed. Through this method, we can analyze the test task scheduling to prevent the deadlock or resources conflict. At last, this paper analyzes the feasibility of this method.

A FULLY AUTOMATIC SYSTEM FOR INAA

A fully automatic system at HWRR of CIAE for INAA is described. All processes of the system, for example, change, transfer and irradiation of sample, data collection and treatment and so on are automatically controlled by an IBM- PC/XT micro- computer. Its applications are as follows: fully automatic determination of uranium content by delayed neutron counting method; fully automatic multielement INAA for short, middle and long lived nuclides.

Fault Analysis and Maintenance of DZZ Series of Automatic Weather Stations

The instruments of regional automatic weather station are placed outside to measure daily changes of meteorological factors. Due to common influence of sun,wind,rain and other factors,it is very easy to cause various faults and damages of the instrument. The construction of regional automatic weather station network plays an important role in improving forecast accuracy,servicing local government and ecological civilization construction,providing scientific disaster prevention and relief decision-making basis for government department. In this paper,based on daily operation situation of regional automatic weather station in Shaoyang region,combining communication,hardware and software,fault situation of collector,temperature and humidity sensor,wind sensor and rainfall sensor in automatic weather station is analyzed in detail. Moreover,some common fault cases are listed and analyzed,some troubleshooting methods are summarized,and daily maintenance measures are proposed.

On the Existence of an Optimal Control of Ship Automatic Steering Instruments

The existence of linear quadratic optimal control of ship automatic steering instruments is studied. Firstly, the sufficient conditions for the quadratic integrability of the solutions of linear second order time-variant differential equations are developed. Secondly, the optimal control form of the ship automatic steering instrument is obtained by using the dynamic programming method, which guarantees a minimal ship sway range, during long-distance navigation, by using as little energy as possible. Finally, based on the above mentioned sufficient conditions, the conditions for the realization of optimal control are obtained, which provides a foundation for choosing the weighted coefficients for optimal control in engineering.

Prototyping low-cost automatic weather stations for natural disaster monitoring

Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable measurements.However,such professional instrumentation is notably expensive while remote sensing from a number of stations is paramount.This imposes challenges on the large-scale weather station deployment for broad monitoring from large observation networks such as in Cemaden—The Brazilian National Center for Monitoring and Early Warning of Natural Disasters.In this context,in this paper,we propose a Low-Cost Automatic Weather Station(LCAWS)system developed from Commercial Off-The-Shelf(COTS)and open-source Internet of Things(IoT)technologies,which provides measurements as reliable as a reference PWS for natural disaster monitoring.When being automatic,LCAWS is a stand-alone photovoltaic system connected wirelessly to the Internet in order to provide real-time reliable end-to-end weather measurements.To achieve data reliability,we propose an intelligent sensor calibration method to correct measures.From a 30-day uninterrupted observation with sampling in minute resolution,we show that the calibrated LCAWS sensors have no statistically significant differences from the PWS measurements.As such,LCAWS has opened opportunities for reducing maintenance costs in Cemaden's observational network.

Design of mobile sensing system for automatical measurement

Based on mobile devices as a solution for measurement faces interesting challenges, which involve poor human- computer interaction and limited computer capability. In this paper, we present the mobile sensing system （MSS） with func- tions of constructing, configuring and implementing measurement applications. MSS consists of a mobile device and a sensor probe, In the mobile device we install a pocket virtual instrument platform （PVIP）, which has object-oriented software ar- chitecture and can be configured through extensible markup language （XML） files. And these configuration files can be written to the probe. Therefore, the probe can produce the measurement of APP in the mobile device. This infrastructure has been illustrated by a sound signal acquisition task and a flexible force measurement task which are finished with an android smartphone and a probe. These examples suggest that MSS is reconfigurable, highly automatical and flexible.

AVEVA Instrumentation仪表安装图设计及自动汇料开发

针对传统设计模式下仪表安装图方案不统一、仪表安装材料统计繁琐等问题,提出了一种基于AVEVA Instrumentation软件(AI软件)Design模块的安装图生成及自动汇料的开发方案。该方案的开发核心是建立1套典型的安装图库及安装材料库,并将其作为种子库存储于SQL数据库中,供工程设计人员调用。该方案通过调用定制的数据库能够快速生成安装图,且在完成仪表安装材料报表定制的基础上,进一步精确地统计安装材料,提高了设计效率和准确率。

全自动凝血分析仪在子痫前期患者凝血功能检测中的临床应用

目的 探究全自动凝血仪在子痫前期患者凝血功能检测中的应用。方法 选取本院2019年3月-2022年3月期间的120例子痫前期患者设为研究组。轻度患者70例,重度患者50例,设为轻度组和重度组。同期选取正常妊娠孕妇120例设为对照组。采用CS-5100全自动凝血分析仪对活化部分凝血活酶时间(APTT)、凝血酶原时间(PT)、纤维蛋白原(Fib)、凝血酶时间(TT)、D-二聚体(D-D)、纤维蛋白原降解产物(FDP)、抗凝血酶-Ⅲ(AT-Ⅲ)水平进行检测;计算不同浓度凝血七项不精密度CV值;测定APTT、PTTT日间不精密度;评判Fib、D-D、FDP、AT-Ⅲ的携带污染率,观察检测结果。结果 与对照组和轻度组相比,研究组和重度组的APTT、PT、TT、AT-Ⅲ水平降低,Fib、D-D、FDP水平升高(P <0.05);APTT、PT、Fib不同浓度(正常、中度、高度)水平的批内不精密度分别为0.475%~2.664%、0.632%~1.066%、1.995%~3.615%;单水平项目TT、D-D、FDP、AT-Ⅲ的CV批内分别为0.712%、4.241%、6.301%、5.441%;APTT、PT、TT日间不精密度较好,但Fib CV略大;Fib、D-D、FDP指标水平的判定标准均≤10%。结论 对子痫前期患者通过全自动凝血仪进行凝血七项检测,能够显著评估患者凝血功能状态,对于评估患者疾病严重程度具有关键作用,能够为临床治疗提供坚实依据,有利于后续治疗方案的制定。

STEAM教育理念下电场自动测绘仪的开发

将静电场教学实践中遇到的问题,作为课外拓展课题研究是新工科人才培养的有效方式之一。本文基于STEAM教育理念,采用项目式学习,以学生为主体,以跨学科融合和创新为导向,制定教学目标和教学方法。将物理理论和实验创新有机融合,引导学生结合单片机技术和Matlab程序,设计出新型可视化电场自动测绘仪。该仪器操作简便高效,测量精度高,还能直观展示电场的动态变化。而学以致用的过程,提高了学生的创新能力和知识综合运用能力,也为高校的教学改革提供了新思路。

基于虚拟仪器的集成运放自动测试教学辅助平台设计

为降低设备故障对模拟电子技术实验教学效率的影响,基于虚拟仪器技术设计了一种集成运放自动测试教学辅助平台。利用集成化虚拟仪器实验平台NI ELVIS II进行数据传输,设计了测试电路板卡;利用Lab-VIEW软件设计了仪器面板和平台软件部分。使用集成运放μA714芯片对平台进行了测试,并在模拟电子技术的实际教学中进行了效果验证。测试和实际使用结果表明,该平台可以准确检测出故障芯片,正确率>95%;相比于未使用本平台时,师生使用本平台进行实验的准确率提升超过20%,耗时降低超过20%。

以实际检测为导向的仪器分析实验教学实践

为了实现学在课堂用于课外的仪器分析训练目标,以实际检测为导向,设计了一个仪器分析实验项目——市售食盐中不同形态碘的含量测定。通过精密度和加标回收率实验,验证了自动电位滴定法的准确性和替代传统国标手动滴定法的可行性。教学实践结果表明,滴定实验现象明显,项目内容充实,检测报告可自动生成以供量值溯源,极大地激发了学生的学习兴趣。

全自动QuEChERS前处理仪结合气相色谱-四极杆-飞行时间质谱法测定橄榄油中222种农药残留

基于QuEChERS方法,建立了全自动QuEChERS前处理仪结合气相色谱-四极杆-飞行时间质谱法(GC-QTOF-MS)快速测定橄榄油中222种农药残留的分析方法,并考察了提取溶剂酸化程度、正己烷体积、振荡时间、离心温度、净化剂对222种农药残留测定的影响。首先选择响应较好且无明显干扰的离子用于定量及定性,再通过对全自动QuEChERS前处理仪的参数设置开发了净化流程,用含2%甲酸的乙腈溶液提取,上清液在含有400 mg N-丙基乙二胺(PSA)、400 mg十八烷基硅烷键合硅胶(C18)和1200 mg无水硫酸镁的离心管中净化离心,净化液经氮气吹干,用乙酸乙酯定容后供仪器分析,最后采用基质标准溶液进行定量。从基质效应、线性范围、检出限、定量限、精密度及正确度等方面对定量分析方法进行验证。结果表明:222种农药中86.04%的农药线性范围为0.02~2.00μg/mL,10.81%农药的线性范围为0.10~2.00μg/mL,3.15%农药的线性范围为0.20~2.00μg/mL,相关系数(R^(2))均大于0.99,222种农药在各自线性范围内线性关系良好;全部被测农药的检出限范围为0.002~0.050 mg/kg,定量限范围为0.007~0.167 mg/kg,其中有170种农药定量限可以达到0.007 mg/kg,21种农药定量限可以达到0.017 mg/kg,占总数量的86.04%;在0.2、0.5和0.8 mg/kg 3个添加水平下,平均回收率为70%~120%的农药占全部被测农药的79.58%,平均回收率为80%~110%的农药占全部被测农药的65.92%,相对标准偏差(RSD,n=6)<10%的农药占全部被测农药的93.54%,RSD(n=6)<20%的农药占全部被测农药的98.35%。应用该方法对14份市售橄榄油样品进行了检测,共检出7种农药,其含量范围为0.0044~0.0490 mg/kg。该方法操作简单、快速、灵敏度高,且自动化程度较强,前处理过程无需人员值守,减轻劳动力的同时减少了人员误差,能够满足橄榄油中多种农药残留检测的需求,也可以为其他油类农药残留检测及复杂基质的自动化前处理提供参考。

基于智能化控制的高效活细胞成像技术

为提升活细胞功能研究的效率与准确性,显微成像平台研发了1款智能化控制精准加样系统。自主研发的加样系统具备远程自动化控制功能,能实现精准的药物定时定点添加。经研究和测试,该系统展现出卓越的通用性,能与常见的光学成像设备搭载使用,并能满足从短期到长期活细胞功能研究的各种实验要求。在活细胞连续成像的过程中,采用智能化与精准化的控制方法,可显著提升实验的准确性、稳定性和效率,尤其是能确保关键数据的完整性。该研究工作有效促进了细胞功能等关键科研领域的深入探索,成功增强了多台光学成像仪器的测试能力和应用价值,同时也推动了创新人才的成长和高标准科研平台的搭建。

不同超声清洗时间对眼科显微器械清洗效果的影响

目的比较不同超声清洗时间对眼科显微器械的清洗效果,探索兼顾清洗质量和低损耗的超声清洗时间。方法选取使用后的眼科白内障包、玻璃体切除包各30个,两种器械包随机均分至A、B、C三组,每组眼科显微器械各180件。三组均采用超声波清洗机+全自动清洗机的清洗方式,超声清洗时间分别为20 s、40 s、60 s。通过目测法、ATP荧光检测和蛋白残留测定法对三组清洗后的器械进行清洗质量评价。结果目测法和ATP生物荧光检测三组的合格率差异无统计学意义(P>0.05);蛋白残留测定三组合格率差异有统计学意义(P<0.05),A组与B、C两组比较,差异有统计学意义(均P<0.0167)。结论超声清洗+全自动清洗机清洗是眼科显微器械的有效清洗方式,超声时间在40~60 s为宜。

化工企业电气仪表自动化控制技术的运用

电气仪表自动控制系统的发展,离不开信息技术的支持,它能够为化工企业的设备装置提供技术保障,还可以带动电气仪表自动化的发展。在现代化生产作业中,研究和开发自动化技术,能够促进工业发展。特别是通过智能化自动控制技术的应用,可进一步提升电气仪表的安全运行效果、增加企业的经济效益。

YOLOX目标检测模型用于自动识别数字减影血管造影图中的血管腔内介入器械

目的 观察YOLOX目标检测模型用于自动识别数字减影血管造影(DSA)图中的血管腔内介入器械的价值。方法 收集37例接受腹部血管腔内介入治疗患者的DSA资料,截取4 435幅图像作为数据集,并按照9∶1比例将其分为训练集(n=3 991)与验证集(n=444)。对数据集中的6种介入器械进行标记后,以YOLOX算法对训练集数据进行深度学习训练,构建YOLOX目标检测模型;基于验证集评估该模型自动识别DSA图中的介入器械的效能。结果共对4 435幅DSA图像设置6 668个标签,分别针对Terumo 0.035in泥鳅导丝(n=587)、Cook Lunderquist超硬导丝(n=990)、Optimed 5F带刻度猪尾导管(n=1 680)、Cordis MPA多功能导管(n=667)、Boston Scientific V-18可控导丝(n=1 330)及Terumo 6F长鞘(n=1 414);训练集分别含上述标签527、875、1 466、598、1 185及1 282个,验证集分别含60、115、214、69、145及132个。YOLOX目标检测模型自动识别验证集中上述器械的像素准确率分别为95.23%、97.32%、99.18%、98.97%、97.60%及98.19%,平均像素准确率达97.75%。结论 YOLOX目标检测模型能够自动识别DSA图中的多种血管腔内介入器械。

一种振弦式智能采集仪的可靠性及稳定性分析

针对目前振弦类数据广泛应用自动化采集方式,但自动化采集设备存在功能不全、使用不便且数据可靠性和稳定性差等问题。本文研发设计了一种振弦式智能采集仪,并利用振弦式智能采集仪与手动频率读数仪在不同场景下同时间进行数据采集测试,通过对比分析两种方式采集得到的数据结果的吻合情况,进一步分析振弦式智能采集仪工作的稳定性。结果表明,本文研发设计的振弦式智能采集仪功能全面且采集数据可靠且较为稳定,满足实际工程的需求。