Mechanical Properties of Remote-Laser Cut CFRP and Thermographic Laser-Process Monitoring

Remote-laser beam cutting is a productive technology without tool wear. Especially when cutting carbon fiber reinforced polymers (CFRP), it offers constant manufacturing quality. Since it is a thermal process, a heat-affected zone (HAZ) is formed at the edge of the cut. Based on quasi-static and cyclic mechanical tests on open-hole specimens, the influence of the process on the mechanical properties of CFRP is shown. The quasi-static tests are in good correlation with results from other researchers by indicating an increase in the maximum tensile stress of the test specimens, cut by remote-laser. The reason is the rearrangement of the shear stresses and a reduction of the notch stress concentration. However, the results of the present study show that excessive expansion of the HAZ leads to a reduction in the maximum tensile stress compared to milled test specimens. Under cyclic load conditions, remote-laser beam cutting does not lead to a more pronounced degradation than milling. The mechanical properties of the notched test pieces are sensitive to the expansion of the HAZ. For the production of components it is therefore necessary that the remote-laser beam cutting is carried out under controlled and documentable conditions. For this purpose, process thermography was tested as a tool for quality assurance. The results show that the technology is basically suitable for this task.

Recent Progress of Commercially Available Biosensors in China and Their Applications in Fermentation Processes

Biosensors, which are the products of the biotechnology industry, are among the key projects of the 7th, 8th, and 9th Fiveyear Plans of China Science ＆ Technology Developing Programs, respectively, and they play an important role in developing and reforming traditional biotechnology. SBA series biosensor analyzer, as the only one commercial biosensor in China, has attracted lots of attention in the process of information gathering and measurement for biological industry with the development of technology and society. In this paper, we presented an overview of the most important contributions dealing with the monitoring of the biochemical analytes in fermentation processes using SBA series biosensor analyzers in China. Future trends of the biosensor analyzer in China were also mentioned in the last section.

An Improved Adaptive Multi-way Principal Component Analysis for Monitoring Streptomycin Fermentation Process

Multi-way principal component analysis (MPCA) had been successfully applied to monitoring the batch and semi-batch process in most chemical industry. An improved MPCA approach, step-by-step adaptive MPCA (SAMPCA), using the process variable trajectories to monitoring the batch process is presented in this paper. It does not need to estimate or fill in the unknown part of the process variable trajectory deviation from the current time until the end. The approach is based on a MPCA method that processes the data in a sequential and adaptive manner. The adaptive rate is easily controlled through a forgetting factor that controls the weight of past data in a summation. This algorithm is used to evaluate the industrial streptomycin fermentation process data and is compared with the traditional MPCA. The results show that the method is more advantageous than MPCA, especially when monitoring multi-stage batch process where the latent vector structure can change at several points during the batch.

Monitoring and Fault Diagnosis for Batch Process Based on Feature Extract in Fisher Subspace

Multivariate statistical process control methods have been widely used in biochemical industries. Batch process is usually monitored by the method of multi-way principal component analysis (MPCA). In this article, a new batch process monitoring and fault diagnosis method based on feature extract in Fisher subspace is proposed.The feature vector and the feature direction are extracted by projecting the high-dimension process data onto the low-dimension Fisher space. The similarity of feature vector between the current and the reference batch is calculated for on-line process monitoring and the contribution plot of weights in feature direction is calculated for fault diagnosis. The approach overcomes the need for estimating or tilling in the unknown portion of the process variables trajectories from the current time to the end of the batch. Simulation results on the benchmark model of penicillin fermentation process can demonstrate that in comparison to the MPCA method, the proposed method is more accurate and efficient for process monitoring and fault diagnosis.

A Robust Statistical Batch Process Monitoring Framework and Its Application

In order to reduce the variations of the product quality in batch processes, multivariate statistical process control methods according to multi-way principal component analysis (MPCA) or multi-way projection to latent structure (MPLS) were proposed for on-line batch process monitoring. However, they are based on the decomposition of relative covariance matrix and strongly affected by outlying observations. In this paper, in view of an efficient projection pursuit algorithm, a robust statistical batch process monitoring (RSBPM) framework,which is resistant to outliers, is proposed to reduce the high demand for modeling data. The construction of robust normal operating condition model and robust control limits are discussed in detail. It is evaluated on monitoring an industrial streptomycin fermentation process and compared with the conventional MPCA. The results show that the RSBPM framework is resistant to possible outliers and the robustness is confirmed.

Monitoring and Fault Diagnosis for Batch Process Based on Feature Extract in Fisher Subspace

Multivariate statistical process control methods have been widely used in biochemical industries. Batch process is usually monitored by the method of multi-way principal component analysis (MPCA). In this article, a new batch process monitoring and fault diagnosis method based on feature extract in Fisher subspace is proposed. The feature vector and the feature direction are extracted by projecting the high-dimension process data onto the low-dimension Fisher space. The similarity of feature vector between the current and the reference batch is calcu- lated for on-line process monitoring and the contribution plot of weights in feature direction is calculated for fault diagnosis. The approach overcomes the need for estimating or filling in the unknown portion of the process vari- ables trajectories from the current time to the end of the batch. Simulation results on the benchmark model of peni- cillin fermentation process can demonstrate that in comparison to the MPCA method, the proposed method is more accurate and efficient for process monitoring and fault diagnosis.

基于Profibus的雨水监测系统设计

本文给出了基于PLC和Profibus总线结构的雨水监测系统架构及实现方案。该系统可实现对城市雨水及污水排放的监控,具有扩展性好、易于维护的优点。

基于ArcGIS Geoprocessing的干旱遥感监测系统研究与设计

ArcGIS Geoprocessing除了提供常见的GIS空间分析功能外,还支持建立复杂的地理处理模型来完成定制的地理处理任务.根据现有的干旱遥感监测模型,采用ArcGIS Geoprocessing技术实现干旱遥感监测模型的建模处理.并以重庆市2006年干旱数据为例进行处理,所得结果和同期干旱状况吻合.使用插件式GIS二次开发技术基于ArcGIS Geoprocessing实现了干旱遥感监测系统.与传统手工分布处理相比,在模型选取、数据转换、数据处理、产品制作等方面,自动化程度得到了极大的改进和提高.系统主要功能为:通过对遥感影像数据的干旱模型自动化处理,快速获取干旱结果空间分布,并生成相关产品为决策部门提供决策依据.

Railway Transport Infrastructure Monitoring by UAVs and Satellites

Improving the rail transport security requires development and implementation of neoteric monitoring and control facilities in conditions of increasing speed and intensity of the train movement and high level of terrorist threat. Use of Earth remote sensing (ERS), permitting to obtain information from large areas with a sufficiently high resolution, can provide significant assistance in solving the mentioned problems. This paper discusses the possibility of using various means of remote sensing such as satellites and unmanned aerial vehicles (UAV), also known as drones, for receiving information in different ranges of the electromagnetic spectrum. The paper states that joint using of both these means gives new possibilities in improving railroad security.

Patient Centered Real-Time Mobile Health Monitoring System

In this paper, we introduce a system architecture for a patient centered mobile health monitoring (PCMHM) system that deploys different sensors to determine patients’ activities, medical conditions, and the cause of an emergency event. This system combines and analyzes sensor data to produce the patients’ detailed health information in real-time. A central computational node with data analyzing capability is used for sensor data integration and analysis. In addition to medical sensors, surrounding environmental sensors are also utilized to enhance the interpretation of the data and to improve medical diagnosis. The PCMHM system has the ability to provide on-demand health information of patients via the Internet, track real-time daily activities and patients’ health condition. This system also includes the capability for assessing patients’ posture and fall detection.

空地一体遥感技术在轨道交通安全保护区巡查中的应用

随着城市轨道交通建设的不断发展,轨道交通沿线安全保护区巡查工作的范围越来越大,内容越来越多,区域内的情况越来越复杂。针对存在的问题,本文构建了一套空地一体的遥感综合监测体系,在巡查工作中引入航空摄影测量、低空无人机监测、车载全景扫描、定点实时监控等多种遥感监测技术及DSM差分计算、深度学习智能识别等多种数据处理技术,并以上海为例开展应用实践。结果表明,本文方法具有可行性,对建立全覆盖、高频次、智能化的巡查模式有参考借鉴价值。

转鼓式固态生物反应器的研究进展

固态发酵是指微生物在含水量极低的固体物料上进行生长、代谢,以获得初生代谢产物和次生代谢产物。固态反应器因其各种工艺参数的在线监测与自动控制,在食品发酵、生物制药、饲料生产等领域有着越来越广泛的用途。根据罐温、溶氧、pH等工艺参数而采用不同的控制模式。在固态发酵过程中,由于微生物生长环境、物料、传质等诸多因素的差异,设计反应器并实现智能化、程序化是有待解决的关键性共同问题。主要对转鼓式生物固态反应器的应用、特征进行分析并对一些目前存在的弊端提出疑问。

钢丝绳远程监测系统的设计与实现

针对现有的工业钢丝绳损伤监测系统的局限性,设计并实现了一款基于LabVIEW、Flask和Vue.js的钢丝绳远程智慧监测系统。该系统兼具传感器数据采集、信号处理、可视化展示、远程检测、数据分析等多项功能,以满足钢丝绳检测的全面需求。系统使用LabVIEW进行传感器数据采集和实时处理,Flask用于构建后端服务器以及数据处理,Vue.js负责前端的可视化展示和用户界面,使工程师和操作人员能够远程监测钢丝绳状态并及时作出反应。试验结果表明,采用的综合性系统设计不仅提升了工业生产中钢丝绳的质量控制水平,也大幅提高了远程监测能力,为工程人员提供了全方位的实时监测和管理工具。

Mass data processing of time series Landsat imagery:pixels to data products for forest monitoring

Free and open access to the Landsat archive has enabled the implementation of national and global terrestrial monitoring projects.Herein,we summarize a project characterizing the change history of Canada’s forested ecosystems with a time series of data representing 1984-2012.Using the Composite2Change approach,we applied spectral trend analysis to annual best-available-pixel(BAP)surface reflectance image composites produced from Landsat TM and ETM+imagery.A total of 73,544 images were used to produce 29 annual image composites,generating∼400 TB of interim data products and resulting in∼25 TB of annual gap-free reflectance composites and change products.On average,10%of pixels in the annual BAP composites were missing data,with 86%of pixels having data gaps in two consecutive years or fewer.Change detection overall accuracy was 89%.Change attribution overall accuracy was 92%,with higher accuracy for standreplacing wildfire and harvest.Changes were assigned to the correct year with an accuracy of 89%.Outcomes of this project provide baseline information and nationally consistent data source to quantify and characterize changes in forested ecosystems.The methods applied and lessons learned build confidence in the products generated and empower others to develop or refine similar satellite-based monitoring projects.

遥感测绘技术在环境监测和灾害预警中的应用现状研究

遥感测绘技术作为一种强大的数据收集和分析工具,在环境监测和灾害预警方面具有极强的重要性.随着技术的快速发展,遥感已经成为了获取广泛、高分辨率环境数据的关键手段.本研究的目的在于全面评估遥感技术在环境和灾害管理领域的应用,包括其在森林保护、水资源监测、大气污染评估以及气候变化研究中的重要作用,本研究还特别关注遥感在灾害预警中的应用,如洪水和地震预警,并讨论这些应用在全球气候变化背景下的日益重要性.此外,还探讨了遥感数据的获取、处理和分析方法及在技术实施过程中遇到的挑战和限制.

自动控制系统中的智能化技术运用

阐述智能化技术的特点,电气自动控制技术中智能化技术应用,包括生产系统中的操作流程、故障处理、控制模型、远程监控设备运转状况,分析PLC技术、神经网络体系的应用。

基于网络的磁力仪台站远程实时监测方法

磁法勘探中,磁力仪台站仪器采集地磁静日变化数据用于探区的地磁场数据的日变改正。为避开电磁干扰,磁力台站通常设置在偏远位置,很难实时监测仪器状况和数据质量,一旦出现问题会导致所有流动站的数据无法进行日变改正而作废。针对此问题,本文提出一种基于移动网络的远程实时监测磁力台站工作状况的方案,具有实时回传台站数据和状态异常警报功能,能够实时进行台站远程监测,解决了台站监测离不开人的难题。

遥感数据分析的矿山边坡变形监测方法

为实现对矿山边坡的实时监测,通过结合无人机数字低空遥感测量技术,建立矿山三维坐标体系并设定测站点中心,对矿山边坡累计变形量与变形速率进行实时监测。实验结果表明:设计的监测方法具有良好应用效果,使矿山边坡变形监测结果的误差得到较好控制,实现对其异常状态与变形的及时感知与快速处理。

基于地理模型和多源遥感的林草生态综合监测方法——以日照市莒县为例

随着生态系统保护工作的不断推进,林草生态系统成为人们关注的重点问题。分析林草生态监测现状可确定目前林草生态监测存在的问题。针对当前林草生态综合监测过程,由于遥感图像分析能力不足,造成监测结果精度不足等问题,提出基于地理模型和多源遥感的林草生态综合监测方法。采集遥感图像,完成3D标定及预处理工作。通过纹理特征提取与支持向量机算法,对林草生态环境遥感影像进行判读。应用多源遥感技术构建地理加权回归模型,实现林草地图斑监测。将图斑带入马尔科夫矩阵模型中,获取林草生态综合变化监测结果。至此,基于地理模型和多源遥感的林草生态综合监测方法设计完成。通过实验证实,此方法的遥感图像分类精度以及监测精度均优于当前方法。

浅谈2023年长春市城市国土空间监测项目实施

随着城市快速发展,全面掌握城市自然资源和人文地理要素情况势在必行,这将为建立健全城市国土空间规划、城市体检、用途管制等国土空间治理工作提供基础的数据支撑。本文以2023年长春市城市国土空间监测为例,从专题资料收集与处理、遥感影像生产、空间监测数据库制作三个主要方面阐述项目实施情况,以及由此得到的几点体会。