基于嵌入式的电量计量采集系统研究

考虑到目前电量计量采集系统线路布置复杂,针对窃电行为的监测和判断能力弱,本文研究一种基于嵌入式的电量计量采集系统。嵌入式电量计量系统的构成有两部分：高压侧用电信息无线监测装置和低压侧用电信息远程监测装置。高压侧用电信息无线监测装置的工作原理为对高压侧的电路信息进行采集,之后通过发射模块将信息传递至远程监控单元,监测人员可通过监控中心直接对电路信息进行远距离实时读取。低压侧用电信息远程监测装置对各个用电用户的用电信息进行直接识别,而后将识别分析结果输送到监控主站的信息库中。实验结果表明：高压无线检测装置检测到的数据通过换算后得到的用户用电情况曲线却不能和低压侧无线检测装置得到的数据曲线重合,说明该装置能够检测到人为窃电操作,验证了本文研究的嵌入式电量计量采集系统能够实现窃电的精确识别。     

基于Mega128和WiFi的电气设备无线监控系统

为了解决人员流动监测设备运行状态的信息滞后问题,减少因此而带来的损失,提出了一种基于Mega128单片机和Wi Fi的电气设备无线监控系统。根据设备正常运行和非正常运行时的工作电流的不同,通过电流互感器检测其工作电流,进而判断其工作状态。最后Mega128将检测到的结果经Wi Fi模块传送至Internet服务器,并在监控界面上显示。经过实验,该系统能够对多个设备的使用情况进行监测,用户能通过监测网站网页读取设备的使用信息并长期保存。     

应用机器人轨迹跟踪技术的电力线路无人机智能化巡检系统设计

野外电力线路易发生损坏,且时变特性干扰较大,检测准确度较低,因此,设计应用机器人轨迹跟踪技术的电力线路无人机智能化巡检系统。该系统通过数据采集模块和飞行状态检测模块,分别进行电力线路图像数据获取与飞行状态监测,飞行控制模块接收图像与状态数据,并在轨迹跟踪控制子模块中使用自适应鲁棒滑模控制算法,实现无人机的轨迹跟踪,同时,该模块经无线数据传输模块将数据传输至地面站,在巡检数据智能分析管理模块中,地面站根据数据信息,完成电力线路故障识别,进而实现电力线路无人机智能化巡检。实验结果表明,该系统具有良好的轨迹跟踪效果,且巡检准确率较高,满足多种天气作业需求。     

输电线路无人机自动巡检系统不间断作业实时监控方法

针对输电线路无人机自动巡检信息冗杂,数据噪声较大,海量数据传输难以完整传输的问题,提出了一种输电线路无人机自动巡检系统不间断作业实时监控方法,保障输电线路不间断作业。构建输电线路不间断作业监控架构,利用无人机自动巡检系统的无人机飞行器实时采集输电线路图像信息,经无线传输模块传输至地面站存储;输电线路不间断作业监控模块调用采集到的数据,采用非局部均值滤波算法去噪处理输电线路图像,将去噪后图像输入至卷积神经网络,优化检测异常输电线路图像,并利用粗定位算法定位异常点,便于巡检人员实时修复输电线路,实时监控输电线路不间断作业。实验结果表明,所提方法能够清晰、直观地检测到输电线路异常点,实时监控输电线路不间断作业;拥有较为优秀的去噪效果,为后期高效、实时检测输电线路异常点提供保障;信息传输性能突出,保证海量数据传输具有极高的完整性。     

基于Webdecoy的攻击行为特征提取研究

为更好地解决Web应用的安全问题,提出了基于Webdecoy的攻击行为特征提取模型.以具体的业务系统为基础,通过嵌入监控代码跟踪对业务系统的访问并获取探测攻击信息,并对获取信息进行归一化处理和属性划分,根据属性的动态比较得到攻击请求的相似性结构.最后对探测行为进行检测评估,对恶意行为给出报警,并通过实验结果验证了该模型的有效性.     

煤矿智能瓦斯巡检管理系统的研制

为保证瓦斯监测数据的准确性、及时性,实现瓦斯安全预警,研制了一套煤矿智能瓦斯巡检管理系统。该系统采用无线技术及传感器技术,可实时监测、显示及语音提示瓦斯浓度、时间、电池电压等信息,并可将巡检信息上传到计算机,经系统配套软件分析处理后形成巡检路线或瓦斯预测曲线等供煤矿安全监控管理人员分析使用。工业性试验结果表明,该系统运行可靠,故障率极低。     

基于机器学习的恶意程序检测系统的研究与设计

本文研究了基于机器学习的恶意程序检测方法，并设计了基于机器学习的恶意程序检测系统。该系统不仅能对于已知程序的安全性进行分析，也能够根据未知程序的行为进行分析检测，判定是否为恶意程序，并使用机器学习技术将程序分类，提高了检测结果的准确率。在对程序安全性的评估中，采用了“模糊层次分析”风险评估法，计算出各类程序行为发生的概率，并根据携带信息、反追踪和反取证3类行为特征中14项参数对程序的安全性进行打分，通过评估打分，能够检测出程序的恶意程度。     

基于RFID手持终端的煤矿安全巡检系统的设计

针对传统的煤矿安全巡检方法采用人工巡检方式存在的问题,提出了一种基于RFID手持终端的煤矿安全巡检系统的设计方案。该方案中,巡检人员使用手持终端读自己的身份识别卡登录,然后通过安全管理服务器下载当班巡检任务和安全隐患库;巡检人员下井,按照下载的巡检任务依次到巡检地点刷地址识别卡,然后根据要求检测气体浓度,排查隐患,并进行相关记录;巡检结束,巡检人员通过安全管理服务器上传巡检的数据结果;安全管理人员对上传的数据进行统计和汇总,从而及时发现隐患,同时根据记录的时间判断巡检人员的脱班漏岗情况。实际应用表明,该系统能够有效地推进煤矿安全巡检工作的规范化和信息化,提升煤矿企业的安全管理水平。     

基于改进双流法的井下配电室巡检行为识别

井下配电室监控视频持续时间较长且行为类型复杂,传统双流卷积神经网络(CNN)法对此类行为识别效果较差.针对该问题,对双流CNN法进行改进,提出了一种基于改进双流法的井下配电室巡检行为识别方法.通过场景分析,将巡检行为分为站立检测、下蹲检测、走动、站立记录、坐下记录5种类型,并制作了巡检行为数据集IBDS5.将每个巡检行为视频等分为3个部分,分别对应巡检开始、巡检中和巡检结束;对3个部分视频分别随机采样,获取代表空间特征的RGB图像和代表运动特征的连续光流图像,并分别输入空间流网络和时间流网络进行特征提取;对2个网络的预测特征进行加权融合,获取巡检行为识别结果.实验结果表明,以Res Net152网络结构为基础,且权重比例为1∶2的空间流和时间流双流融合网络具有较高的识别准确度,Top-1准确度达到98.92%;本文方法在IBDS5数据集和公共数据集UCF101上的识别准确率均优于3D-CNN、传统双流CNN等现有方法.     

嵌入式视频监控系统中的运动目标检测

在设计实现的基于嵌入式Web的远程视频监控系统上,引入了运动目标检测,将帧间运动信息和帧间边缘信息相融合,提出了一种运动目标检测的新算法,能够对监控范围内人员的非法入侵或非法移动进行侦测和识别,根据识别结果,发出相应的警报,从而实现了监控系统的智能化.实验结果表明,这种检测方法算法简单、运算量小,适合于实时应用.     

A method of evaluating inspector's performance differences and job requirements

Large individual differences are among the most consistent findings in the study of industrial inspection. From a statistical point of view, a large proportion of the variation in inspection performance is attributed to this individual factor. Based on the conclusions obtained from the review of previous papers, the relations between subjects' cognitive factors and inspection performance were shown to be in need of further exploration. The objective of this paper is to introduce a method that can explore this large proportion of variation by concentrating on individuals' cognitive attributes and how each contributes to the efficiency and effectiveness of inspection performance. In an experiment, three inspection tasks and 11 cognitive pretests were included. Through factor analysis and Pearson correlations, some significant predictive relationships were found. The findings can be applied to set up selection criteria as well as training schemes for industrial inspectors.     

The performance of the N-fold requirement inspection method

Faults in system requirements can be very harmful. It is therefore often required that the inspection achieves a high fault detection ratio (FDR). To achieve this, a large number of inspectors is required. Large teams are known to be inefficient. Therefore, the N-fold requirements inspection method divides the inspectors intoN small efficient teams. All temas inspect the same requirements document. Experiments with both information and real-time systems demonstrate that the different teams detect different faults such that they achieve together a higher FDR value. The analysis suggests that the FDR is primarily a function of the level of expertise of the inspectors and of the number of teams. A quite simple probabilistic model that matches the experimental results enables the prediction of the FDR as a function of these two parameters. A diagram based on the model enables a fast estimation of the FDR and of the most effective number of inspections teams money-wise. The model may also be employed for measuring the efficiency of requirement inspection methods.     

基于深度可分离卷积的地铁隧道巡检视频分析

地铁隧道安全目前主要依靠地铁轨道巡检员在轨道无车时人工巡轨检查,这种方法速度慢、工作效率低,而且巡检效果完全依赖于轨道巡检员的经验和状态。针对这一问题,提出了一种基于深度可分离卷积的地铁隧道巡检视频异常报警系统,该系统使用提出的SubwayNet卷积神经网络完成对巡检视频图像的分类。利用制作的地铁隧道巡检数据集对构建的卷积神经网络进行训练并保存模型,制作了图形用户界面并加入声音报警的功能,最后将程序文件打包为可执行文件。实验结果表明,该系统的分类准确率能够达到96%,速度能够达到52 fps,满足对视频实时、准确分析的要求。     

基于综合监控的设备状态修方案研究

随着工业控制领域的不断发展,综合监控系统已经日趋成熟并于工业现场运行较长时间。而基于综合监控系统获取的大量历史数据的分析和实时数据的使用并没有开展深入的探讨。本方案提出了一种基于综合监控系统的状态修方案,把综合监控系统的历史数据经过一定的清洗,建模导入到大数据平台,通过相应的算法分析,从而改善维修决策模型并建立设备评价体系;把实时数据实时的传递到设备状态页面,减轻了传统巡检工作,保证了设备检查效果;把设备报警数据通过分类,分项,直接派生检修工单,实现了设备维修的自动化。     

Perspective-based Usability Inspection: An Empirical Validation of Efficacy

Inspection is a fundamental means of achieving software usability. Past research showed that the current usability inspection techniques were rather ineffective. We developed perspective-based usability inspection, which divides the large variety of usability issues along different perspectives and focuses each inspection session on one perspective. We conducted a controlled experiment to study its effectiveness, using a post-test only control group experimental design, with 24 professionals as subjects. The control group used heuristic evaluation, which is the most popular technique for usability inspection. The experimental design and the results are presented, which show that inspectors applying perspective-based inspection not only found more usability problems related to their assigned perspectives, but also found more overall problems. Perspective-based inspection was shown to be more effective for the aggregated results of multiple inspectors, finding about 30% more usability problems for 3 inspectors. A management implication of this study is that assigning inspectors more specific responsibilities leads to higher performance. Internal and external threats to validity are discussed to help better interpret the results and to guide future empirical studies.     

Evaluation of best system performance: Human,automated, and hybrid inspection systems

Recently, 100% inspection with automated systems has seen more frequent application than traditional sampling inspection with human inspectors. Nevertheless, humans still outperform machines in most attribute inspection tasks. Because neither humans nor automation can achieve superior inspection system performance, hybrid inspection systems where humans work cooperatively with machines merit study. In response to this situation, this research was conducted to evaluate three of the following different inspection systems: (1) a human inspection system, (2) a computer search/human decision‐making inspection system, and (3) a human/computer share search/decision‐making inspection system. Results from this study showed that the human/computer share search/decision‐making system achieve the best system performance, suggesting that both should be used in the inspection tasks rather than either alone. Furthermore, this study looked at the interaction between human inspectors and computers, specifically the effect of system response bias on inspection quality performance. These results revealed that the risky system was the best in terms of accuracy measures. Although this study demonstrated how recent advances in computer technology have modified previously prescribed notions about function allocation alternatives in a hybrid inspection environment, the adaptability of humans was again demonstrated, indicating that they will continue to play a vital role in future hybrid systems. © 2003 Wiley Periodicals, Inc. Hum Factors Man 13: 137–152, 2003.     

Visual lobe shape characteristics of experienced industrial inspectors and inexperienced subjects

This article reports research on visual lobe shape differences between experienced industrial inspectors and inexperienced students and the effects of years of inspection experience on lobe‐shape characteristics. Comparison of the visual lobes of students and inspectors showed that lobe roundness of the inspectors was higher than that of the students. Also, marked improvement in lobe roundness and regularity for inspectors was evident in those inspectors who had relatively long experience in inspection work, indicating that daily inspection practice did not seem to be an effective way of improving lobe‐shape characteristics. The increased lobe roundness level did not change, however, even when the inspectors had not performed an inspection job for a long period of time. This finding suggests that the improved lobe‐roundness level could be maintained even without any follow‐up inspection practice. It seems that intensive lobe training rather than inspection practice may be required to improve lobe‐shape characteristics in a short time. No relationship was found between lobe‐shape parameters and the ranked inspection performance of the inspectors, which indicated that, for the inspectors, better search performance may be related more to their better decision making rather than to their higher lobe‐roundness level or inspection speed. © 2010 Wiley Periodicals, Inc.     

Selection tests for visual inspection on a multiple fault type task

Although individual differences between inspectors is the most significant factor in differences in inspection performance there are no suitable selection tests. The task was analysed to indicate the required mental characteristics and from this a battery often selection tests was devised. These are used with a simulated task developed on a computer plotter to include the search and decision components of inspection. Presentation was by sets of slides which contained 2, 4 or 6 fault types and slides were classified as fault-free, acceptable fault, or reject. Subjects were 48 students and 18 industrial inspectors. Results were analysed by multivariate analysis of covariance and showed no difference between the student and industrial subjects. The best predictor was a simplified version of the task. Very good predictive ability was obtained with the Embedded Figures Test, and other good predictors were lobe size and mental imagery. If these tests were not used good predictive ability was obtained with a subset of the WAIS test. Eysenck's test of extroversion, and Gordon's test of Mental Imagery Control.     

The Impact of Educational Background on the Effectiveness of Requirements Inspections: An Empirical Study

While the inspection of various software artifacts increases the quality of the end product, the effectiveness of an inspection depends largely on the individual inspectors involved. To address that issue, a large-scale controlled inspection experiment with over 70 professionals was conducted at Microsoft Corporation that focused on the relationship between an inspector's background and their effectiveness during a requirements inspection. The results of the study showed that inspectors with university degrees in majors not related to computer science found significantly more defects than those with degrees in computer science majors. We also observed that level of education (Masters, PhD), prior industrial experience or other job related experiences did not significantly impact the effectiveness of an inspector. The only other type of experience that had a significant impact on effectiveness was experience in writing requirements, i.e. professionals with prior experience writing requirements found statistically significant more defects than their counterparts.     

An application of texture analysis to materials inspection

A large set of texture features were measured for a collection of samples of an industrial material which had been graded in quality by inspectors. Features were identified, based on gray-level co-occurrence statistics, that had a high correlation with the grades. Such features could be used for on-line inspection of the material.