基于PCA的故障传感器重构的理论研究

本文基于PCA(Principal component analysis)理论对故障传感器进行重构.首先将数据分别投影于主元子空间和残差子空间,然后定义故障的方向向量;因为过程变量间具有的强相关性,则沿故障各自的方向可对故障变量进行重构.     

基于改进核主元分析的TE过程故障诊断

对于复杂非线性化工过程,传统的核主元分析(KPCA)方法在故障检测方面明显优越于普通的PCA方法,但存在故障辨识效果差的问题,而且实际得到的数据不可避免地带有噪声、随机干扰。针对此,提出一种改进的核主元分析方法,对数据进行小波去噪预处理,利用核主元分析方法进行故障检测,并利用计算核函数的偏导方法求取KPCA监控中每个原始变量对统计量T2和SPE的贡献率,根据每个变量对监控统计量贡献程度的不同,可以辨识出故障源。把上述方法应用到TE(Tennessee Eastman)化工过程,仿真结果表明该方法不仅能够去噪、抗干扰和准确检测故障,而且能够有效辨识故障。     

基于主元分析的锅炉系统故障检测与诊断

针对锅炉系统的故障检测与诊断问题,介绍了基于主元分析的故障检测与诊断方法,给出了在多变量统计过程中应用广泛的T~2和SPE(Q)统计量。采集锅炉正常工况下的历史数据建立PCA主元模型,利用所建立的模型检测锅炉运行的实时数据,采用贡献图法对检测到的故障数据进行诊断分析,识别出故障原因,从而实现锅炉系统故障检测与诊断的目的。     

事件驱动的多模型MPCA统计监视方法及其应用

过程的安全性和产品的一致性是工业界共同关注的研究课题.如果对整个间歇过程只用一个线性化模型来处理,不仅会使主元个数大大增加,而且有许多故障无法检测到.结合间歇产生过程对象特点,将整个操作周期划分成多个子过程,分别建立多个子过程MPCA模型.在监视过程中,采用事件驱动方式在多模型之间切换,然后比较子模型的SPE等统计量和统计控制线的大小,判断过程状态是否处于异常.根据贡献图识别故障发生的原因,定位故障源.将所提出的建模和监视策略应用到锦西化工集团聚氯乙烯间歇生产,该方法能够快速有效地监视PVC生产过程中每一阶段性能的变化,及时准确地识别故障和诊断故障发生的原因,同时模型内存空间占用少,计算量小.     

高速列车双通道速度传感器故障检测与隔离研究

高速列车双通道速度传感器在随列车高速运行时受粉尘、振动、温度变化等因素影响,易出现车轴故障检测虚漏警或误诊等问题。现阶段工程中常利用测试对比等方法检测速度传感器状态,但无法及时监测且易产生虚报警。因此,利用改进主元分析法(PCA)和改进重构贡献图法(IRBCP)建立全新的速度传感器故障检测隔离系统。首先,利用可检测故障幅值选择合适的故障检测统计量并细化,再利用基于组合最大化思想的改进重构贡献图法,确保单故障、多故障均可隔离。以高速列车双通道速度传感器为例,实验验证了所提的策略能够满足常见速度传感器故障的检测隔离需求,准确有效。     

质量相关的回转窑故障诊断

针对水泥烧制过程工艺复杂,各变量数据之间存在强耦合关系的特点,提出了偏最小二乘(partial least squares,PLS)算法结合贡献图分析的方法,应用到回转窑系统中进行故障诊断。该文选取质量变量,建立过程变量和质量变量之间的回归关系,构建PLS模型实现通过过程变量数据对质量变量数据的预测。设置一定置信度的控制限,对超过控制限的故障进行报警。通过相对贡献图方法找出对故障贡献最大的变量,分析故障原因。仿真结果表明,该方法可以及时检测到影响水泥品质的故障并确定故障原因。     

基于子空间混合相似度的过程监测与故障诊断

针对现代工业过程多变量、过程数据通常同时包含高斯性和非高斯性分布的特点,提出了一种基于混合子空间的系统性能监控与故障诊断方法.首先使用小波去噪、PCA和ICA方法来进行过程检测,然后将基于PCA特征子空间距离相似度和基于ICA子空间余弦相似度的方法结合,建立故障诊断库,计算混合相似度,确定各类故障的诊断阈值.最后对在线的数据进行监控,判断过程是否正常.当有故障发生时,利用混合子空间相似度确定故障类型.该方法可以充分利用过程数据中的高斯和非高斯信息.通过对Tennessee Eastman(TE)过程的仿真研究,验证了该方法的可行性与有效性,与变量贡献图方法相比可以更加有效地监测出故障原因.     

基于MAF-ICA的工业过程故障诊断

针对复杂工业数据存在自相关的特点,提出一种基于最小/最大自相关因子分析(MAF)结合独立元分析(ICA)的故障诊断方法。首先利用自相关因子分析得到监测量的最大自相关矩阵,该矩阵包含数据信息的空间特征,并且去除了噪声;然后对其进行独立元分析,根据高阶统计信息,提取出独立元;并依据I2和SPE统计量值来判断系统的工作状态;最后采用变量贡献图对故障进行定位。将该方法应用到TE过程,验证了其可行性以及与ICA和MAF相比时的优越性。     

基于神经网络和高阶统计量的滚动轴承故障分类

提出一种基于高阶统计量特征和BP神经网络相结合的滚动轴承故障分类方法。以滚动轴承的高阶统计量(双谱、三阶累积量)以及一些常见的无量纲指标作为轴承故障特征输入,以BP神经网络作为分类器,成功地对滚动轴承4种不同的故障进行了分类。对比RBF神经网络,尽管BP神经网络的训练速度不快,但分类效果良好。研究表明,高阶统计量和BP神经网络相结合的滚动轴承分类方法是有效的。     

基于重构贡献和灰关联熵的变压器诊断方法

提出了一种基于重构贡献和灰关联熵相结合的变压器故障诊断新方法.该方法在利用油中溶解气体分析数据建立主元模型后,基于故障重构的思想,计算样本各变量重构贡献率作为特征量,规格化处理来提取变压器油中溶解气体的故障特征信息.为了克服单一灰关联分析中易造成局部关联及信息损失等缺陷,采用灰关联熵方法进行变压器故障类型诊断.实例研究结果表明,该方法具有良好的故障识别能力,提高了故障诊断的准确性.     

飞行时间质谱仪射频四极杆驱动器的研制

针对自制垂直引入式飞行时间质谱仪（orthogonal extraction time-of-flight mass spectrometer, O-TOFMS）的需要,运用直接数字频率合成 (direct digital frequency synthesis,DDS)技术,研制了射频四极杆的高压射频驱动电路装置。该驱动器频率可调范围为0.5~2 MHz,幅度最高达到1 000 Vp-p。该射频四极杆驱动器（radio frequency quadrupole driver,RFQ Driver）可用于分子离子反应器（molecule ion reactor,MIR）和RFQ驱动,其结构简洁、成本低、性能稳定可靠。     

Rapid one-of-a-kind production

To shorten the product development cycle time and reduce the cost at the same time, which is very critical for the survival of those small and mid-sized one-of-a-kind production (SMOKP) companies, various computer communication, simulation and computer aided engineering and management techniques have been widely used in these SMOKP companies. However, according to our study, the applications of these advanced computer technologies in these SMOKP companies are lack of system integration and synergy, which result in communication errors, reworks, duplications and hence a longer product development lead time and a higher cost. To solve this problem, an inter/intranet based computer aided rapid product development system is presented in this paper. This system consists of a number of inter/intranet based computer models or sub-systems for supporting rapid development of a one-of-a-kind product. It also employs a novel concurrent product development strategy called “prototype based incremental product development strategy” and an integrated product data structure called “product production structure”. Some industrial implementations of the proposed system, product development strategy and product data structure are also reported in the paper.     

Rapid one-of-a-kind production

To shorten the product development cycle time and reduce the cost at the same time, which is very critical for the survival of those small and mid-sized one-of-a-kind production (SMOKP) companies, various computer communication, simulation and computer aided engineering and management techniques have been widely used in these SMOKP companies. However, according to our study, the applications of these advanced computer technologies in these SMOKP companies are lack of system integration and synergy, which result in communication errors, reworks, duplications and hence a longer product development lead time and a higher cost. To solve this problem, an inter/intranet based computer aided rapid product development system is presented in this paper. This system consists of a number of inter/intranet based computer models or subsystems for supporting rapid development of a one-of-a-kind product. It also employs a novel concurrent product development strategy called “prototype based incremental product development strategy” and an integrated product data structure called “product production structure”. Some industrial implementations of the proposed system, product development strategy and product data structure are also reported in the paper.     

从光电容积图中提取脉搏率、呼吸率和心率的新方法

光电容积描记图(PPG)是一种利用光学技术无创检测人体心血管脉搏波的方法。PPG信号来源于MIMIC数据库,它含有许多生理信息。本文提出了将集合经验模态分解(EEMD)、倒谱、快速傅里叶变化和过零点检测相结合的方法,从PPG中可靠地估算脉搏率(PR)、心率(HR)和呼吸频率(RR)。首先,将PPG信号通过EEMD分解为有限个固有模态函数(IMF)。因为EEMD有自适应滤波特性,所以估算不同的生理参数时,可以用不同的IMF分量来重构信号。其次,估算脉搏率时,舍去低频含有伪迹的IMF,再通过过零点检测可以得到瞬时脉搏率。然后,估算心率时,用1 Hz~1.67 Hz(60次/分钟~100次/分钟)的IMF来重构信号,再求倒谱,选取反映心脏活动的频带来得到心率。最后,估算呼吸率时,用0.05 Hz~0.75 Hz(3次/分钟~45次/分钟)的IMF来重构信号,然后对呼吸信号求快速傅里叶变化得到频谱图,寻找频谱图中的峰值得到呼吸率。对来自MIMIC数据库的53个成人PPG信号进行了仿真。仿真结果表明使用该综合信号处理方法提取的生理参数与实际生理参数一致,且该方法有运算量小,精确度高的优点(误差不超过1.17%)。     

简介虚拟制造中的网络虚拟现实技术

介绍了网络虚拟现实建模语言（VRML），VRML具有动态对象描述和超链接、通用性、扩展性、易实现性等特点。VRML浏览器和生成VRML文件的工具广泛使用于多种平台的计算机，是虚拟制造VM与虚拟设计中的网络虚拟现实技术的基础。     

UPLC-MS/MS测定二苯甲烷二异氰酸酯

建立了二苯甲烷二异氰酸酯（MDI）的超高效液相色谱-串联质谱（UPLC-MS/MS）联用的分析方法。实验用甲醇作衍生试剂,将二苯甲烷二异氰酸酯衍生成二苯甲烷二氨基甲酸甲酯（MDC）,通过测定二苯甲烷二氨基甲酸甲酯来确定二苯甲烷二异氰酸酯的含量。实验采用Waters Acquity BEH C18超高效液相色谱柱,甲醇-0.1%甲酸作为梯度洗脱液,二苯甲烷二氨基甲酸甲酯在1.5 min内与其他化合物进行完全分离,经四极杆质谱选择离子监测模式检测。线性范围为2~100 μg/L,检出限为1 μg/L,相关系数0.999 4。考察了水、甲酸、甲酸铵流动相体系,以及进样量大小对样品的分离效果,发现甲酸流动相体系的分离效果优于其他两种流动相体系,同时发现在进样量大时出现平头峰。并且在优化条件下,对实际样品中游离的二苯甲烷二异氰酸酯进行了测定。     

血清AFP、CA199、GGT、ALP联检肝癌早期诊断价值

目的:探讨甲胎蛋白(AFP)、糖类抗原199(CA199)、谷氨酰转肽酶(GGT)和碱性磷酸酶(ALP)单独或联合检测对原发性肝癌(PHC)的早期诊断价值。方法:本研究为回顾性研究,筛选2016年-2019年本院87例原发性肝癌(PHC)患者、105例慢性乙肝患者及104例健康志愿者,收集不同组首次入院和体检外周血检测数据和其他临床资料。比较各血清指标在组间差异性,分析了血清学指标与入组PHC临床分期和病理分型的相关性,进一步利用ROC曲线法分析血清指标单项与联合诊断的灵敏度、特异度。结果:AFP、CA199、GGT、ALP检测均值在PHC组均明显高于慢乙肝组和健康体检组。AFP阳性检测值与PHC临床分期(r=0.9536)和病理分型(r=0.525)呈正相关性。AFP诊断PHC灵敏度和特异性分别为60.87%和77.97%、精准度AUC为0.726。联合四项指标检测灵敏度、特异度和AUC分别为75.36%、65.64%、0.806。结论:AFP、CA199、GGT、ALP四项指标联合检测可提高原发性肝癌早期诊断的准确率,操作性强且易于推广。     

Effect on crystalline structure of AISI M2 steel using tungsten–thorium electrode through MRR,EWR, and surface finish

To investigate on the crystalline structure of AISI M2 steel by using tungsten–thorium electrode in electrical discharge machining (EDM) process was studied. Furthermore, the investigation were carried out for finding the value of material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR) of tool steel material depending upon three variable input process parameters. On the basis of weight loss, the value of MRR and EWR were calculated at optimized process parameter. Subsequently, surface topography of the processed material were examined through different characterization techniques like scanning electron microscopy (SEM), Optical surface profiler (OSP) and Atomic force microscopy (AFM), respectively. In XRD study, broadening of the peak was observed which confirmed the change in material properties due to the homogeneous dispersion of the particles inside the matrix. Lowest surface roughness and MRR of 0.001208 mg/min was obtained. Minimum surface roughness was obtained 1.12 μm and 2.18427 nm by OSP and AFM study, respectively. Also, minimum EWR was found as 0.013986 mg/min.     

A novel virtual instrument for power quality surveillance based in higher-order statistics and case-based reasoning

This paper presents the performance results of a Virtual Instrument (VI) based in Case-Based Reasoning (CBR), conceived to online monitor the power-quality. The PC-based instrument receives data through a DAQ board and a differential probe, while maintaining economy by eliminating the extra network construction and hardware. Being flexible, presents an user-friendly interface and a large data storage capacity, since it uses the hard disk. The computational guts of the instrument are based in third and fourth-order statistics (along with the variance), which enhance detection capability and reject noise influence. A time-domain sliding window sweeps the register under test and offers a time-variation pattern which reflects the deviation of the statistical estimator with respect to the steady state. This three-valued time-series comprises variance, skewness and kurtosis evolution, and constitutes a triple input to the innovative CBR module, which in turn is capable of distinguishing electrical anomalies among five categories (the sixth is reserved to the healthy signal): non-50 Hz, 50-Hz-asymmetrical, 50-symmetrical non-sinusoidal, swell and sag. Online surveillance tests developed over the local electrical network show acceptable accuracy (96%).