PLS-based EWMA fault detection strategy for process monitoring

Fault detection (FD) and diagnosis in industrial processes is essential to ensure process safety and maintain product quality. Partial least squares (PLS) has been used successfully in process monitoring because it can effectively deal with highly correlated process variables. However, the conventional PLS-based detection metrics, such as the Hotelling's T² and the Q statistics are ill suited to detect small faults because they only use information from the most recent observations. Other univariate statistical monitoring methods, such as the exponentially weighted moving average (EWMA) control scheme, has shown better abilities to detect small faults. However, EWMA can only be used to monitor single variables. Therefore, the main objective of this paper is to combine the advantages of the univariate EWMA and PLS methods to enhance their performances and widen their applicability in practice. The performance of the proposed PLS-based EWMA FD method was compared with that of the conventional PLS FD method through two simulated examples, one using synthetic data and the other using simulated distillation column data. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS, especially in the presence of faults with small magnitudes.     

显微构造分析法和包裹体方法在断层研究中的应用

在工程建设中，工地及邻近地区的断层活动性是工程设计的一项重要依据。在总结以往研究的基础上，介绍了显微构造分析法和包裹体方法在断层活动性评价中的国内外最新研究成果。事实表明，这两种方法在工程地质领域具有良好的应用前景。     

交通安全对策的关联树法分析

分析了交通安全的影响因素,结合系统工程理论,建立了道路交通安全对策关联树,并计算了指标的重要度,为提出合理的交通安全对策提供了理论依据.     

基于决策树的辽宁省北部沙漠化信息提取研究

以沙漠化问题较突出的辽宁省北部地区为例,选取2007年Landsat 5 TM遥感影像作为基本数据源,通过对影像中耕地、林地、草地、水域等常见地物及典型沙漠化土地进行光谱特征分析和波段间的相互运算,将修改型土壤调整植被指数（MSAVI）、归一化差异水体指数（NDWI）和遥感图像缨帽变换后的土壤亮度指数（SBI）、绿度植被指数（GVI）及湿度指数（WVI）等特征变量融入决策树分类模型后进行分层分离,从而实现对沙漠化信息的高精度提取。结果显示,决策树分类法可排除提取地物时的干扰信息,是保证沙漠化土地信息快速自动提取的方法之一。     

隐伏断裂的地气测量及其意义

传统概念的地气测量是指地下上升到地表并扩散到大气空间的天然状态气体 ,如CO2 、CH4 、Rn、Hg、H2 等。近十多年的研究证实地气还包含着新的内涵 ,即地壳岩石以及地表土壤中还存着痕量的金属与非金属气体 ,通过捕集这些气体 ,可以获得更多的深部地质构造、矿床信息。据报导 ,国内外的研究主要是在已知矿床上做的正演研究。本文是在已知隐伏断层构造上方地表 ,试验金属与非金属地气存在的可能性。     

Sulfur speciation and bioaccumulation in camphor tree leaves as atmospheric sulfur indicator analyzed by synchrotron radiation XRF and XANES

Analyzing and understanding the effects of ambient pollution on plants is getting more and more attention as a topic of environmental biology.A method based on synchrotron radiation X-ray fluorescence and X-ray absorption near edge structure spectroscopy was established to analyze the sulfur concentration and speciation in mature camphor tree leaves (CTLs),which were sampled from 5 local fields in Shanghai,China.Annual SO2 concentration,SO42-concentration in atmospheric particulate,SO42-and sulfur concentration in soil were also analyzed to explore the relationship between ambient sulfur sources and the sulfur nutrient cycling in CTLs.Total sulfur concentration in mature camphor tree leaves was 766-1704 mg/kg.The mainly detected sulfur states and their corresponding compounds were +6 (sulfate,include inorganic sulfate and organic sulfate),+5.2 (sulfonate),+2.2 (suloxides),+0.6 (thiols and thiothers),+0.2 (organic sulfides).Total sulfur concentration was strongly correlated with sulfate proportion with a linear correlation coefficient up to 0.977,which suggested that sulfur accumulated in CTLs as sulfate form.Reduced sulfur compounds (organic sulfides,thiols,thioethers,sulfoxide and sulfonate) assimilation was sufficed to meet the nutrient requirement for growth at a balanced level around 526 mg/kg.The sulfate accumulation mainly caused by atmospheric sulfur pollution such as SO2 and airborne sulfate particulate instead of soil contamination.From urban to suburb place,sulfate in mature CTLs decreased as the atmospheric sulfur pollution reduced,but a dramatic increase presented near the seashore,where the marine sulfate emission and maritime activity pollution were significant.The sulfur concentration and speciation in mature CTLs effectively represented the long-term biological accumulation of atmospheric sulfur pollution in local environment.     

基于决策树的城市黑臭水体遥感分级

水体黑臭程度遥感监测是了解城市水质现状和综合评价城市水环境治理效果的重要手段.以南京、常州、无锡和扬州为研究区,共采集171个样点,同步测量水质参数和光学参数,分析黑臭水体与一般水体的水色和光学特征,构建决策树模型进行重度黑臭水体、轻度黑臭水体和非黑臭水体（记为一般水体）识别.结果表明：①根据色度可将水体分为1~6类水体,其中,类型1~4为黑臭水体,分别为灰黑色、深灰色、灰色和浅灰色水体,类型5和类型6水体为一般水体,分别为绿色系和黄色系水体;②类型1水体的非色素颗粒物和有色可溶性有机物含量高,但色素颗粒物的吸收并不占主导,类型2和5水体的吸收以色素颗粒物吸收占主导,类型3、4和6水体的吸收以非色素颗粒物吸收占主导;③根据六类水体的反射光谱差异用黑臭水体差值指数（difference of black-odorous water index,DBWI）、三波段面积水体指数（green-red-nir area water index,G-R-NIR AWI）、绿光波段反射率和归一化黑臭水体指数（normalized difference black-odorous water index,NDBWI）构建的水体分类识别决策树,能够有效识别出重、轻度黑臭水体和一般水体;④将决策树模型应用于2019年4月9日扬州的PlanetScope影像上,并利用10个同步过境点进行验证,整体识别精度达到80.00%,K值达到0.67.通过水色分类后的城市水体分级模型方法,可推广应用于类似的水体,为黑臭水体监管提供技术方法.     

北京10个常绿树种颗粒物吸附能力研究

大气中颗粒物PM(particulate matter)不仅造成环境污染,还对人体造成严重的危害.城市绿色植物作为大气过滤器,能够有效地提高城市空气质量,保护人体健康.因此了解不同树种对空气颗粒物的吸附滞纳作用是必要的.以北京植物园10种常绿植被为研究对象,应用空气气溶胶再发生器(QRJZFSQ-I)测定了北京市常见6种乔木和4种灌木叶片对空气总悬浮颗粒物(TSP)、PM10、PM2.5和PM1.0的吸附能力.结果表明:1不同树种叶片表面附着颗粒物的能力差异明显,最高的是雪松(Cedrus deodara)和油松(Pinus tabuliformis),吸附量分别是(18.95±0.71)μg·cm-2和(14.61±0.78)μg·cm-2,冷杉(Abies fabri)最小,为(8.02±0.4)μg·cm-2;2不同树种叶片单位面积对不同颗粒物的附着能力也存在差异,附着PM10能力最强的是油松和雪松,附着PM2.5能力最强的是雪松、铺地柏(Juniperus procumbens)、龙柏(Juniperus chinensis cv.kaizuka)和油松,附着PM1.0能力最强的是雪松、铺地柏、冷杉和油松;3不同月份叶片上附着的各粒级颗粒物(PM10、PM2.5)占TSP的比例不同.其中PM10在4~6月之间主要表现两种变化趋势,一是先上升后下降,主要为灌木树种;二是逐渐上升,主要的树种是乔木树种.而PM2.5则没有这种明显的变化趋势.     

我国水源污染事故风险点定量识别方法

水源事故的频发会对城市供水系统产生威胁,有必要针对供水系统风险进行评估和防控。针对水源事故频发及高发因素定量甄别研究,筛选统计了国内近20年来1 900多起水质突发事故案例,梳理了触发水源水质污染的多种因素,通过构建水源水质安全事故树和贝叶斯网络进行了相互验证分析。结果表明：我国水源污染事故主要因素贡献为依次突然排放(0.466)、污染长期累积(0.242)、交通事故(0.109)等;采用贝叶斯网络计算进行验证,其结果与事故树方法一致性较好。该方法有助于水源污染防控工作中风险点甄别和排序,可为我国饮用水安全保障水平的提升提供支撑。     

基于大气被动式采样的人体头发中类二(口恶)英多氯联苯暴露的途径

本研究通过分析采集自云南省开远市的13个树皮混合样品和13个相应的头发混合样品中DL-PCBs的水平、同族体分布及相关性,研究了当地人群对DL-PCBs的主要暴露途径.结果表明,云南开远树皮和头发样品中DL-PCBs的含量分别为4.0~88.9 pg·g^-1和4.1~19.3 pg·g^-1,其在当地环境和人体中的污染程度均较轻.树皮和头发样品中主要的DL-PCB同族体均是PCB-118,分别占总含量的48%和61%.树皮样品中DL-PCBs的各同族体具有相同的源,其主要的来源可能是大气的长距离输移.云南开远市居民头发中的PCBs可能来源于内部暴露和外部暴露的综合作用,其中外部暴露对低氯代PCBs的贡献要高于高氯代PCBs.