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.     

井下光谱多参数分析系统开发

本系统基于气体浓度光学分析方法理论朗伯-比尔(Lambert-Beer)定律、光谱气体检测技术开发,实现了对煤矿火灾与瓦斯灾害超前预警、灾害产生的有毒有害气体实时监测和煤矿环境气体爆炸危险性辨识,对于煤矿灾害防治、救灾过程中杜绝次生灾害,保障煤矿工人及救护队员的生命安全,促进煤矿安全生产具有重要意义。     

SELECTING TREND TESTS FOR WATER QUALITY SERIES WITH SERIAL CORRELATION AND MISSING VALUES1

ABSTRACT: The use of nonparametric tests for monotonic trend has flourished in recent years to support routine water quality data analyses. The validity of an assumption of independent, identically distributed error terms is an important concern in selecting the appropriate nonparametric test, as is the presence of missing values. Decision rules are needed for choosing between alternative tests and for deciding whether and how to pre-process data before trend testing. Several data pre-processing procedures in conjunction with the Mann-Kendall tau and the Seasonal Kendall test (with and without serial correlation correction) are evaluated using synthetic time series with generated serial correlation and missing data. A composite test (pre-testing for serial correlation followed by one of two trend tests) is evaluated and was found to perform satisfactorily.     

Sensitivity analysis of a parameterization of the stomatal component of the DO3SE model for Quercus ilex to estimate ozone fluxes

A sensitivity analysis of a proposed parameterization of the stomatal conductance (g(s)) module of the European ozone deposition model (DO(3)SE) for Quercus ilex was performed. The performance of the model was tested against measured g(s) in the field at three sites in Spain. The best fit of the model was found for those sites, or during those periods, facing no or mild stress conditions, but a worse performance was found under severe drought or temperature stress, mostly occurring at continental sites. The best performance was obtained when both f(phen) and f(SWP) were included. A local parameterization accounting for the lower temperatures recorded in winter and the higher water shortage at the continental sites resulted in a better performance of the model. The overall results indicate that two different parameterizations of the model are needed, one for marine-influenced sites and another one for continental sites.     

人类活动对长江河口硝酸盐输入通量的影响

利用长江口枯季潮区界大通站近 4 0年来的水文化学观测资料 ,求得长江径流来源的硝酸盐通量 ,并以此作为长江河口硝酸盐的输入通量。结合历年长江流域的社会经济统计资料和降水量资料等分析 ,发现长江河口硝酸盐的输入通量与流域的人口密度、农业氮肥施用量、灌溉面积以及降水量等显著正相关。随着人口的增长 ,流域内的人类活动不断加剧 ,直接或间接地对长江河口硝酸盐的输入通量产生影响。而降水及灌溉等活动促进了土壤中氮素向河流流失的过程 ,并经长江径流向河口、海洋输送。 90年代后期 ,由人类因素造成的硝酸盐通量的增加占长江河口硝酸盐输入通量的95 %以上。降水引起的水土流失和大气氮氧化物的沉降是硝酸盐通量增加的直接原因 ,而农业活动、燃料燃烧和污水排放等人类活动是该通量变化的主要控制因素     

Evaluation of Carbon Uptake and Emissions by Forests in Korea During the Last Thirty Years (1973–2002)

The contribution of Korean forests to carbon sequestration for anthropogenic carbon emissions was evaluated. In addition, monitoring of carbon species released from forest fires was conducted. Despite a high carbon uptake by Korean forests, a tremendous increase in fossil fuel burning resulted in a small contribution by forests to carbon removal. The removal efficiency had a 5–31% range with an average of 12% during the period 1973–2002. In 2000, the amount of carbon released from burned trees corresponded to 1.6% of carbon uptake by forests. The distribution of surface CO concentration (ppb) derived from MOPITT (Measurement of Pollution in the Troposphere) showed high CO levels over the East/Japan Sea on April 10, 2000 when the largest forest fires occurred along the east coast of Korea. Trajectory analysis and ground CO measurements also indicated that CO levels over the East/Japan Sea were influenced by forest fires. This study suggests that continuous monitoring of carbon emissions from forest fires is needed for a more reliable estimate of carbon flux in the environment.     

Decision making under uncertainty in case of soil remediation

Decisions on soil remediation are one of the most difficult management issues of municipal and state agencies. The assessment of contamination is uncertain, the costs of remediation are high, and the impacts on the environment are multiple. This paper presents a general, transparent, and consistent method for decision making among the remediation alternatives. Soil washing, phytoremediation, and no remediation are exemplarily considered. Multi-criteria utility functions including (a) the cost of remediation (b) the impact on human health and agricultural productivity, and (c) the economic gain after remediation are constructed using probability density functions representing contamination for all site coordinates. Herewith, the probability of different types of (i) correct decisions such as a hit or a true rejection and (ii) erroneous decisions such as a false alarm or miss are examined. The decision theoretic model is applied to a case study on heavy metal contaminated soil. This case study reveals the non-linear structure of multi-criteria-decision making. The case study shows that the geostatistical uncertainties of the log-normal distributed soil contamination must be taken into account: When uncertainties are not considered and the utilities are assessed according to the estimated value for a spatial unit, only few (N=26) spatial units result where the utility score of the alternative soil washing are higher than the utility score to the no remediation alternative. However, when taking into account geostatistical uncertainties of the log-normal soil distribution this number is about ten times greater (N=237). Furthermore, the use of 'maximizing expected utility' as decision rule is critical in that it may lead to a high probability of misses.     

MnFe2O4磁性纳米棒非均相Fenton催化降解水中四环素的研究

采用水热合成法成功制备出MnFe₂O₄磁性纳米棒（s-MnFe₂O₄）,并考察了商品化的Fe₃O₄、MnFe₂O₄和合成的s-MnFe₂O₄纳米棒这3种磁性纳米颗粒作为非均相Fenton催化剂降解水中四环素抗生素的性能.同时,采用X射线衍射（XRD）、透射电镜（TEM）、N₂吸附-脱附、振动样品磁强计（VSM）及X射线光电子能谱（XPS）等技术对催化剂的理化性质进行了表征.非均相Fenton催化降解四环素的结果表明,s-MnFe₂O₄具有最高的催化活性,反应180 min,四环素的去除率可以达到87.6%,TOC的去除率达到47.5%.自由基捕获试验证实了羟基自由基（·OH）是非均相Fenton氧化过程中的主要活性物种.s-MnFe₂O₄磁性纳米棒的高催化活性归因于其表面拥有较高含量的Mn³⁺和Fe²⁺物种,它们的存在能加速界面电子的转移效率,从而促进·OH的生成.合成的s-MnFe₂O₄催化剂具有良好的稳定性,循环使用6次,四环素的去除率仅从87.6%降低到80.2%,且氧化过程中活性组分的流失很少.