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.     

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.     

全球液化石油气运输网络贸易社区特征及其演化分析

液化石油气在全球清洁能源消耗市场中扮演着极为重要的角色,其通过船舶在不同港口之间进行运输,而港口之间通过局部密集的运输关系,形成了联系极为紧密的贸易社区。采用复杂网络社区探测方法,基于2013—2017年全球液化石油气船舶轨迹大数据构建运输网络,并对其贸易社区特征及其演化趋势开展分析。结果表明：（1）液化石油气（Liquefied Petroleum Gas,LPG）贸易社区内的港口之间的联系更加紧密,不同社区内的枢纽港口联系也日益紧密;（2）各个贸易社区的规模呈现出增长趋势,且同一社区内的港口在地理空间上变得更为集聚;（3）亚太地区、中东、西北欧和地中海地区形成的社区在全球LPG贸易中一直保持着重要地位,而随着时间推移,美洲社区已逐渐从一个相对孤立的社区发展成为与其他社区存在紧密联系的社区。     

磁性氧化石墨处理乳化含油废水及磁致增强效应

以高铁酸钾为氧化剂,基于改进Hummers法制备了新型磁性氧化石墨材料,在SEM、FTIR、氮气吸脱附和表面接触角表征基础上,探究了该材料处理乳化含油废水的效果及磁致增强效应.结果表明：相较于石墨,磁性氧化石墨比表面积增大,表面有卷曲结构并负载着Fe₃O₄颗粒,具有含氧官能团,存在疏水性较强的微观孔隙结构.在外加磁场条件下,磁性氧化石墨团聚,形成疏水性宏观孔隙结构,利于乳化油滴的吸附和附着.磁性氧化石墨处理乳化含油废水的能力远好于石墨与粉末活性炭,且处理效率与磁场强度成正相关,COD去除率可达95%以上.使用后的磁性氧化石墨进行溶剂萃取或热处理,可以循环使用.磁性氧化石墨经过4次循环使用,热再生效率为92%,溶剂萃取再生效率为86%.以上研究为乳化含油废水的处理提供了一种有效的方法.     

电化学微传感器检测水中痕量铜离子

为改善微电极在阳极溶出伏安法检测重金属离子过程中低电流响应和低电催化能力的缺点,提出了一种在碳纤维微电极表面合成还原氧化石墨烯/纳米金材料制得还原氧化石墨烯纳米金修饰碳纤维微电极（rGO/AuNPs CFMEs）的方法.通过SEM表征,所制备的rGO/AuNPs CFMEs具有比表面积高、吸附能力强和催化活性好的特点,因此改性微电极适合作为方波阳极溶出伏安法（SWASV）测定水中铜离子（Cu²⁺）的工作电极.在构建微传感器测试水中痕量铜离子系统后,对pH值、电导率、富集时间和富集电位等检测条件进行了优化.在pH值为4,电导率为36.1S/m,富集时间为360s,富集电位为-1.2V的最佳条件下,铜的线性范围和检出限分别0~1.0μmol/L和2.4nmol/L.此外,微传感器的可重复性、长期稳定性以及选择性也得到了验证.     

磁性有序介孔碳的制备及其对水中双酚A的吸附

采用水热法成功制备了磁性有序介孔碳（Fe-OMC）,用于吸附水中双酚A （BPA）.采用高倍投射电镜、X射线衍射仪、傅里叶红外光谱仪、比表面积分析仪和振动样品磁强计对Fe-OMC进行表征.结果表明,该吸附剂具备较大的比表面积、独特的有序介孔孔道结构、丰富的含氧官能团以及较强的超顺磁性.Fe-OMC能够高效地吸附去除水中的BPA,平衡吸附量可达72.62mg/g,经过外加磁场分离回收后依旧具备较好的吸附性能.随着BPA浓度从1mg/L提高到20mg/L,其平衡吸附量由8.33mg/g增至91.78mg/g.随着pH值的升高呈现出先降低后升高再降低的趋势,最高吸附量出现在pH=8（75.34mg/g）.Fe-OMC对BPA的吸附过程可用准二级吸附动力学模型和Langmuir吸附等温模型进行描述.计算的热力学参数表明,Fe-OMC对BPA的吸附过程是自发进行的放热过程.