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.     

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。     

地表水样品自然沉降时间对总磷测定结果的影响分析

地表水中总磷含量高低是评定水质优劣的一项重要指标,分析数据表明丰水期中总磷主要来源于泥沙中吸附的有机磷和无机磷,而溶解态磷含量较少;水样中总磷含量随着自然沉降时间的延长而逐渐降低.因此样品采集回来后样品的自然沉降时间是影响地表水中总磷测定结果的一个主要原因之一.     

定量风险评价标准探讨

围绕定量评价标准对风险的度量和制定风险评价标准的基本原则等方面的进展和存在的问题进行了初步的探讨，分析归纳了国处有着的个人风险和社会风险标准，提出具有重大危害性的工业设施对员工或公众造成的风险，不应显著高于人们在日常生活中接触到其他风险；每年１０＾－６的死亡风险是可以忽略不计的个人风险水平等观点。     

生物硝化池污水中硝化细菌的快速定量研究

实验采用聚合酶链式反应（PCR）技术与最大几率数法（MPN）相结合的MPN－PCR法对生物硝化池污水中的硝化细菌进行快速定量。所用的一对PCR引物是在对硝化细菌的16SrRNA基因进行系统比较的基础上设计合成的，可以扩增出大小为388bp的DNA片段。以从生物硝化池污水中抽提的含硝化细菌DNA的混合DNA为模板，进行PCR扩增并确定合适的扩增条件。运用MPN－PCR法进行定量检测的整个过程可在几小时之内完成。     

相关分析在大气优化布点过程中的成功演绎

通过相关指数在广东省城市大气环境监测省控站优化组筛选中的实践和探究,表明相关分析是个简单、实用、有效的方法,具有参考和应用价值。