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.     

Research on flow assurance of deepwater submarine natural gas pipelines: Hydrate prediction and prevention

The formation of hydrate will lead to serious flow assurance problems in deepwater submarine natural gas transmission pipelines. However, the accurate evaluation model of the hydrate blocking risk for submarine natural gas transportation is still lacking. In this work, a novel model is established for evaluating the hydrate risk in deepwater submarine gas pipelines. Based on hydrate growth-deposition mechanism, the mathematical model mainly consists of mass, momentum and energy conservation equations. Meantime, the model results are obtained by finite difference method and iterative technique. Finally, the model has been applied in the production of deepwater gas field (L Gas Field) in China, and the sensitivity analysis of relevant parameters has been carried out. The results show that: (a). The mathematical model can well predict the hydrate blockage risk in deepwater natural gas pipelines after verification. (b). Hydrate is easily formed at the intersection of horizontal pipeline and vertical riser, and the maximum blocking position often occurs in middle of the riser. (c). The hydrate blockage degree and length of hydrate formation region (HFR) decrease with the increase of gas transport rate. (d). The hydrate blockage degree and length of HFR decrease with the increase of gas transport temperature. (e). The hydrate blockage degree and length of HFR increase with the extension of horizontal pipeline. (f). Injecting inhibitors can effectively inhibit hydrate formation and blockage, but the improvement of transmission measures can significantly reduce the dosage of inhibitor. It is concluded that measures such as increasing gas transportation rate and temperature, shortening horizontal pipeline length, optimizing inhibitor injection point and injection rate can play a safe, economic and efficient role in hydrate preventing and controlling.     

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.     

灰色协调度模型在产业用水系统分析中的应用

揭示产业用水系统的时空动态发展规律，探讨其内部的协调关系，是开展节水型社会建设规划，实现水资源可持续利用的关键。然而，目前对产业用水系统的协调性分析还缺乏较为有效的理论和方法。以往在利用协调度模型进行用水系统有序度研究时，通常采用两段叙述的线性分段函数表示，较不适用于描述产业用水系统内部要素的非线性结构。因此，针对产业用水系统的特性，利用灰关联原理建立有序度函数，以建立更适于用水系统分析的灰色协调度模型。利用该模型对上海市1997~2005年产业用水系统进行实证研究，结果显示：上海市产业用水系统基本有序，发展比较协调，其用水综合效益较大，但距离最优状态尚有潜力可挖；其中，农业用水子系统的发展较为欠缺，在未来用水规划中应予以重视。     

核算间接冷却水污染当量数的研讨

针对间接冷却水的特点和核算其污染当量数过程中存在的问题，阐述了间接冷却水的界定，水源水的采样监测技术，本底值的扣除以及超标排放的判别等环节的技术要求和注意事项，并就与之密切相关的几个问题展开了讨论,为核算间接冷却水当量数提供了一定的参考依据，建议增加水湿排放指标，以切实控制间接冷却水造成的主要污染－热污染。     

2010年上海世博会与长江三角洲都市圈的联动发展

本文在分析世界博览会发展过程的基础上，阐述了2010年上海世博会对上海乃至长江三角洲都市圈联动发展的机遇和挑战，并提出了长江三角洲都市圈空间整合与联动发展的战略措施。     

生态型港口综合评价指标体系初探

基于上海市建设生态型城市的长期目标，将港口作为城市生态系统中重要的子系统，对如何建设生态型港口提出了综合评价指标体系。通过筛选得到45项单因素指标，针对不同类型的港区有所分异，整个评价体系分为5个准则层（生态环境、经济效率、污染控制、环境管理、社会评价）和10个因素层（大气/声环境、生物资源、基底质量、经济发展、生产效率、循环经济、污染排放、清洁生产、环保投入、社会参与），并采用AHP（层次分析）法确定了各层次的权重分配。进而根据2005年上海港年均生产状况和2006年上半年的港区环境－资源调查，尝试对上海港7种主要类型（集装箱、件杂货/成品、多用途、干散、粮食港区、液散、客运）的15个港区进行了现状评估。然而，生态港评价系统的指标选取、权重制定、评估级别等实践与完善仍需要多学科和政府职能部门的参与。最后，项目还提出了水生态健康、航道淤积、生态风险、水陆景观等非定量生态港评价因子。