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.     

Food aid and food crisis in Sub-Saharan Africa: Statistical trends and implications*

This paper documents the rapid expansion and changes in food aid flows to Sub-Saharan Africa up to mid-1985. Trends for Sub-Saharan Africa as a whole and for the more seriously affected countries are examined, as are the comparative experiences of food aid of individual countries in the region. Table 11 lists the Sub-Saharan African countries and indicates the most seriously affected food-short countries, as defined by the WFP/FAO task force. It should be borne in mind that some practical problems exist in compiling data on food aid. These include lack of availability of reliable data, especially of most recent data; lack of common terminology and definitions; and different accounting systems. These data problems are sometimes a source of confusion. However, the basic facts are clear: food aid gradually emerged during the early 1980s as a resource too often of considerable significance to many countries of Sub-Saharan Africa. These trends were only accelerated with the crisis of 1984-1985. These facts provide a point of reference for further analysis of the sources of the crisis, its actual dimensions and consequences.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Trihalomethanes in Drinking Water of Greater Québec Region (Canada): Occurrence, Variations and Modelling

The levels of trihalomethanes (THMs) – the main species of by-product from water chlorination – were monitored in thedistribution systems of the five major drinking water utilitiesof the greater area of Québec City in order to investigate andmodel their occurrence on a spatial and seasonal basis. Data forTHMs and other water quality and operational parametersassociated with their formation were generated through a 16 monthsampling program involving several sites representing variablewater residence times, from the plant to the system extremity.The results demonstrate that the differences in measured THMlevels between the five utilities are mainly due to the variablequality of raw waters, the type of water treatment process beingused and the type and levels of applied disinfectant. Dependingon the utility, average THM levels were from 1.3 to 2.5 timeshigher in the system extremities than in the water leaving thetreatment plant. Also, average levels of THMs measured in summerat the distribution system extremities were, depending on theutility, from 2.5 to 5 times higher than the average levelsmeasured in winter. The seasonal differences were found to besignificantly greater than those observed by others in waterutilities in the United States and Europe and are explained inlarge part by the considerable changes, over the year, in thequality and temperature of surface waters in Southern Québec. Forthe five utilities under study, multivariate regression modelswere developed in order to predict spatial and seasonalvariations of THMs. Both residual chlorine demand and temperaturewere found to be better, statistically, as predictors for THMoccurrence. The usefulness of the developed models for routineand long term water quality management, as well as for assessmentof human exposure to THMs, are also discussed.     

linking various aspects of atmospheric change through a systems analysis of food

Although interdisciplinary collaboration to address a singleenvironmental problem is more common than in the past, all toooften the significant atmospheric problems of our day such asstratospheric ozone depletion, acidic deposition or climaticchange are addressed on a single issue basis. Systems analysis isa way of looking at a problem in a holistic, integrated fashionthrough including as many as practicable of the importantcomponents, and the linkages among them. Systems analysisoften begins with a conceptual model which, even if lackingquantification, is a useful means of changing ones thinking to amulti-issue approach. If possible, conceptual models areoperationalized by quantification (using the best availablescientific knowledge) of the stocks and flows of the relevantcomponents of the problem, and the processes that are involved.In this paper, a systems approach to food production is used tolink various atmospheric issues such as regional acidification andclimatic change. A spreadsheet model of food demand andproduction in various world regions examined the possible effectof atmospheric change on how much food we can grow, andwhether or not we may be able to meet the increased demand inthe year 2025. Using relatively modest changes in factors ofagricultural production, the spreadsheet model calculated globalshortfalls by the year 2025 of the order of 10 to 20% in someimportant agricultural crops, despite the improvements in cropproduction factors that are envisaged by the Food andAgricultural Organization from now until the year 2010, and thatwere extrapolated in this paper to 2025. The model alsocalculated that climatic change in combination with eithertropospheric ozone or increased UV-B radiation caused bydepletion of the stratospheric ozone layer may in general makethe situation worse than in the case of climatic change alone.Given the large uncertainties in the input data, the results in thispaper should not be viewed as predictions but rather as anexample of taking a relatively simple systems approach to foodproduction using a spreadsheet model, and calculating the effectsthat various aspects of atmospheric change might have upon it.Therefore, it is extremely important to know the effects uponcrop production factors of climatic change, tropospheric ozoneand increased UV-B radiation not only as individual issues, butalso of their combined effect since it is probable that in manyregions they will occur in combination.     

Application of CFD Methods for Modelling in Air Pollution Problems: Possibilities and Gaps

Different urban air pollution problems deal with complex structure of air flows and turbulence. For such problems the Computer Fluid Dynamics (CFD) methods become widely used. However, this approach despite a number of advantages has some problems. Experience of use of CFD tools for development of models and suggestions of their applications for a local scale air pollution over a complex terrain and stable stratification are discussed in this paper, including: Topography and complex geometry: choose of the co-ordinate system and computer grid; Turbulence closure for air pollution modelling: modified k- model for stable stratified ABL; Boundary conditions for vertical profiles of velocity for stable-stratified atmosphere; Effects of the radiation and thermal budget of inclined surfaces to dispersion of pollutants; Artificial sources of air dynamics and circulation.Some examples of CFD applications for air pollution modelling for a flat terrain, mountainous area, mining open cast and indoor ventilation are discussed. Modified k- model for stably-stratified ABL is suggested. Due to the isotropic character of the k- model a combination of it in vertical with the sub-grid turbulence closure in horizontal can be more suitable for ABL. An effective scheme of boundary conditions for velocity profiles, based on the developed similarity theory for stable-stratified ABL, is suggested. Alongside with the common studies of atmospheric dispersion, the CFD methods have also demonstrated a good potential for studying anthropogenic and artificial-ventilation sources of air dynamic and circulation in local-scale processes of air pollution.     

Multipoint source method in air pollution modelling of cold start emission

The paper presents a new method of air pollution modelling on a micro scale. For estimation of concentration of car exhaust pollutants, each car is treated as an instantaneous moving emission source. This approach enables us to model time and spatial changes of emission, especially during cold and cool start of an engine. These stages of engine work are a source of significant pollution concentration in urban areas. In this work, two models are proposed: one for the estimation of emission after cold start of the engine and another for the prediction of pollutant concentration. The first model (defined for individual exhaust gas pollutants) enables us to calculate the emission as a function of time after the cold or cool start, ambient temperature and average speed of motion. This model uses the HBEFA database. The second mathematical model is developed in order to calculate the pollutant dispersion and concentrations. The finite volume method is applied to discretise the set of partial differential equations describing wind flow and pollutant dispersion in the domain considered. Models presented in this paper can be called short-term models on a small spatial scale. The results of numerical simulation of pollutant emission and dispersion are also presented.     

上海地区二氧化硫浓度和风速的统计关系

应用上海市1986年6月至1987年5月间5个自动监测站的全年每日逐时SO_2浓度平均值和同步的风速平均值资料,按季进行比较、归纳,得到风速—SO_2浓度的诊断判据,并利用1984年全年的相应资料进行验证,准确率达85％;得到了各季浓度—风速的回归方程,和浓度—风速、温差的二元回归方程、复相关系数。     

Random walk modeling of wake dispersion for the exhaust tower of an underground tunnel in urban area

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