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.     

Ecological and Economic Services Provided by Birds on Jamaican Blue Mountain Coffee Farms

Abstract: Coffee farms can support significant biodiversity, yet intensification of farming practices is degrading agricultural habitats and compromising ecosystem services such as biological pest control. The coffee berry borer (Hypothenemus hampei) is the world's primary coffee pest. Researchers have demonstrated that birds reduce insect abundance on coffee farms but have not documented avian control of the berry borer or quantified avian benefits to crop yield or farm income. We conducted a bird‐exclosure experiment on coffee farms in the Blue Mountains, Jamaica, to measure avian pest control of berry borers, identify potential predator species, associate predator abundance and borer reductions with vegetation complexity, and quantify resulting increases in coffee yield. Coffee plants excluded from foraging birds had significantly higher borer infestation, more borer broods, and greater berry damage than control plants. We identified 17 potential predator species (73% were wintering Neotropical migrants), and 3 primary species composed 67% of migrant detections. Average relative bird abundance and diversity and relative resident predator abundance increased with greater shade‐tree cover. Although migrant predators overall did not respond to vegetation complexity variables, the 3 primary species increased with proximity to noncoffee habitat patches. Lower infestation on control plants was correlated with higher total bird abundance, but not with predator abundance or vegetation complexity. Infestation of fruit was 1–14% lower on control plants, resulting in a greater quantity of saleable fruits that had a market value of US$44–$105/ha in 2005/2006. Landscape heterogeneity in this region may allow mobile predators to provide pest control broadly, despite localized farming intensities. These results provide the first evidence that birds control coffee berry borers and thus increase coffee yield and farm income, a potentially important conservation incentive for producers.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

Epidemiologic Analysis of Factors Associated with Local Disappearances of Native Ranid Frogs in Arizona

Abstract:  We examined factors that may independently or synergistically contribute to amphibian population declines. We used epidemiologic case–control methodology to sample and analyze a large database developed and maintained by the Arizona Game and Fish Department that describes historical and currently known ranid frog localities in Arizona, U.S.A. Sites with historical documentation of target ranid species ( n = 324) were evaluated to identify locations where frogs had disappeared during the study period (case sites) and locations where frog populations persisted (control sites). Between 1986 and 2003, 117 (36%) of the 324 sites became case sites, of which 105 were used in the analyses. An equal number of control sites were sampled to control for the effects of time. Risk factors, or predictor variables, were defined from environmental data summarized during site surveys and geographic information system data layers. We evaluated risk factors with univariate and multifactorial logistic-regression analyses to derive odds ratios (OR). Odds for local population disappearance were significantly related to 4 factors in the multifactorial model. Disappearance of frog populations increased with increasing elevation (OR = 2.7 for every 500 m, p < 0.01). Sites where disappearances occurred were 4.3 times more likely to have other nearby sites that also experienced disappearances (OR = 4.3, p < 0.01), whereas the odds of disappearance were 6.7 times less (OR = 0.15, p < 0.01) when there was a source population nearby. Sites with disappearances were 2.6 times more likely to have introduced crayfish than were control sites (OR = 2.6, p = 0.04). The identification of factors associated with frog disappearances increases understanding of declines occurring in natural populations and aids in conservation efforts to reestablish and protect native ranids by identifying and prioritizing implicated threats.     

氨法脱硫在热电厂中应用

随着二氧化硫对环境的污染越来越严重，国家环保局对燃煤电厂二氧化硫排放进行严格控制，电厂加装脱硫装置是迟早的事。阐述了氨法脱硫的工艺流程和自动控制．同时结合工程调试中出现的问题进行分析，为今后的脱硫工程提供一些借鉴。     

乌鲁木齐空气微生物含量的测定

用自然平皿沉降法对乌鲁木齐市13个室内外空气测点作了微生物含量的测定,结果表明平均室外空气的细菌、真菌、总菌含量及F/T%分别为28583 8、780 5、29364 3CFU·m-3及2 7,证实了该市空气处于中度微生物污染状态。少量测点显示其空气已受到严重污染,空气质量不佳。室内空气微生物污染也重。空气微生物污染以细菌为主。分析了室外空气微生物含量的时空分布特点差异,探讨了其成因,并与其他城市作了比较。文章指出增强环境忧患意识,采用切实而有效措施,减少环境污染的必要性。     

水危机与生态环境保护

本文对水危机及全球水源状况进行了分析，为保护人类水资源与生态环境进行了有益的探索。     

供水管线震害量化参数--渗漏面积的估算方法

为了分析管线破坏状态对震后供水管网功能的影响，首先需要对管线的震害状态进行量化。建议用管线渗漏面积标定管线的破坏状态。在管线震害分析和理论计算的基础上，提出了震后管线渗漏面积的计算方法，为进一步进行供水管网抗震分析和设计提供了研究基础。     

矿井水是宝贵的地下水资源

本文针对煤矿矿井水是废水的错误认识，深入浅出地讨论了矿井水的水质特征，鲜明地提出矿井水是宝贵的地下水资源的观点，以及矿井水资源化的法规保证。     

东部油田采出污水处理的长远对策

从综合治理，合理利用采出污水的长远利益出发，针对东部油田高含水阶段的新特点，提出地面高效处理，地下控水稳油相结合的治理策略，探讨了相关的技术和方法，并讨论了采出污水回注利用中应加强研究的几个问题。