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.     

A first trimester trisomy 13/trisomy 18 risk algorithm combining fetal nuchal translucency thickness,maternal serum free β-hCG and PAPP-A

This study examines 45 cases of trisomy 13 and 59 cases of trisomy 18 and reports an algorithm to identify pregnancies with a fetus affected by trisomy 13 or 18 by a combination of maternal age fetal nuchal translucency (NT) thickness, and maternal serum free β-hCG and PAPP-A at 11–14 weeks of gestation. In this mixed trisomy group the median MoM NT was increased at 2.819, whilst the median MoMs for free β-hCG and PAPP-A were reduced at 0.375 and 0.201 respectively. We predict that with the use of the combined trisomy 13 and 18 algorithm and a risk cut-off of 1 in 150 will for a 0.3% false positive rate allow 95% of these chromosomal defects to be identified at 11–14 weeks. Such algorithms will enhance existing first trimester screening algorithms for trisomy 21. Copyright © 2002 John Wiley & Sons, Ltd.