工作场所和环境空气污染物浓度通过开放路径傅立叶变换红外光谱测量:一种统计过程控制技术,用于检测正常操作条件的变化。

M S Malachowski, S P Levine, G Herrin, R C Spear, M Yost, Z Yi
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引用次数: 22

摘要

开放路径傅里叶变换红外光谱(OP-FTIR)是一种新的空气监测技术,可用于实时或近实时测量空气污染物的浓度。OP-FTIR光谱已用于监测工作场所的气体和蒸气暴露,危险废物场所的排放,并跟踪围栏沿线的排放。本文讨论了一种统计过程控制技术,该技术可以与OP-FTIR光谱仪收集的空气监测数据一起使用,以检测工作场所或围栏线中偏离正常操作条件的情况。时间序列数据,绘制连续的空气样本浓度的时间,进行了分析。通过拟合动态模型去除时间序列数据中的自相关。控制图与模型拟合数据的残差一起使用,以确定是否可以快速检测到偏离定义的正常操作条件。利用不同室内空气流量和混合条件下收集的数据,对Shewhart控制图和指数加权移动平均(EWMA)控制图进行评估。在快速变化的条件下,Shewhart控制图能够检测到模拟过程区域中的泄漏。发现EWMA控制图对空气监测数据中的漂移和缓慢变化的浓度更为敏感。时间序列和统计过程控制技术也应用于在一家化工厂实地研究期间获得的数据。对丙烯腈- 1,3-丁二烯-苯乙烯(ABS)聚合工艺的生产区域进行了近实时监测。基于时间序列和统计过程控制技术的决策逻辑在工作场所和环境监测中有多种应用。这些应用可能包括发出警报或警告信号,提高工人呼吸保护水平,或在确定气体和蒸汽浓度失控时疏散社区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Workplace and environmental air contaminant concentrations measured by open path Fourier transform infrared spectroscopy: a statistical process control technique to detect changes from normal operating conditions.

Open path Fourier transform infrared (OP-FTIR) spectroscopy is a new air monitoring technique that can be used to measure concentrations of air contaminants in real or near-real time. OP-FTIR spectroscopy has been used to monitor workplace gas and vapor exposures, emissions from hazardous waste sites, and to track emissions along fence lines. This paper discusses a statistical process control technique that can be used with air monitoring data collected with an OP-FTIR spectrometer to detect departures from normal operating conditions in the workplace or along a fence line. Time series data, produced by plotting consecutive air sample concentrations in time, were analyzed. Autocorrelation in the time series data was removed by fitting dynamic models. Control charts were used with the residuals of the model fit data to determine if departures from defined normal operating conditions could be rapidly detected. Shewhart and exponentially weighted moving average (EWMA) control charts were evaluated for use with data collected under different room air flow and mixing conditions. Under rapidly changing conditions the Shewhart control chart was able to detect a leak in a simulated process area. The EWMA control chart was found to be more sensitive to drifts and slowly changing concentrations in air monitoring data. The time series and statistical process control techniques were also applied to data obtained during a field study at a chemical plant. A production area of an acrylonitrile, 1,3-butadiene, and styrene (ABS) polymer process was monitored in near-real time. Decision logics based on the time series and statistical process control technique introduced suggest several applications in workplace and environmental monitoring. These applications might include signaling of an alarm or warning, increasing levels of worker respiratory protection, or evacuation of a community, when gas and vapor concentrations are determined to be out-of-control.

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