煙氣排放連續(xù)監(jiān)測系統(tǒng)不確定度分析
發(fā)布時間：2019-05-22 23:52
【摘要】：煙氣排放連續(xù)監(jiān)測系統(tǒng)(CEMS),是我國對固定污染源有組織排放進行連續(xù)監(jiān)測的設(shè)備,尤其是對火電廠污染源的連續(xù)監(jiān)測。目前相關(guān)環(huán)保部門已經(jīng)將CEMS監(jiān)測數(shù)據(jù)作為排污核查、排污收費等相關(guān)工作的制定基礎(chǔ),因此,CEMS監(jiān)測數(shù)據(jù)的準確性對于環(huán)境監(jiān)測工作具有非常重要的意義。我國從2000年開始對CEMS的性能進行檢測,也稱為適用性檢測。本文通過對蘭州某熱電廠CEMS設(shè)備的監(jiān)測數(shù)據(jù)進行不確定度評定,并結(jié)合質(zhì)量控制圖對數(shù)據(jù)質(zhì)量進行進一步驗證,從不確定的角度對CEMS的數(shù)據(jù)分散性及設(shè)備穩(wěn)定性進行了說明。選取該廠7份CEMS監(jiān)測日報表中的監(jiān)測數(shù)據(jù)作為監(jiān)測結(jié)果。首先對顆粒物監(jiān)測系統(tǒng)分析發(fā)現(xiàn),1號、2號、7號監(jiān)測報表的顆粒物濃度不確定度較大,數(shù)據(jù)分散性大,結(jié)合質(zhì)量控制圖可知,三份監(jiān)測報表的質(zhì)量控制圖均表現(xiàn)為失控,證明數(shù)據(jù)質(zhì)量差。4號、5號、6號監(jiān)測報表的不確定度較小,說明數(shù)據(jù)分散性小,結(jié)合質(zhì)量控制圖可知,三份監(jiān)測報表的數(shù)據(jù)質(zhì)量較高。在對各個分量的分析過程中可知,測量重復性對其貢獻度較大,儀器本身的精度與誤差對其相對較小。對顆粒物監(jiān)測系統(tǒng)還分析了置信區(qū)間半寬和允許區(qū)間半寬,其中置信區(qū)間半寬為7.47%,允許區(qū)間半寬為21.52%,均符合顆粒物連續(xù)自動監(jiān)測儀器性能指標要求。對于該設(shè)備的氣態(tài)污染物監(jiān)測系統(tǒng),本文分析了SO2濃度和NOx濃度的監(jiān)測數(shù)據(jù)。對SO2濃度監(jiān)測數(shù)據(jù)的不確定度分析可知,1號和3號監(jiān)測報表的SO2濃度數(shù)據(jù)的不確定度都較高,說明數(shù)據(jù)的分散性較大,而對應(yīng)的質(zhì)量控制圖均失控,證明了數(shù)據(jù)質(zhì)量差。4號監(jiān)測報表的SO2濃度數(shù)據(jù)的不確定度最小,說明數(shù)據(jù)分散性小,對應(yīng)的質(zhì)量控制圖表現(xiàn)為數(shù)據(jù)質(zhì)量最好,證明了數(shù)據(jù)的可靠程度高。對NOx濃度監(jiān)測數(shù)據(jù)的不確定度分析可知,1號日報表的NOx濃度監(jiān)測數(shù)據(jù)的不確定度最大,說明數(shù)據(jù)的分散性大,而該報表所對應(yīng)的質(zhì)量控制圖表現(xiàn)為失控,證明了數(shù)據(jù)質(zhì)量差,可信度低。4號報表的NOx濃度監(jiān)測數(shù)據(jù)的不確定度最小,對應(yīng)的質(zhì)量控制圖數(shù)據(jù)質(zhì)量表現(xiàn)最好,證明了數(shù)據(jù)的可靠程度高。由分析結(jié)果可知,雖然對兩種污染物使用相同的測量原理,但SO2濃度的不確定度明顯大于NOx濃度的不確定度。對其不確定度分量進行分析可知,SO2濃度的不確定度主要由測量重復性引入,說明測量過程對SO2濃度的監(jiān)測影響較大。對CEMS進行不確定度分析時,建立的測量模型并不是唯一的,若采取不同測量方法或程序,則不確定度的分析模型也不相同。本文根據(jù)蘭州某熱電廠的CEMS設(shè)備建立了相應(yīng)的初步分析模型,做到了盡量不遺漏不確定度來源,經(jīng)過計算得到各個系統(tǒng)的不確定度。為企業(yè)煙氣自動監(jiān)測領(lǐng)域的不確定度分析提供參考。更進一步說明了不確定度分析在環(huán)境監(jiān)測工作中所具有的重要學術(shù)價值和實際意義。
[Abstract]:(CEMS), a continuous monitoring system for flue gas emissions, is a continuous monitoring equipment for organized emissions of fixed pollution sources in China, especially for pollution sources in thermal power plants. At present, the relevant environmental protection departments have taken CEMS monitoring data as the basis of emission verification, sewage charge and other related work. Therefore, the accuracy of CEMS monitoring data is of great significance to environmental monitoring. Since 2000, the performance of CEMS has been tested in China, also known as applicability testing. In this paper, the uncertainty of the monitoring data of CEMS equipment in a thermal power plant in Lanzhou is evaluated, and the data quality is further verified by the quality control chart. The data dispersion and equipment stability of CEMS are explained from an uncertain point of view. The monitoring data of 7 CEMS monitoring daily statements were selected as the monitoring results. First of all, it is found that the particle concentration uncertainty of No. 1, No. 2 and No. 7 monitoring reports is large and the data dispersion is large. Combined with the quality control chart, it can be seen that the quality control charts of the three monitoring reports are out of control. It is proved that the quality of the data is poor. The uncertainty of the monitoring statements No. 4, No. 5 and No. 6 is small, which indicates that the dispersion of the data is small. Combined with the quality control chart, it can be seen that the data quality of the three monitoring reports is higher. In the process of analyzing each component, it can be seen that the repeatability of measurement contributes greatly to it, and the accuracy and error of the instrument itself are relatively small. The half width of confidence interval and the half width of allowable interval are also analyzed for particulate matter monitoring system, in which the half width of confidence interval is 7.47%, and the half width of allowable interval is 21.52%, all of which meet the performance requirements of continuous automatic monitoring instrument of particulate matter. For the gaseous pollutant monitoring system of the equipment, the monitoring data of SO2 concentration and NOx concentration are analyzed in this paper. The uncertainty analysis of SO2 concentration monitoring data shows that the uncertainty of SO2 concentration data of No. 1 and No. 3 monitoring reports is higher, which indicates that the dispersion of the data is large, and the corresponding quality control chart is out of control. It is proved that the data quality is poor. The uncertainty of SO2 concentration data in No. 4 monitoring report is the smallest, which indicates that the data dispersion is small, and the corresponding quality control chart shows that the data quality is the best, which proves that the reliability of the data is high. The uncertainty analysis of NOx concentration monitoring data shows that the uncertainty of NOx concentration monitoring data in daily report No. 1 is the largest, which indicates that the dispersion of the data is large, and the quality control chart corresponding to the report is out of control, which proves that the data quality is poor. The reliability is low. The uncertainty of NOx concentration monitoring data in report No. 4 is the smallest, and the quality performance of the corresponding quality control chart is the best, which proves that the reliability of the data is high. The results show that although the same measurement principle is used for the two pollutants, the uncertainty of SO2 concentration is obviously greater than that of NOx concentration. Through the analysis of its uncertainty component, it can be seen that the uncertainty of SO2 concentration is mainly introduced by the repeatability of measurement, which indicates that the measurement process has a great influence on the monitoring of SO2 concentration. When the uncertainty analysis of CEMS is carried out, the measurement model is not unique, and if different measurement methods or programs are adopted, the analysis model of uncertainty is also different. In this paper, according to the CEMS equipment of a thermal power plant in Lanzhou, the corresponding preliminary analysis model is established, and the source of uncertainty is not omitted as far as possible, and the uncertainty of each system is obtained by calculation. It provides a reference for the uncertainty analysis in the field of automatic monitoring of enterprise flue gas. The important academic value and practical significance of uncertainty analysis in environmental monitoring are further explained.
【學位授予單位】：蘭州交通大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：X84
本文編號：2483393
[Abstract]:(CEMS), a continuous monitoring system for flue gas emissions, is a continuous monitoring equipment for organized emissions of fixed pollution sources in China, especially for pollution sources in thermal power plants. At present, the relevant environmental protection departments have taken CEMS monitoring data as the basis of emission verification, sewage charge and other related work. Therefore, the accuracy of CEMS monitoring data is of great significance to environmental monitoring. Since 2000, the performance of CEMS has been tested in China, also known as applicability testing. In this paper, the uncertainty of the monitoring data of CEMS equipment in a thermal power plant in Lanzhou is evaluated, and the data quality is further verified by the quality control chart. The data dispersion and equipment stability of CEMS are explained from an uncertain point of view. The monitoring data of 7 CEMS monitoring daily statements were selected as the monitoring results. First of all, it is found that the particle concentration uncertainty of No. 1, No. 2 and No. 7 monitoring reports is large and the data dispersion is large. Combined with the quality control chart, it can be seen that the quality control charts of the three monitoring reports are out of control. It is proved that the quality of the data is poor. The uncertainty of the monitoring statements No. 4, No. 5 and No. 6 is small, which indicates that the dispersion of the data is small. Combined with the quality control chart, it can be seen that the data quality of the three monitoring reports is higher. In the process of analyzing each component, it can be seen that the repeatability of measurement contributes greatly to it, and the accuracy and error of the instrument itself are relatively small. The half width of confidence interval and the half width of allowable interval are also analyzed for particulate matter monitoring system, in which the half width of confidence interval is 7.47%, and the half width of allowable interval is 21.52%, all of which meet the performance requirements of continuous automatic monitoring instrument of particulate matter. For the gaseous pollutant monitoring system of the equipment, the monitoring data of SO2 concentration and NOx concentration are analyzed in this paper. The uncertainty analysis of SO2 concentration monitoring data shows that the uncertainty of SO2 concentration data of No. 1 and No. 3 monitoring reports is higher, which indicates that the dispersion of the data is large, and the corresponding quality control chart is out of control. It is proved that the data quality is poor. The uncertainty of SO2 concentration data in No. 4 monitoring report is the smallest, which indicates that the data dispersion is small, and the corresponding quality control chart shows that the data quality is the best, which proves that the reliability of the data is high. The uncertainty analysis of NOx concentration monitoring data shows that the uncertainty of NOx concentration monitoring data in daily report No. 1 is the largest, which indicates that the dispersion of the data is large, and the quality control chart corresponding to the report is out of control, which proves that the data quality is poor. The reliability is low. The uncertainty of NOx concentration monitoring data in report No. 4 is the smallest, and the quality performance of the corresponding quality control chart is the best, which proves that the reliability of the data is high. The results show that although the same measurement principle is used for the two pollutants, the uncertainty of SO2 concentration is obviously greater than that of NOx concentration. Through the analysis of its uncertainty component, it can be seen that the uncertainty of SO2 concentration is mainly introduced by the repeatability of measurement, which indicates that the measurement process has a great influence on the monitoring of SO2 concentration. When the uncertainty analysis of CEMS is carried out, the measurement model is not unique, and if different measurement methods or programs are adopted, the analysis model of uncertainty is also different. In this paper, according to the CEMS equipment of a thermal power plant in Lanzhou, the corresponding preliminary analysis model is established, and the source of uncertainty is not omitted as far as possible, and the uncertainty of each system is obtained by calculation. It provides a reference for the uncertainty analysis in the field of automatic monitoring of enterprise flue gas. The important academic value and practical significance of uncertainty analysis in environmental monitoring are further explained.
【學位授予單位】：蘭州交通大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：X84
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