On-line monitoring and fault diagnosis of chemical process is extremely important for operation safety and product quality. Principal component analysis (PCA) has been widely used in multivariate statistical process m...On-line monitoring and fault diagnosis of chemical process is extremely important for operation safety and product quality. Principal component analysis (PCA) has been widely used in multivariate statistical process monitoring for its ability to reduce processes dimensions. PCA and other statistical techniques, however, have difficulties in differentiating faults correctly in complex chemical process. Support vector machine (SVM) is a novel approach based on statistical learning theory, which has emerged for feature identification and classification. In this paper, an integrated method is applied for process monitoring and fault diagnosis, which combines PCA for fault feature extraction and multiple SVMs for identification of different fault sources. This approach is verified and illustrated on the Tennessee Eastman benchmark process as a case study. Results show that the proposed PCA-SVMs method has good diagnosis capability and overall diagnosis correctness rate.展开更多
Software projects influenced by many human factors generate various risks. In order to develop highly quality software, it is important to respond to these risks reasonably and promptly. In addition, it is not easy fo...Software projects influenced by many human factors generate various risks. In order to develop highly quality software, it is important to respond to these risks reasonably and promptly. In addition, it is not easy for project managers to deal with these risks completely. Therefore, it is essential to manage the process quality by promoting activities of process monitoring and design quality assessment. In this paper, we discuss statistical data analysis for actual project management activities in process monitoring and design quality assessment, and analyze the effects for these software process improvement quantitatively by applying the methods of multivariate analysis. Then, we show how process factors affect the management measures of QCD (Quality, Cost, Delivery) by applying the multiple regression analyses to observed process monitoring data. Further, we quantitatively evaluate the effect by performing design quality assessment based on the principal component analysis and the factor analysis. As a result of analysis, we show that the design quality assessment activities are so effective for software process improvement. Further, based on the result of quantitative project assessment, we discuss the usefulness of process monitoring progress assessment by using a software reliability growth model. This result may enable us to give a useful quantitative measure of product release determination.展开更多
建立超高效液相色谱-串联质谱同时、快速分析18种酚类物质的方法,测定比较铁皮石斛茎、叶、花部位含量差异。样品用甲醇-水溶液提取,提取液中的目标化合物经Waters T3 C_(18)柱梯度洗脱分离,电喷雾串联三重四极杆质谱仪正、负离子扫描...建立超高效液相色谱-串联质谱同时、快速分析18种酚类物质的方法,测定比较铁皮石斛茎、叶、花部位含量差异。样品用甲醇-水溶液提取,提取液中的目标化合物经Waters T3 C_(18)柱梯度洗脱分离,电喷雾串联三重四极杆质谱仪正、负离子扫描方式多反应监测模式检测。结果表明:以18种酚类物质标准品作为对照,在铁皮石斛样品中共检出15种酚类组分,分别为3,5-二羟基苯甲酸、橘皮素、绿原酸、槲皮素、芦丁、对羟基苯甲酸、咖啡酸、丁香酸、香草酸、山柰酚、对香豆酸、芥子酸、阿魏酸、3-羟基肉桂酸、水杨酸。铁皮石斛不同部位多酚组分含量为花>叶>茎,相对于其他酚类组分,芦丁在铁皮石斛茎、叶、花中的含量均为最高。铁皮石斛不同部位主要酚类组分表现出一定的差别:铁皮石斛花中主要含有芦丁、咖啡酸、阿魏酸和对羟基苯甲酸,铁皮石斛叶中芦丁和阿魏酸的含量相对较高,而铁皮石斛茎部主要酚类组分则为芦丁、阿魏酸与香草酸。实验结果可为铁皮石斛不同部位酚类组分的利用提供一定的科学依据。展开更多
文摘On-line monitoring and fault diagnosis of chemical process is extremely important for operation safety and product quality. Principal component analysis (PCA) has been widely used in multivariate statistical process monitoring for its ability to reduce processes dimensions. PCA and other statistical techniques, however, have difficulties in differentiating faults correctly in complex chemical process. Support vector machine (SVM) is a novel approach based on statistical learning theory, which has emerged for feature identification and classification. In this paper, an integrated method is applied for process monitoring and fault diagnosis, which combines PCA for fault feature extraction and multiple SVMs for identification of different fault sources. This approach is verified and illustrated on the Tennessee Eastman benchmark process as a case study. Results show that the proposed PCA-SVMs method has good diagnosis capability and overall diagnosis correctness rate.
文摘Software projects influenced by many human factors generate various risks. In order to develop highly quality software, it is important to respond to these risks reasonably and promptly. In addition, it is not easy for project managers to deal with these risks completely. Therefore, it is essential to manage the process quality by promoting activities of process monitoring and design quality assessment. In this paper, we discuss statistical data analysis for actual project management activities in process monitoring and design quality assessment, and analyze the effects for these software process improvement quantitatively by applying the methods of multivariate analysis. Then, we show how process factors affect the management measures of QCD (Quality, Cost, Delivery) by applying the multiple regression analyses to observed process monitoring data. Further, we quantitatively evaluate the effect by performing design quality assessment based on the principal component analysis and the factor analysis. As a result of analysis, we show that the design quality assessment activities are so effective for software process improvement. Further, based on the result of quantitative project assessment, we discuss the usefulness of process monitoring progress assessment by using a software reliability growth model. This result may enable us to give a useful quantitative measure of product release determination.
文摘建立超高效液相色谱-串联质谱同时、快速分析18种酚类物质的方法,测定比较铁皮石斛茎、叶、花部位含量差异。样品用甲醇-水溶液提取,提取液中的目标化合物经Waters T3 C_(18)柱梯度洗脱分离,电喷雾串联三重四极杆质谱仪正、负离子扫描方式多反应监测模式检测。结果表明:以18种酚类物质标准品作为对照,在铁皮石斛样品中共检出15种酚类组分,分别为3,5-二羟基苯甲酸、橘皮素、绿原酸、槲皮素、芦丁、对羟基苯甲酸、咖啡酸、丁香酸、香草酸、山柰酚、对香豆酸、芥子酸、阿魏酸、3-羟基肉桂酸、水杨酸。铁皮石斛不同部位多酚组分含量为花>叶>茎,相对于其他酚类组分,芦丁在铁皮石斛茎、叶、花中的含量均为最高。铁皮石斛不同部位主要酚类组分表现出一定的差别:铁皮石斛花中主要含有芦丁、咖啡酸、阿魏酸和对羟基苯甲酸,铁皮石斛叶中芦丁和阿魏酸的含量相对较高,而铁皮石斛茎部主要酚类组分则为芦丁、阿魏酸与香草酸。实验结果可为铁皮石斛不同部位酚类组分的利用提供一定的科学依据。
