[Objectives]To explore the correlation of processing technology,physical parameters and chemical components during plain stir-baking of Trichosanthis Radix.[Methods]Based on mixture uniform experiment design,the Trich...[Objectives]To explore the correlation of processing technology,physical parameters and chemical components during plain stir-baking of Trichosanthis Radix.[Methods]Based on mixture uniform experiment design,the Trichosanthis Radix was prepared by plain stir-bake method.Delphi method was used to evaluate and select the highest-scoring processed product for measuring physical parameters.UV spectrophotometry was used to determine the contents of starch and polysaccharide.The correlation and linear regression model of processing technology,physical parameters and chemical components were established with the aid of SPSS 26.0[Results]After processing by plain stir-bake method,the relative density and chromaticity showed a decreasing trend in the processed products of Trichosanthis Radix,the oxidation value,hydroscopic rate and swelling decreased firstly and then increased,and pH increased firstly and then decreased.The content of total starch decreased,the content of polysaccharide increased,and there was a negative correlation between them.There was a significant positive correlation between temperature and oxidation value,swelling and hydroscopic rate,hydroscopic rate and polysaccharide,and there was a significant negative correlation between relative density and hydroscopic rate or polysaccharide,total starch and hydroscopic rate or swelling.The linear relation model between processing technology and physical parameters and chemical components was r2>0.9.[Conclusions]After processing by plain stir-bake method,the physical parameters of Trichosanthis Radix changed,and there may be mutual conversion between total starch and polysaccharides.To a certain extent,physical parameters can be used to evaluate the quality of processed products of Trichosanthis Radix.This study is expected to provide a reference for research on quality evaluation of processed products of traditional Chinese medicine.展开更多
Process monitoring techniques are of paramount importance in the chemical industry to improve both the product quality and plant safety.Small or incipient irregularities may lead to severe degradation in complex chemi...Process monitoring techniques are of paramount importance in the chemical industry to improve both the product quality and plant safety.Small or incipient irregularities may lead to severe degradation in complex chemical processes,and the conventional process monitoring techniques cannot detect these irregularities.In this study to improve the performance of monitoring,an online multiscale fault detection approach is proposed by integrating multiscale principal component analysis(MSPCA) with cumulative sum(CUSUM) and exponentially weighted moving average(EWMA) control charts.The new Hotelling's T~2 and square prediction error(SPE) based fault detection indices are proposed to detect the incipient irregularities in the process data.The performance of the proposed fault detection methods was tested for simulated data obtained from the CSTR system and compared to that of conventional PCA and MSPCA based methods.The results demonstrate that the proposed EWMA based MSPCA fault detection method was successful in detecting the faults.Moreover,a comparative study shows that the SPEEWMA monitoring index exhibits a better performance with lower values of missed detections ranging from 0% to 0.80% and false alarms ranging from 0% to 21.20%.展开更多
Many applications of principal component analysis (PCA) can be found in dimensionality reduction. But linear PCA method is not well suitable for nonlinear chemical processes. A new PCA method based on im-proved input ...Many applications of principal component analysis (PCA) can be found in dimensionality reduction. But linear PCA method is not well suitable for nonlinear chemical processes. A new PCA method based on im-proved input training neural network (IT-NN) is proposed for the nonlinear system modelling in this paper. Mo-mentum factor and adaptive learning rate are introduced into learning algorithm to improve the training speed of IT-NN. Contrasting to the auto-associative neural network (ANN), IT-NN has less hidden layers and higher training speed. The effectiveness is illustrated through a comparison of IT-NN with linear PCA and ANN with experiments. Moreover, the IT-NN is combined with RBF neural network (RBF-NN) to model the yields of ethylene and propyl-ene in the naphtha pyrolysis system. From the illustrative example and practical application, IT-NN combined with RBF-NN is an effective method of nonlinear chemical process modelling.展开更多
The large blast furnace is essential equipment in the process of iron and steel manufacturing. Due to the complex operation process and frequent fluctuations of variables, conventional monitoring methods often bring f...The large blast furnace is essential equipment in the process of iron and steel manufacturing. Due to the complex operation process and frequent fluctuations of variables, conventional monitoring methods often bring false alarms. To address the above problem, an ensemble of greedy dynamic principal component analysis-Gaussian mixture model(EGDPCA-GMM) is proposed in this paper. First, PCA-GMM is introduced to deal with the collinearity and the non-Gaussian distribution of blast furnace data.Second, in order to explain the dynamics of data, the greedy algorithm is used to determine the extended variables and their corresponding time lags, so as to avoid introducing unnecessary noise. Then the bagging ensemble is adopted to cooperate with greedy extension to eliminate the randomness brought by the greedy algorithm and further reduce the false alarm rate(FAR) of monitoring results. Finally, the algorithm is applied to the blast furnace of a large iron and steel group in South China to verify performance.Compared with the basic algorithms, the proposed method achieves lowest FAR, while keeping missed alarm rate(MAR) remain stable.展开更多
目的:采用超高效液相色谱串联四极杆飞行时间质谱法,探讨白芍炒制前后化学成分的变化。方法:采用AgilentC18色谱柱,0. 1%甲酸水溶液-乙腈梯度洗脱,体积流量0. 3 m L/min,串联四级杆飞行时间质谱分别测定不同产地各10批生、炒白芍中的化...目的:采用超高效液相色谱串联四极杆飞行时间质谱法,探讨白芍炒制前后化学成分的变化。方法:采用AgilentC18色谱柱,0. 1%甲酸水溶液-乙腈梯度洗脱,体积流量0. 3 m L/min,串联四级杆飞行时间质谱分别测定不同产地各10批生、炒白芍中的化学成分。结果:分别在生、炒白芍中鉴定出40种化学成分。结论:通过UHPLC-Q-TOF-MS/MS技术,为分析生、炒白芍中的化学成分提供一种快速、高效的分析方法,为综合评价生白芍和炒白芍的质量提供参考。展开更多
Acanthopanax trifoliatus( L.) Merr is a common traditional Chinese herbal medicine in central and southern regions of China. It has high medicinal and edible value and mainly contains flavonoids,polysaccharides,saponi...Acanthopanax trifoliatus( L.) Merr is a common traditional Chinese herbal medicine in central and southern regions of China. It has high medicinal and edible value and mainly contains flavonoids,polysaccharides,saponins and volatile components. Its active extracts have antioxidant,anti-inflammatory,anti-fatigue,and analgesic effects. From the biological characteristics,effective chemical components,extraction methods,cultivation techniques,pharmacological effects,toxicological activities,and product development status,this paper reviewed in detail the research status of A. trifoliatus in China and abroad,to provide a scientific basis for in-depth research and development,and utilization of A. trifoliatus.展开更多
Raw material blending process is an essential part of the cement production process. The main purpose of the process is to guarantee a certain oxide composition for the raw meal at the outlet of the mill by regulating...Raw material blending process is an essential part of the cement production process. The main purpose of the process is to guarantee a certain oxide composition for the raw meal at the outlet of the mill by regulating the four raw materials. But the chemical compositions of raw materials vary from time to time, resulting in difficulties to control the oxide compositions to a predefined value. Therefore, a novel algorithm to estimate the chemical compositions of the raw materials is developed. The paper mainly consists of two parts. In model construction part, a novel constrained least square model is proposed to overcome the deviation introduced by long-term drift of the material components, and the model parameters are estimated with an online strategy. And in validation part, the approach is implemented to two examples including datasets from simulation model and the actual industrial process. The final results show the effectiveness of the proposed method.展开更多
基金Science and Technology Research and Development Project of Chengde City,Hebei Province(201706A043)Young Scholar Program of Hebei Pharmaceutical Association Hospital Pharmaceutical Research Project(2020—Hbsyxhqn0029)Public Health Service Subsidy Fund Project of Chinese Medicine Department,State Administration of Traditional Chinese Medicine(Guo Zhong Yi Gui Cai Fa[2015]No.21).
文摘[Objectives]To explore the correlation of processing technology,physical parameters and chemical components during plain stir-baking of Trichosanthis Radix.[Methods]Based on mixture uniform experiment design,the Trichosanthis Radix was prepared by plain stir-bake method.Delphi method was used to evaluate and select the highest-scoring processed product for measuring physical parameters.UV spectrophotometry was used to determine the contents of starch and polysaccharide.The correlation and linear regression model of processing technology,physical parameters and chemical components were established with the aid of SPSS 26.0[Results]After processing by plain stir-bake method,the relative density and chromaticity showed a decreasing trend in the processed products of Trichosanthis Radix,the oxidation value,hydroscopic rate and swelling decreased firstly and then increased,and pH increased firstly and then decreased.The content of total starch decreased,the content of polysaccharide increased,and there was a negative correlation between them.There was a significant positive correlation between temperature and oxidation value,swelling and hydroscopic rate,hydroscopic rate and polysaccharide,and there was a significant negative correlation between relative density and hydroscopic rate or polysaccharide,total starch and hydroscopic rate or swelling.The linear relation model between processing technology and physical parameters and chemical components was r2>0.9.[Conclusions]After processing by plain stir-bake method,the physical parameters of Trichosanthis Radix changed,and there may be mutual conversion between total starch and polysaccharides.To a certain extent,physical parameters can be used to evaluate the quality of processed products of Trichosanthis Radix.This study is expected to provide a reference for research on quality evaluation of processed products of traditional Chinese medicine.
基金Department for the technical and administrative support and the financial support from the Yayasan UTP grant(Cost centre:015LC0-132).
文摘Process monitoring techniques are of paramount importance in the chemical industry to improve both the product quality and plant safety.Small or incipient irregularities may lead to severe degradation in complex chemical processes,and the conventional process monitoring techniques cannot detect these irregularities.In this study to improve the performance of monitoring,an online multiscale fault detection approach is proposed by integrating multiscale principal component analysis(MSPCA) with cumulative sum(CUSUM) and exponentially weighted moving average(EWMA) control charts.The new Hotelling's T~2 and square prediction error(SPE) based fault detection indices are proposed to detect the incipient irregularities in the process data.The performance of the proposed fault detection methods was tested for simulated data obtained from the CSTR system and compared to that of conventional PCA and MSPCA based methods.The results demonstrate that the proposed EWMA based MSPCA fault detection method was successful in detecting the faults.Moreover,a comparative study shows that the SPEEWMA monitoring index exhibits a better performance with lower values of missed detections ranging from 0% to 0.80% and false alarms ranging from 0% to 21.20%.
基金Supported by Beijing Municipal Education Commission (No.xk100100435) and the Key Research Project of Science andTechnology from Sinopec (No.E03007).
文摘Many applications of principal component analysis (PCA) can be found in dimensionality reduction. But linear PCA method is not well suitable for nonlinear chemical processes. A new PCA method based on im-proved input training neural network (IT-NN) is proposed for the nonlinear system modelling in this paper. Mo-mentum factor and adaptive learning rate are introduced into learning algorithm to improve the training speed of IT-NN. Contrasting to the auto-associative neural network (ANN), IT-NN has less hidden layers and higher training speed. The effectiveness is illustrated through a comparison of IT-NN with linear PCA and ANN with experiments. Moreover, the IT-NN is combined with RBF neural network (RBF-NN) to model the yields of ethylene and propyl-ene in the naphtha pyrolysis system. From the illustrative example and practical application, IT-NN combined with RBF-NN is an effective method of nonlinear chemical process modelling.
基金supported by the National Natural Science Foundation of China (61903326, 61933015)。
文摘The large blast furnace is essential equipment in the process of iron and steel manufacturing. Due to the complex operation process and frequent fluctuations of variables, conventional monitoring methods often bring false alarms. To address the above problem, an ensemble of greedy dynamic principal component analysis-Gaussian mixture model(EGDPCA-GMM) is proposed in this paper. First, PCA-GMM is introduced to deal with the collinearity and the non-Gaussian distribution of blast furnace data.Second, in order to explain the dynamics of data, the greedy algorithm is used to determine the extended variables and their corresponding time lags, so as to avoid introducing unnecessary noise. Then the bagging ensemble is adopted to cooperate with greedy extension to eliminate the randomness brought by the greedy algorithm and further reduce the false alarm rate(FAR) of monitoring results. Finally, the algorithm is applied to the blast furnace of a large iron and steel group in South China to verify performance.Compared with the basic algorithms, the proposed method achieves lowest FAR, while keeping missed alarm rate(MAR) remain stable.
文摘目的:采用超高效液相色谱串联四极杆飞行时间质谱法,探讨白芍炒制前后化学成分的变化。方法:采用AgilentC18色谱柱,0. 1%甲酸水溶液-乙腈梯度洗脱,体积流量0. 3 m L/min,串联四级杆飞行时间质谱分别测定不同产地各10批生、炒白芍中的化学成分。结果:分别在生、炒白芍中鉴定出40种化学成分。结论:通过UHPLC-Q-TOF-MS/MS技术,为分析生、炒白芍中的化学成分提供一种快速、高效的分析方法,为综合评价生白芍和炒白芍的质量提供参考。
基金Supported by Joint Fund Project of Guizhou Provincial Department of Science and Technology(Qian Ke He LH Zi[2015]7716)Open Fund Project for Development Engineering Research Center of National Medicinal Plant Resources of Colleges and Universities in Guizhou Province(Qian Jiao He KY Zi[2014]227)
文摘Acanthopanax trifoliatus( L.) Merr is a common traditional Chinese herbal medicine in central and southern regions of China. It has high medicinal and edible value and mainly contains flavonoids,polysaccharides,saponins and volatile components. Its active extracts have antioxidant,anti-inflammatory,anti-fatigue,and analgesic effects. From the biological characteristics,effective chemical components,extraction methods,cultivation techniques,pharmacological effects,toxicological activities,and product development status,this paper reviewed in detail the research status of A. trifoliatus in China and abroad,to provide a scientific basis for in-depth research and development,and utilization of A. trifoliatus.
基金Supported by the National Key R&D Program of China(2016YFB0303401)the National Natural Science Foundation of China(61333010,61503138).
文摘Raw material blending process is an essential part of the cement production process. The main purpose of the process is to guarantee a certain oxide composition for the raw meal at the outlet of the mill by regulating the four raw materials. But the chemical compositions of raw materials vary from time to time, resulting in difficulties to control the oxide compositions to a predefined value. Therefore, a novel algorithm to estimate the chemical compositions of the raw materials is developed. The paper mainly consists of two parts. In model construction part, a novel constrained least square model is proposed to overcome the deviation introduced by long-term drift of the material components, and the model parameters are estimated with an online strategy. And in validation part, the approach is implemented to two examples including datasets from simulation model and the actual industrial process. The final results show the effectiveness of the proposed method.
