Locality preserving projection (LPP) is a newly emerging fault detection method which can discover local manifold structure of a data set to be analyzed, but its linear assumption may lead to monitoring performance de...Locality preserving projection (LPP) is a newly emerging fault detection method which can discover local manifold structure of a data set to be analyzed, but its linear assumption may lead to monitoring performance degradation for complicated nonlinear industrial processes. In this paper, an improved LPP method, referred to as sparse kernel locality preserving projection (SKLPP) is proposed for nonlinear process fault detection. Based on the LPP model, kernel trick is applied to construct nonlinear kernel model. Furthermore, for reducing the computational complexity of kernel model, feature samples selection technique is adopted to make the kernel LPP model sparse. Lastly, two monitoring statistics of SKLPP model are built to detect process faults. Simulations on a continuous stirred tank reactor (CSTR) system show that SKLPP is more effective than LPP in terms of fault detection performance.展开更多
Many chemical processes can be modeled as Wiener models, which consist of a linear dynamic subsystem followed by a static nonlinear block. In this paper, an effective discrete-time adaptive control method is proposed ...Many chemical processes can be modeled as Wiener models, which consist of a linear dynamic subsystem followed by a static nonlinear block. In this paper, an effective discrete-time adaptive control method is proposed for Wiener nonlinear systems with uncertainties. The parameterization model is derived based on the inverse of the nonlinear function block. The adaptive control method is motivated by self-tuning control and is derived from a modified Clarke criterion function, which considers both tracking properties and control efforts. The uncertain parameters are updated by a recursive least squares algorithm and the control law exhibits an explicit form. The closed-loop system stability properties are discussed. To demonstrate the effectiveness of the obtained results, two groups of simulation examples including an application to composition control in a continuously stirred tank reactor(CSTR) system are studied.展开更多
A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the...A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.展开更多
The mathematic model of combined converter with two different flow modes of gas-cooled reactor was established. The effects of gas flow mode in gas-cooled reactor on combined converter was investigated with the yield ...The mathematic model of combined converter with two different flow modes of gas-cooled reactor was established. The effects of gas flow mode in gas-cooled reactor on combined converter was investigated with the yield of methanol was 1 400 kt/a. The results show that if the flow mode of the cooling pipe gas and the catalytic bed gas change from countercurrent to concurrent, the catalytic bed temperature distribution does not fit the most optimum temperature curve of reversible exothermic reaction and the heat duty of heat changer in whole process increased seriously, which means that there is much more equipment investment and more operating cost. The gas flow mode of gas-cooled reactor affects the methanol yield slightly. There- fore, the countercurrent gas flow mode of gas-cooled reactor is more lucrative in the combined converter process.展开更多
S. platensis （Spirulinaplatensis） algae were grown in batch reactors at 30 ± 1℃ with a continuous illumination of 50 ±2 μmol·m^-2·s^-1 using different growth media and air flow rates. A modifie...S. platensis （Spirulinaplatensis） algae were grown in batch reactors at 30 ± 1℃ with a continuous illumination of 50 ±2 μmol·m^-2·s^-1 using different growth media and air flow rates. A modified Gompertz kinetic model was applied to estimate the maximum concentration of algae and the growth rate at different conditions. A peak cell productivity of 21.91 mg·L^-1·day^-1 （dry biomass） was determined using commercial nutrient media （F/2, part A and part B） and modified Zarrouk medium at an air flow rate of 3 L·L^-1·min^-1. Using the commercial media at high concentrations yielded high biomass concentrations. The results of the modified Gompertz kinetic model indicated that the highest growth rate was 0.118 g·L^-1·day^-1. This growth rate was determined for S. platensis cultivated using 0.399 mL·L^-1 of the commercial media. Response surface methodology was applied to optimize the parameters （temperature, pH, and chitosan dose） that affect the efficiency of the flocculation of S. platensis. An optimum flocculation of 98.7% was determined at a pH, temperature, and chitosan dose of 5.5, 30℃, and 75 mL·L^-1, respectively.展开更多
The Daya Bay Reactor Neutrino Experiment is to measure the smallest mixing angle θ13.The experiment contains three major experiment halls,Daya Bay near site,Linao near site and far site,and two major kinds of detecto...The Daya Bay Reactor Neutrino Experiment is to measure the smallest mixing angle θ13.The experiment contains three major experiment halls,Daya Bay near site,Linao near site and far site,and two major kinds of detectors,antineutrino detector which is to detect the antineutrinos by the inverse beta-decay reaction in Gd-LS,and muon detector which is to study and reject cosmogenic backgrounds.The goal of the detector control system(DCS)is to operate and detect the detectors and keep them running in safety.In consideration of the limited fund of this system and manpower of working on this system,the LabVIEW is chosen to develop the detector control system.The architecture of DCS adopts the distributed data management which is based on client-server model.The server part is to detect and operate parameters from hardware,save data to database and release data to clients,the client is to receive data from the server.The detector control system contains three parts:the hardware part,the local control system and the global control part.The local control system includes high voltage supply system,low voltage supply system,VME crate system,temperature and humidity system,gas pressure system,and so on.展开更多
基金Supported by the National Natural Science Foundation of China （61273160）, the Natural Science Foundation of Shandong Province of China （ZR2011FM014） and the Fundamental Research Funds for the Central Universities （10CX04046A）.
文摘Locality preserving projection (LPP) is a newly emerging fault detection method which can discover local manifold structure of a data set to be analyzed, but its linear assumption may lead to monitoring performance degradation for complicated nonlinear industrial processes. In this paper, an improved LPP method, referred to as sparse kernel locality preserving projection (SKLPP) is proposed for nonlinear process fault detection. Based on the LPP model, kernel trick is applied to construct nonlinear kernel model. Furthermore, for reducing the computational complexity of kernel model, feature samples selection technique is adopted to make the kernel LPP model sparse. Lastly, two monitoring statistics of SKLPP model are built to detect process faults. Simulations on a continuous stirred tank reactor (CSTR) system show that SKLPP is more effective than LPP in terms of fault detection performance.
基金Supported by the National Natural Science Foundation of China(61473072)
文摘Many chemical processes can be modeled as Wiener models, which consist of a linear dynamic subsystem followed by a static nonlinear block. In this paper, an effective discrete-time adaptive control method is proposed for Wiener nonlinear systems with uncertainties. The parameterization model is derived based on the inverse of the nonlinear function block. The adaptive control method is motivated by self-tuning control and is derived from a modified Clarke criterion function, which considers both tracking properties and control efforts. The uncertain parameters are updated by a recursive least squares algorithm and the control law exhibits an explicit form. The closed-loop system stability properties are discussed. To demonstrate the effectiveness of the obtained results, two groups of simulation examples including an application to composition control in a continuously stirred tank reactor(CSTR) system are studied.
基金Supported by the National Natural Science Foundation of China(61374140)Shanghai Pujiang Program(12PJ1402200)
文摘A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.
文摘The mathematic model of combined converter with two different flow modes of gas-cooled reactor was established. The effects of gas flow mode in gas-cooled reactor on combined converter was investigated with the yield of methanol was 1 400 kt/a. The results show that if the flow mode of the cooling pipe gas and the catalytic bed gas change from countercurrent to concurrent, the catalytic bed temperature distribution does not fit the most optimum temperature curve of reversible exothermic reaction and the heat duty of heat changer in whole process increased seriously, which means that there is much more equipment investment and more operating cost. The gas flow mode of gas-cooled reactor affects the methanol yield slightly. There- fore, the countercurrent gas flow mode of gas-cooled reactor is more lucrative in the combined converter process.
文摘S. platensis （Spirulinaplatensis） algae were grown in batch reactors at 30 ± 1℃ with a continuous illumination of 50 ±2 μmol·m^-2·s^-1 using different growth media and air flow rates. A modified Gompertz kinetic model was applied to estimate the maximum concentration of algae and the growth rate at different conditions. A peak cell productivity of 21.91 mg·L^-1·day^-1 （dry biomass） was determined using commercial nutrient media （F/2, part A and part B） and modified Zarrouk medium at an air flow rate of 3 L·L^-1·min^-1. Using the commercial media at high concentrations yielded high biomass concentrations. The results of the modified Gompertz kinetic model indicated that the highest growth rate was 0.118 g·L^-1·day^-1. This growth rate was determined for S. platensis cultivated using 0.399 mL·L^-1 of the commercial media. Response surface methodology was applied to optimize the parameters （temperature, pH, and chitosan dose） that affect the efficiency of the flocculation of S. platensis. An optimum flocculation of 98.7% was determined at a pH, temperature, and chitosan dose of 5.5, 30℃, and 75 mL·L^-1, respectively.
文摘The Daya Bay Reactor Neutrino Experiment is to measure the smallest mixing angle θ13.The experiment contains three major experiment halls,Daya Bay near site,Linao near site and far site,and two major kinds of detectors,antineutrino detector which is to detect the antineutrinos by the inverse beta-decay reaction in Gd-LS,and muon detector which is to study and reject cosmogenic backgrounds.The goal of the detector control system(DCS)is to operate and detect the detectors and keep them running in safety.In consideration of the limited fund of this system and manpower of working on this system,the LabVIEW is chosen to develop the detector control system.The architecture of DCS adopts the distributed data management which is based on client-server model.The server part is to detect and operate parameters from hardware,save data to database and release data to clients,the client is to receive data from the server.The detector control system contains three parts:the hardware part,the local control system and the global control part.The local control system includes high voltage supply system,low voltage supply system,VME crate system,temperature and humidity system,gas pressure system,and so on.
