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
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
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
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
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
Traditional principal component analysis （PCA） is a second-order method and lacks the ability to provide higherorder representations for data variables. Recently, a statistics pattern analysis （SPA） framework has ...Traditional principal component analysis （PCA） is a second-order method and lacks the ability to provide higherorder representations for data variables. Recently, a statistics pattern analysis （SPA） framework has been incorporated into PCA model to make full use of various statistics of data variables effectively. However, these methods omit the local information, which is also important for process monitoring and fault diagnosis. In this paper, a local and global statistics pattern analysis （LGSPA） method, which integrates SPA framework and locality pre- serving projections within the PCK is proposed to utilize various statistics and preserve both local and global in- formation in the observed data. For the purpose of fault detection, two monitoring indices are constructed based on the LGSPA model. In order to identify fault variables, an improved reconstruction based contribution （IRBC） plot based on LGSPA model is proposed to locate fault variables. The RBC of various statistics of original process variables to the monitoring indices is calculated with the proposed RBC method. Based on the calculated RBC of process variables＇ statistics, a new contribution of process variables is built to locate fault variables. The simula- tion results on a simple six-variable system and a continuous stirred tank reactor system demonstrate that the proposed fault diagnosis method can effectively detect fault and distinguish the fault variables from normal variables.展开更多
Sericite is mica-based natural clay that is annealed at 800 ℃ for 4 h, followed by acid activation using 3.0 mol L-1HCl at 100℃. The interaction of cesium(I), Cs(I), with sericite could provide useful data for the s...Sericite is mica-based natural clay that is annealed at 800 ℃ for 4 h, followed by acid activation using 3.0 mol L-1HCl at 100℃. The interaction of cesium(I), Cs(I), with sericite could provide useful data for the study of soil erosion or mass water movement utilizing the natural radioactive Cs. In this study sericite and activated sericite were used to assess their suitability in the attenuation of Cs from the aquatic environment under both batch and column experiments. The surface morphological studies indicated that a disordered and heterogeneous surface structure was exhibited by the activated sericite, whereas the native sericite exhibited a compact and layered structure. The Brunauer-Emmett-Teller(BET) specific surface area results indicated a significant increase in the surface area due to the activation of sericite. The batch reactor data collected for various parametric studies revealed that an increase in p H(from 2.0 to 8.0) and sorbate concentration(from 10.0 to 100.0 mg L-1) apparently favored the attenuation of Cs(I). The timedependent sorption data revealed that Cs(I) uptake was very rapid, and it achieved its saturation value within just 50 min of contact.The kinetic modeling studies indicated that the uptake of Cs(I) followed a pseudo-second-order rate equation; hence, the attenuation capacity of these solids for Cs(I) was estimated to be 0.858 and 4.353 mg g-1for sericite and activated sericite solids, respectively.The adsorption isotherm modeling data showed a reasonably good applicability of the Freundlich model than the Langmuir model.The effect of background electrolyte concentrations(0.001 to 0.1 mol L-1) of Mg(NO3)2indicated that the presence of this electrolyte could not significantly affect the percent removal of Cs(I) by activated sericite. Furthermore, the fixed-bed column reactor operations were performed to obtain the breakthrough data, which were fitted well to the Thomas non-linear equation. Therefore, the loading capacity of Cs(I) was estimated to be 1.585 mg g-1at the initial influent Cs(I) concentration of 30.0 mg L-1at p H 5.0.展开更多
In this study, a new controller for chaos synchronization is proposed. It consists of a state feedback controller and a robust control term using Legendre polynomials to compensate for uncertainties. The truncation er...In this study, a new controller for chaos synchronization is proposed. It consists of a state feedback controller and a robust control term using Legendre polynomials to compensate for uncertainties. The truncation error is also considered. Due to the orthogonal functions theorem, Legendre polynomials can approximate nonlinear functions with arbitrarily small approximation errors. As a result, they can replace fuzzy systems and neural networks to estimate and compensate for uncertainties in control systems. Legendre polynomials have fewer tuning parameters than fuzzy systems and neural networks. Thus, their tuning process is simpler. Similar to the parameters of fuzzy systems, Legendre coefficients are estimated online using the adaptation rule obtained from the stability analysis. It is assumed that the master and slave systems are the Lorenz and Chen chaotic systems, respectively. In secure communication systems, observer-based synchronization is required since only one state variable of the master system is sent through the channel. The use of observer-based synchronization to obtain other state variables is discussed. Simulation results reveal the effectiveness of the proposed approach. A comparison with a fuzzy sliding mode controller shows that the proposed controller provides a superior transient response. The problem of secure communications is explained and the controller performance in secure communications is examined.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.
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.
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.
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(61273160,61403418)the Natural Science Foundation of Shandong Province(ZR2014FL016)the Fundamental Research Funds for the Central Universities(14CX06132A)
文摘Traditional principal component analysis （PCA） is a second-order method and lacks the ability to provide higherorder representations for data variables. Recently, a statistics pattern analysis （SPA） framework has been incorporated into PCA model to make full use of various statistics of data variables effectively. However, these methods omit the local information, which is also important for process monitoring and fault diagnosis. In this paper, a local and global statistics pattern analysis （LGSPA） method, which integrates SPA framework and locality pre- serving projections within the PCK is proposed to utilize various statistics and preserve both local and global in- formation in the observed data. For the purpose of fault detection, two monitoring indices are constructed based on the LGSPA model. In order to identify fault variables, an improved reconstruction based contribution （IRBC） plot based on LGSPA model is proposed to locate fault variables. The RBC of various statistics of original process variables to the monitoring indices is calculated with the proposed RBC method. Based on the calculated RBC of process variables＇ statistics, a new contribution of process variables is built to locate fault variables. The simula- tion results on a simple six-variable system and a continuous stirred tank reactor system demonstrate that the proposed fault diagnosis method can effectively detect fault and distinguish the fault variables from normal variables.
基金Supported by the National Research Foundation(NRF)of MEST,Korea(No.2012R1A2A4A01001539)the Converging Technology Project of the Ministry of Environment,Korea(No.2013001450001)
文摘Sericite is mica-based natural clay that is annealed at 800 ℃ for 4 h, followed by acid activation using 3.0 mol L-1HCl at 100℃. The interaction of cesium(I), Cs(I), with sericite could provide useful data for the study of soil erosion or mass water movement utilizing the natural radioactive Cs. In this study sericite and activated sericite were used to assess their suitability in the attenuation of Cs from the aquatic environment under both batch and column experiments. The surface morphological studies indicated that a disordered and heterogeneous surface structure was exhibited by the activated sericite, whereas the native sericite exhibited a compact and layered structure. The Brunauer-Emmett-Teller(BET) specific surface area results indicated a significant increase in the surface area due to the activation of sericite. The batch reactor data collected for various parametric studies revealed that an increase in p H(from 2.0 to 8.0) and sorbate concentration(from 10.0 to 100.0 mg L-1) apparently favored the attenuation of Cs(I). The timedependent sorption data revealed that Cs(I) uptake was very rapid, and it achieved its saturation value within just 50 min of contact.The kinetic modeling studies indicated that the uptake of Cs(I) followed a pseudo-second-order rate equation; hence, the attenuation capacity of these solids for Cs(I) was estimated to be 0.858 and 4.353 mg g-1for sericite and activated sericite solids, respectively.The adsorption isotherm modeling data showed a reasonably good applicability of the Freundlich model than the Langmuir model.The effect of background electrolyte concentrations(0.001 to 0.1 mol L-1) of Mg(NO3)2indicated that the presence of this electrolyte could not significantly affect the percent removal of Cs(I) by activated sericite. Furthermore, the fixed-bed column reactor operations were performed to obtain the breakthrough data, which were fitted well to the Thomas non-linear equation. Therefore, the loading capacity of Cs(I) was estimated to be 1.585 mg g-1at the initial influent Cs(I) concentration of 30.0 mg L-1at p H 5.0.
文摘In this study, a new controller for chaos synchronization is proposed. It consists of a state feedback controller and a robust control term using Legendre polynomials to compensate for uncertainties. The truncation error is also considered. Due to the orthogonal functions theorem, Legendre polynomials can approximate nonlinear functions with arbitrarily small approximation errors. As a result, they can replace fuzzy systems and neural networks to estimate and compensate for uncertainties in control systems. Legendre polynomials have fewer tuning parameters than fuzzy systems and neural networks. Thus, their tuning process is simpler. Similar to the parameters of fuzzy systems, Legendre coefficients are estimated online using the adaptation rule obtained from the stability analysis. It is assumed that the master and slave systems are the Lorenz and Chen chaotic systems, respectively. In secure communication systems, observer-based synchronization is required since only one state variable of the master system is sent through the channel. The use of observer-based synchronization to obtain other state variables is discussed. Simulation results reveal the effectiveness of the proposed approach. A comparison with a fuzzy sliding mode controller shows that the proposed controller provides a superior transient response. The problem of secure communications is explained and the controller performance in secure communications is examined.
