The partial oxidation of methane (POM) to syngas over Ni/ γ Al 2O 3 catalyst has been investigated in a fluidized bed reactor. The results showed that the isothermal operation could be achieved, and CH 4 conversion a...The partial oxidation of methane (POM) to syngas over Ni/ γ Al 2O 3 catalyst has been investigated in a fluidized bed reactor. The results showed that the isothermal operation could be achieved, and CH 4 conversion and H 2 selectivity near thermodynamic equilibrium could be obtained. It was indicated that the coke deposited on the catalyst could be reduced by using a fluidized bed reactor. The CH 4 conversion as well as CO and H 2 selectivity kept almost constantly at above 92% with time on stream, no phase transformation took place on the support, and the catalyst had no remarkable Ni loss during the reaction for 100 h.展开更多
Dynamic principal component analysis(DPCA) is an extension of conventional principal component analysis(PCA) for dealing with multivariate dynamic data serially correlated in time.Based on the fact that the measured v...Dynamic principal component analysis(DPCA) is an extension of conventional principal component analysis(PCA) for dealing with multivariate dynamic data serially correlated in time.Based on the fact that the measured variables in relation to chunk monitoring of the industrial fluidized-bed reactor are highly cross-correlated and auto-correlated, this paper presents a practical strategy for chunk monitoring by adopting DPCA in order to overcome the shortcomings of the conventional method.After introducing the basic principle of DPCA, both how to determine the time lagged length of data matrix and how to calculate the nonparametric control limits when the dynamic data are not subject to the assumption of independently identically distribution(IID) were discussed.An appropriate DPCA model based on the real data from a industrial fluidized-bed reactor was built, with parallel analysis and empirical reference distribution(ERD)method to select time lagged length and control limits, respectively.During data pretreatment, data smoothing was used to reduce noise and the serial correlations to some degree.The simulation test results showed the effectiveness of the DPCA based method.展开更多
文摘The partial oxidation of methane (POM) to syngas over Ni/ γ Al 2O 3 catalyst has been investigated in a fluidized bed reactor. The results showed that the isothermal operation could be achieved, and CH 4 conversion and H 2 selectivity near thermodynamic equilibrium could be obtained. It was indicated that the coke deposited on the catalyst could be reduced by using a fluidized bed reactor. The CH 4 conversion as well as CO and H 2 selectivity kept almost constantly at above 92% with time on stream, no phase transformation took place on the support, and the catalyst had no remarkable Ni loss during the reaction for 100 h.
文摘Dynamic principal component analysis(DPCA) is an extension of conventional principal component analysis(PCA) for dealing with multivariate dynamic data serially correlated in time.Based on the fact that the measured variables in relation to chunk monitoring of the industrial fluidized-bed reactor are highly cross-correlated and auto-correlated, this paper presents a practical strategy for chunk monitoring by adopting DPCA in order to overcome the shortcomings of the conventional method.After introducing the basic principle of DPCA, both how to determine the time lagged length of data matrix and how to calculate the nonparametric control limits when the dynamic data are not subject to the assumption of independently identically distribution(IID) were discussed.An appropriate DPCA model based on the real data from a industrial fluidized-bed reactor was built, with parallel analysis and empirical reference distribution(ERD)method to select time lagged length and control limits, respectively.During data pretreatment, data smoothing was used to reduce noise and the serial correlations to some degree.The simulation test results showed the effectiveness of the DPCA based method.
