High-temperature thin-film thermocouples(TFTCs)have attracted significant attention in the aerospace and steel metallurgy industry.However,previous studies on TFTCs have primarily focused on the two-dimensional planar...High-temperature thin-film thermocouples(TFTCs)have attracted significant attention in the aerospace and steel metallurgy industry.However,previous studies on TFTCs have primarily focused on the two-dimensional planar-type,whose thermal sensitive area has to be perpendicular to the test environment,and therefore affects the thermal fluids pattern or loses accuracy.In order to address this problem,recent studies have developed three-dimensional probe-type TFTCs,which can be set parallel to the test environment.Nevertheless,the probe-type TFTCs are limited by their measurement threshold and poor stability at high temperatures.To address these issues,in this study,we propose a novel probe-type TFTC with a sandwich structure.The sensitive layer is compounded with indium oxide doped zinc oxide and fabricated using screen-printing technology.With the protection of sandwich structure on electrode film,the sensor demonstrates robust high-temperature stability,enabling continuous working at 1200℃ above 5 h with a low drift rate of 2.3℃·h^(−1).This sensor exhibits a high repeatability of 99.3% when measuring a wide range of temperatures,which is beyond the most existing probe-type TFTCs reported in the literature.With its excellent high-temperature performance,this temperature sensor holds immense potentials for enhancing equipment safety in the aerospace engineering and ensuring product quality in the steel metallurgy industry.展开更多
Extended Kalman Filter(EKF)algorithm is widely used in parameter estimation for nonlinear systems.The estimation precision is sensitively dependent on EKF’s initial state covariance matrix and state noise matrix.The ...Extended Kalman Filter(EKF)algorithm is widely used in parameter estimation for nonlinear systems.The estimation precision is sensitively dependent on EKF’s initial state covariance matrix and state noise matrix.The grid optimization method is always used to find proper initial matrix for off-line estimation.However,the grid method has the draw back being time consuming hence,coarse grid followed by a fine grid method is adopted.To further improve efficiency without the loss of estimation accuracy,we propose a genetic algorithm for the coarse grid optimization in this paper.It is recognized that the crossover rate and mutation rate are the main influencing factors for the performance of the genetic algorithm,so sensitivity experiments for these two factors are carried out and a set of genetic algorithm parameters with good adaptability were selected by testing with several gyros’experimental data.Experimental results show that the proposed algorithm has higher efficiency and better estimation accuracy than the traversing grid algorithm.展开更多
基金supports from the National Key Research and Development Program of China(2022YFB3207502).
文摘High-temperature thin-film thermocouples(TFTCs)have attracted significant attention in the aerospace and steel metallurgy industry.However,previous studies on TFTCs have primarily focused on the two-dimensional planar-type,whose thermal sensitive area has to be perpendicular to the test environment,and therefore affects the thermal fluids pattern or loses accuracy.In order to address this problem,recent studies have developed three-dimensional probe-type TFTCs,which can be set parallel to the test environment.Nevertheless,the probe-type TFTCs are limited by their measurement threshold and poor stability at high temperatures.To address these issues,in this study,we propose a novel probe-type TFTC with a sandwich structure.The sensitive layer is compounded with indium oxide doped zinc oxide and fabricated using screen-printing technology.With the protection of sandwich structure on electrode film,the sensor demonstrates robust high-temperature stability,enabling continuous working at 1200℃ above 5 h with a low drift rate of 2.3℃·h^(−1).This sensor exhibits a high repeatability of 99.3% when measuring a wide range of temperatures,which is beyond the most existing probe-type TFTCs reported in the literature.With its excellent high-temperature performance,this temperature sensor holds immense potentials for enhancing equipment safety in the aerospace engineering and ensuring product quality in the steel metallurgy industry.
文摘Extended Kalman Filter(EKF)algorithm is widely used in parameter estimation for nonlinear systems.The estimation precision is sensitively dependent on EKF’s initial state covariance matrix and state noise matrix.The grid optimization method is always used to find proper initial matrix for off-line estimation.However,the grid method has the draw back being time consuming hence,coarse grid followed by a fine grid method is adopted.To further improve efficiency without the loss of estimation accuracy,we propose a genetic algorithm for the coarse grid optimization in this paper.It is recognized that the crossover rate and mutation rate are the main influencing factors for the performance of the genetic algorithm,so sensitivity experiments for these two factors are carried out and a set of genetic algorithm parameters with good adaptability were selected by testing with several gyros’experimental data.Experimental results show that the proposed algorithm has higher efficiency and better estimation accuracy than the traversing grid algorithm.
