Aero engines are key power components that provide thrust for the aircraft.The cerme turbine disc allows the new-generation domestic fighter aircraft to increase the overall thrust of the aero engine.Quantifying coati...Aero engines are key power components that provide thrust for the aircraft.The cerme turbine disc allows the new-generation domestic fighter aircraft to increase the overall thrust of the aero engine.Quantifying coatings and analyzing the stress on the teeth play critical roles in improving the turbine disc’s performance,which are two issues must be solved urgently.First,this work pro poses a quantitative analysis algorithm to conduct the Three-Dimensional(3D)distribution informa tion mining of the extracted coatings.Then,it proposes an Industrial Computed Laminography(ICL)reconstruction algorithm for non-destructively reconstructing the turbine disc’s high-quality3D morphological actual feature.Finally,a Finite Element Analysis(FEA)under the ultimate thrus is conducted on ICL reconstruction to verify the working status of the new-generation aero-engine turbine disc.The results show that the proposed quantitative analysis algorithm digitizes the aggre gated conditions of the coating with a statistically normalized Z_(1)value of–2.15 and a confidence leve higher than 95%.Three image-quality quantitative indicators:Peak Signal-to-Noise Ratio(PSNR)Structural Similarity Index Measure(SSIM),and Normalized Mean Square Distance(NMSD)of the proposed ICL reconstruction algorithm on turbine disc laminographic image are 26.45,0.88,and 0.73respectively,which are better than other algorithms.The mechanical analysis of ICL more realisti cally reflects the stress and deformation than that of 3D modeling.This work provides new ideas for the iterative research of new-generation aero-engine turbine discs.展开更多
In this work, two chemometrics methods are applied for the modeling and prediction of electrophoretic mobilities of some organic and inorganic compounds. The successive projection algorithm, feature selection （SPA） ...In this work, two chemometrics methods are applied for the modeling and prediction of electrophoretic mobilities of some organic and inorganic compounds. The successive projection algorithm, feature selection （SPA） strategy, is used as the descriptor selection and model development method. Then, the support vector machine （SVM） and multiple linear regression （MLR） model are utilized to construct the non-linear and linear quantitative structure-property relationship models. The results obtained using the SVM model are compared with those obtained using MLR reveal that the SVM model is of much better predictive value than the MLR one. The root-mean-square errors for the training set and the test set for the SVM model were 0.1911 and 0.2569, respectively, while by the MLR model, they were 0.4908 and 0.6494, respectively. The results show that the SVM model drastically enhances the ability of prediction in QSPR studies and is superior to the MLR model.展开更多
基金supported by the National Natural Science Foundation of China(No.51975026)。
文摘Aero engines are key power components that provide thrust for the aircraft.The cerme turbine disc allows the new-generation domestic fighter aircraft to increase the overall thrust of the aero engine.Quantifying coatings and analyzing the stress on the teeth play critical roles in improving the turbine disc’s performance,which are two issues must be solved urgently.First,this work pro poses a quantitative analysis algorithm to conduct the Three-Dimensional(3D)distribution informa tion mining of the extracted coatings.Then,it proposes an Industrial Computed Laminography(ICL)reconstruction algorithm for non-destructively reconstructing the turbine disc’s high-quality3D morphological actual feature.Finally,a Finite Element Analysis(FEA)under the ultimate thrus is conducted on ICL reconstruction to verify the working status of the new-generation aero-engine turbine disc.The results show that the proposed quantitative analysis algorithm digitizes the aggre gated conditions of the coating with a statistically normalized Z_(1)value of–2.15 and a confidence leve higher than 95%.Three image-quality quantitative indicators:Peak Signal-to-Noise Ratio(PSNR)Structural Similarity Index Measure(SSIM),and Normalized Mean Square Distance(NMSD)of the proposed ICL reconstruction algorithm on turbine disc laminographic image are 26.45,0.88,and 0.73respectively,which are better than other algorithms.The mechanical analysis of ICL more realisti cally reflects the stress and deformation than that of 3D modeling.This work provides new ideas for the iterative research of new-generation aero-engine turbine discs.
文摘In this work, two chemometrics methods are applied for the modeling and prediction of electrophoretic mobilities of some organic and inorganic compounds. The successive projection algorithm, feature selection （SPA） strategy, is used as the descriptor selection and model development method. Then, the support vector machine （SVM） and multiple linear regression （MLR） model are utilized to construct the non-linear and linear quantitative structure-property relationship models. The results obtained using the SVM model are compared with those obtained using MLR reveal that the SVM model is of much better predictive value than the MLR one. The root-mean-square errors for the training set and the test set for the SVM model were 0.1911 and 0.2569, respectively, while by the MLR model, they were 0.4908 and 0.6494, respectively. The results show that the SVM model drastically enhances the ability of prediction in QSPR studies and is superior to the MLR model.
