TY - JOUR
T1 - 基于改进Kriging模型的舰载机着舰下沉速度影响性分析研究
AU - Xue, Xiaofeng
AU - Wang, Yuanzhuo
AU - Lu, Cheng
N1 - Publisher Copyright:
© 2019 Journal of Northwestern Polytechnical University.
PY - 2019/4/1
Y1 - 2019/4/1
N2 - The sinking velocity of carrier-based aircraft is an important input for landing gear design, and has a great influence on the weight of the landing gear and airframe structure. Aiming at exploring the effect of the various related landing parameters on the sinking velocity for carrier-based aircraft at the actual service environment, and based on F/A-18A measured landing data, the correlation degree between 15 landing parameters and sinking velocity is analyzed by partial correlation analysis method in multivariate statistics. The results show that the aircraft instantaneous gliding angle and deck pitch angle are highly correlated with the sinking velocity, the approach velocity and the engaging velocity are moderately correlated with the sinking velocity. The above four parameters are used as the independent variables, an improved Kriging surrogate model for the sinking velocity of F/A-18A aircraft is established, and Genetic algorithm is used to optimize the undetermined coefficients of correlation functions. The complex correlation coefficient of the sinking velocity predicted by the proposed model is 0.981, the average relative error is 1.813% and the maximum relative error is 6.771%. And comparing the empirical formula with the ordinary Kriging model, the precision index is the best. The proposed model provides the best prediction results. The improved Kriging surrogate model and the results obtained in this paper can provide a basis for studying the sinking velocity and controlling landing attitude for similar models carrier-based aircraft.
AB - The sinking velocity of carrier-based aircraft is an important input for landing gear design, and has a great influence on the weight of the landing gear and airframe structure. Aiming at exploring the effect of the various related landing parameters on the sinking velocity for carrier-based aircraft at the actual service environment, and based on F/A-18A measured landing data, the correlation degree between 15 landing parameters and sinking velocity is analyzed by partial correlation analysis method in multivariate statistics. The results show that the aircraft instantaneous gliding angle and deck pitch angle are highly correlated with the sinking velocity, the approach velocity and the engaging velocity are moderately correlated with the sinking velocity. The above four parameters are used as the independent variables, an improved Kriging surrogate model for the sinking velocity of F/A-18A aircraft is established, and Genetic algorithm is used to optimize the undetermined coefficients of correlation functions. The complex correlation coefficient of the sinking velocity predicted by the proposed model is 0.981, the average relative error is 1.813% and the maximum relative error is 6.771%. And comparing the empirical formula with the ordinary Kriging model, the precision index is the best. The proposed model provides the best prediction results. The improved Kriging surrogate model and the results obtained in this paper can provide a basis for studying the sinking velocity and controlling landing attitude for similar models carrier-based aircraft.
KW - Carrier-based aircraft
KW - Compaction-analysis
KW - Correlation analysis
KW - Genetic algorithm
KW - Kriging model
KW - Multivariate statistics
KW - Sinking velocity
UR - http://www.scopus.com/inward/record.url?scp=85065830438&partnerID=8YFLogxK
U2 - 10.1051/jnwpu/20193720218
DO - 10.1051/jnwpu/20193720218
M3 - 文章
AN - SCOPUS:85065830438
SN - 1000-2758
VL - 37
SP - 218
EP - 224
JO - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
JF - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
IS - 2
ER -