首页|A novel reliability analysis method for engineering problems:Expanded learning intelligent back propagation neural network

A novel reliability analysis method for engineering problems:Expanded learning intelligent back propagation neural network

扫码查看
Estimating the failure probability of highly reliable structures in practice engineering,such as aeronautical components,is challenging because of the strong-coupling and the small failure probability traits.In this paper,an Expanded Learning Intelligent Back Propagation(EL-IBP)neu-ral network approach is developed:firstly,to accurately characterize the engineering response cou-pling relationships,a high-fidelity Intelligent-optimized Back Propagation(IBP)neural network metamodel is developed;furthermore,to elevate the analysis efficacy for small failure assessment,a novel expanded learning strategy for adaptive IBP metamodeling is proposed.Three numerical examples and one typical practice engineering case are analyzed,to validate the effectiveness and engineering application value of the proposed method.Methods comparison shows that the EL-IBP method holds significant efficiency and accuracy superiorities in engineering issues.The current study may shed a light on pushing the adaptive metamodeling technique deeply toward complex engineering reliability analysis.

Reliability analysisBack propagation neural networkAdaptive metamodelVariance expansionSmall failure probabilityStrong-coupling

Ying HUANG、Jianguo ZHANG、Xiaoduo FAN、Qi GONG、Lukai SONG

展开 >

School of Reliability and Systems Engineering,Beihang University,Beijing 100191,China

AVIC Aero Polytechnology Establishment,Beijing 100028,China

Department of Mechanical Engineering,The Hong Kong Polytechnic University,Hong Kong 100872,China

Research Institute of Aero-Engine,Beihang University,Beijing 102206,China

展开 >

2024

中国航空学报(英文版)
中国航空学会

中国航空学报(英文版)

CSTPCDEI
影响因子:0.847
ISSN:1000-9361
年,卷(期):2024.37(12)