航空科学技术2025，Vol.36Issue(1)：1-10,10.DOI:10.19452/j.issn1007-5453.2025.01.001
基于深度神经网络的航炮炮振载荷识别
Dynamic Load Identification of Gun Bay Based on Deep Neural Network
摘要
Abstract
In the design of aircraft structures,it is necessary to consider the anti-gun vibration design of aircraft structures and to determine the dynamic load when the aircraft machine gun is firing.In comparison with the traditional dynamic load recognition method,deep neural networks supported by deep learning technology have a strong fitting ability and a broad application prospect in dynamic load recognition.This paper presents a vibration load identification method for artillery hands,established from the perspective of deep neural network application.A simplified artillery bay model with similar structural dynamics of a certain type of gun bay was taken as the research object to simulate the dynamic load environment of the complex waveform impact load and the simplified gun bay experimental model.From the perspective of signal processing,the damped dynamic system is equivalent to a finite-length impulse response system.The corresponding feature signals are extracted,and impact dynamic load recognition experiments are carried out on the simplified gun bay model by means of the LSTM neural network.The application performance of the method is examining in terms of robustness.Finally,the method established in this article was used to identify the shock wave load experienced by a certain type of gun compartment in a real gun vibration load environment,verifying the applicability of the method in practical application scenarios and providing new ideas and technical approaches for the identification of complex impact loads such as gun vibration loads.关键词
深度学习/载荷识别/振动分析/特征提取/鲁棒性Key words
deep learning/load identification/vibration analysis/feature extraction/robustness分类
航空航天引用本文复制引用
黄虎,刘翛然,王用岩,杨建,杨智春..基于深度神经网络的航炮炮振载荷识别[J].航空科学技术,2025,36(1):1-10,10.基金项目
航空科学基金(20220015053002) Aeronautical Science Foundation of China(20220015053002) （20220015053002）
