摘要
分析了影响耳片结构疲劳状态的主要因素 ,把这些因素归纳为静强度、抗疲劳设计与制造以及使用过程中的疲劳积累三大类。采用多层B P人工神经网络结构 ,构造了能映射各因素与总体效果影响的人工神经网络系统。该系统采用了一个主网络和两个子网络的结构 ,降低了状态空间的维数 ,提高了运算速度 ,较好地反映了实际结构的疲劳失效机理 。
Artificial neural network method is introduced to diagnose fatigue damage status of the lugs in the aircraft. The factors to influence the fatigue damage have been analyzed and divided into three categories: static strength, anti fatigue design and accumulative fatigue damage. A system has been set up through B P artificial neural network to show the effect of these factors to the fatigue damage status. In order to reduce the dimension of status space, the system has one main network and two subsequent networks.
出处
《理化检验（物理分册）》
CAS
2001年第11期477-479,共3页
Physical Testing and Chemical Analysis(Part A:Physical Testing)
基金
航空科学基金资助项目 ( 93G5 2 132 )
