基于小波分形的飞行器结构系统早期故障识别  

EARLY FAULT IDENTIFICATION OF AIRCRAFT STRUCTURE SYSTEM BASED ON WAVELET AND FRACTION

作　　者：王仲生[1] 何红[1] 

机构地区：[1]西北工业大学航空学院,西安710072

出　　处：《机械强度》2008年第6期893-896,共4页Journal of Mechanical Strength

基　　金：国家自然科学基金(60472116;50675178);航空科学基金(03I53068)资助项目~~

摘　　要：在对飞行器结构系统早期故障特点进行分析的基础上,将小波分析与分形理论相结合,提出利用小波分析提取早期故障特征信号和根据分形关联维数对飞行器结构系统早期故障进行快速识别的方法。文中对飞行器结构系统早期故障奇异特征的提取、关联维数的计算、早期故障的识别等进行分析和研究,并给出具体算法模型和实施步骤。结果表明,小波分析能有效地提取飞行器结构系统早期故障奇异特征信号,根据局部斜率和嵌入维数得到的关联维数,能快速识别出早期故障。In order to fast identify the early fault of the aircraft structure system, a method is presented to combine of wavelet with fractal..It is based on analysis of early fault on the aircraft structure system, and singular characteristic signals of early fault are extracted by wavelet anafysis and early fault of the aircraft structure system can be identified by the fractal correlation dimension. At the same time, the extraction of early fault singular eigenvalue, the calculation of correlation dimension and the identification of early fault on the aircraft structure system are analyzed, and the algorithm and implement step are given, too. Results showed that singular characteristic signal of the aircraft structure system can be effectively extracted by wavelet analysis and the early fault can be fast identified by calculation of the fractal correlation dimension. It provides an effective method to improve identification ability of early fault on the aircraft structure system to combine wavelet analysis with fractal geometry.

关 键 词：飞行器 结构系统 小波与分形 早期故障识别 

分 类 号：V214.1[航空宇航科学与技术—航空宇航推进理论与工程] TP206.3[自动化与计算机技术—检测技术与自动化装置]