基于小波的蜂窝板面超高速撞击声发射信号损伤特征提取

发布时间：2018-02-26 16:20

本文关键词： 超高速撞击声发射小波变换蜂窝板损伤模式 Kruskal-Wallis检验　出处：《爆炸与冲击》2017年05期 　论文类型：期刊论文

【摘要】：为了通过超高速撞击声发射信号识别蜂窝结构受空间碎片撞击后的损伤状态,提出一种基于小波的损伤特征提取方法。采用超高速撞击声发射技术,以铝合金蜂窝板为研究对象,通过超高速撞击实验获取实验信号。分析超高速撞击声发射信号的时频特征及板波模态等特征,采用Daubechies小波变换将信号中模态分离,根据小波系数计算各尺度小波能量分数及小波能量熵特征,分析各特征参数与损伤间的关系,并通过Kruskal-Wallis检验方法验证各特征值对损伤识别的贡献。结果表明:小波能量分数和小波能量熵具有一定的损伤模式分类能力;250kHz以上的小波能量分数具有良好的损伤模式分类能力;非超声部分的低频信号对损伤识别存在干扰。
[Abstract]:In order to identify the damage state of honeycomb structure after space debris impact by hypervelocity impact acoustic emission signal, a wavelet based damage feature extraction method is proposed. Taking aluminum alloy honeycomb plate as the research object, the experimental signals are obtained by hypervelocity impact experiments. The time-frequency characteristics and plate wave modes of the ultra-high velocity impact acoustic emission signals are analyzed. The Daubechies wavelet transform is used to separate the modes in the signals. According to wavelet coefficients, wavelet energy fraction and wavelet energy entropy characteristics are calculated, and the relationship between each characteristic parameter and damage is analyzed. The results show that wavelet energy fraction and wavelet energy entropy have a certain ability of damage pattern classification. Wavelet energy fraction above 250 kHz has good damage pattern classification ability. The low frequency signal of non-ultrasonic part interferes with damage identification.
【作者单位】：哈尔滨工业大学空间碎片高速撞击研究中心;
【基金】：空间碎片专项十二五项目中央高校基本科研业务费专项项目(HIT.NSRIF.2015029)
【分类号】：V415;V528

【相似文献】