Textile-reinforced composites,due to their excellent highstrength-to-low-mass ratio, provide promising alternatives to conventional structural materials in many high-tech sectors. 3D braided composites are a kind of a...Textile-reinforced composites,due to their excellent highstrength-to-low-mass ratio, provide promising alternatives to conventional structural materials in many high-tech sectors. 3D braided composites are a kind of advanced composites reinforced with 3D braided fabrics; the complex nature of 3D braided composites makes the evaluation of the quality of the product very difficult. In this investigation,a defect recognition platform for 3D braided composites evaluation was constructed based on dual-tree complex wavelet packet transform( DT-CWPT) and backpropagation( BP) neural networks. The defects in 3D braided composite materials were probed and detected by an ultrasonic sensing system. DT-CWPT method was used to analyze the ultrasonic scanning pulse signals,and the feature vectors of these signals were extracted into the BP neural networks as samples. The type of defects was identified and recognized with the characteristic ultrasonic wave spectra. The position of defects for the test samples can be determined at the same time. This method would have great potential to evaluate the quality of 3D braided composites.展开更多
信号在毫米波段的快速衰减是影响毫米波雷达测距范围的重要因素之一。为了增加基于线性调频连续波(linear frequency modulation continuous wave,LFMCW)技术的毫米波雷达的有效作用距离,采用小波包分析与快速傅里叶变换相结合的方法对...信号在毫米波段的快速衰减是影响毫米波雷达测距范围的重要因素之一。为了增加基于线性调频连续波(linear frequency modulation continuous wave,LFMCW)技术的毫米波雷达的有效作用距离,采用小波包分析与快速傅里叶变换相结合的方法对雷达目标进行测距。给出了该方法的实现步骤,并在1GHz带宽的24GHz LFMCW雷达实验平台上验证了该方法的有效性。实验结果表明,与经典的差拍-傅里叶测距方法相比,本文方法可以将实验雷达的有效作用范围从1～30m扩大至1～60m。展开更多
基金National Natural Science Foundation of China(No.51303131)
文摘Textile-reinforced composites,due to their excellent highstrength-to-low-mass ratio, provide promising alternatives to conventional structural materials in many high-tech sectors. 3D braided composites are a kind of advanced composites reinforced with 3D braided fabrics; the complex nature of 3D braided composites makes the evaluation of the quality of the product very difficult. In this investigation,a defect recognition platform for 3D braided composites evaluation was constructed based on dual-tree complex wavelet packet transform( DT-CWPT) and backpropagation( BP) neural networks. The defects in 3D braided composite materials were probed and detected by an ultrasonic sensing system. DT-CWPT method was used to analyze the ultrasonic scanning pulse signals,and the feature vectors of these signals were extracted into the BP neural networks as samples. The type of defects was identified and recognized with the characteristic ultrasonic wave spectra. The position of defects for the test samples can be determined at the same time. This method would have great potential to evaluate the quality of 3D braided composites.
