科创中国

Eddy current pulsed thermography(ECPT) is an emerging Non-destructive testing and evaluation(NDT & E) technique, which uses hybrid eddy current and thermography NDT & E techniques that enhances the detectability from their compensation. Currently, this technique is limited by the manual selection of proper contrast frames and the issue of improving the efficiency of defect detection of complex structure samples remains a challenge. In order to select a specific frame from transient thermal image sequences to maximize the contrast of thermal variation and defect pattern from complex structure samples, an energy driven approach to compute the coefficient energy of wavelet transform is proposed which has the potential of automatically selecting both optimal transient frame and spatial scale for defect detection using ECPT. According to analysis of the variation of different frequency component and the comparison study of the detection performance of different scale and wavelets, the frame at the end of heating phase is automatically selected as an optimal transient frame for defect detection. In addition, the detection capabilities of the complex structure samples can be enhanced through proper spatial scale and wavelet selection. The proposed method has successfully been applied to low speed impact damage detection of carbon fibre reinforced polymer(CFRP) composite as well as providing the guidance to improve the detectability of ECPT technique.

对医学图像进行去噪、增强可提高信息的利用率.传统的小波增强算法应用于医学图像时处理效果一般,针对该问题提出了一种基于二进小波变换的图像增强算法.首先,对图像进行多级小波分解,得到低频信息(尺度系数)和多个层次的高频信息(小波系数);然后,对图像的高频信息采用双闽值增强函数进行处理,同时,对图像的低频信息采用单阈值增强函数进行处理;最后,利用得到的低频信息和高频信息进行小波反变换.实验表明,该方法无论是增强效果还是抗噪性能都明显优于传统的图像增强算法,同时对医学图像具有较好的处理效果.