Wang Fei, Wang Yonghui, Liu Junyan, Wang Yang
Opt Express. 2018 Aug 20;26(17):21403-21417. doi: 10.1364/OE.26.021403.
In this paper, we demonstrated a novel thermal-wave radar imaging approach with use of a dual-directional (down then up) chirp (or linear frequency modulation, LFM) modulated laser as an external excitation source and signal processing by Fractional Fourier transform (FrFT), which can enhance the defect detectability and extend the depth-resolution dynamic range. The thermal-wave signal was reconstructed by use of dimensionless normalization scaling (DNS) method, and furthermore, it explored the centralized feature of energy spectral density in FrFT domain. The amplitude and phase angle at the peak energy density in FrFT domain were extracted to form the corresponding image and used for the defect detection and identification. The experiments were carried over a carbon fiber reinforced polymer (CFRP) specimen with the artificial flat bottom holes (FBHs) to validate the defect detection capability using FrFT based enhanced TWRI compared to the FFT based TWRI or conventional lock-in thermography (LIT) by taking the defect signal to noise ratio (SNR) into account.
在本文中，我们展示了一种新颖的热波雷达成像方法，该方法使用双向（先向下然后向上）啁啾（或线性调频，LFM）调制激光作为外部激发源，并通过分数傅里叶变换（FrFT）进行信号处理，这可以提高缺陷检测能力并扩展深度分辨率动态范围。利用无量纲归一化缩放（DNS）方法重建热波信号，此外，还探索了FrFT域中能量谱密度的集中特征。提取FrFT域中峰值能量密度处的幅度和相位角以形成相应图像，并用于缺陷检测和识别。通过碳纤维增强聚合物（CFRP）试件上的人工平底孔（FBH）进行实验，通过考虑缺陷信噪比（SNR），与基于快速傅里叶变换（FFT）的热波雷达成像（TWRI）或传统锁相热成像（LIT）相比，验证基于FrFT的增强型TWRI的缺陷检测能力。
