Xu Bin, Sun Yuanhaoji, Li Jinhua, Deng Zhiyong, Li Hongyu, Zhang Bo, Liu Kai
School of Mechanical Engineering, Sichuan University, Chengdu 610065, China.
Nuclear Fuel and Material Institute, Nuclear Power Institute of China, Chengdu 610213, China.
Sensors (Basel). 2023 Aug 21;23(16):7291. doi: 10.3390/s23167291.
Zirconium sheet has been widely used in various fields, e.g., chemistry and aerospace. The surface scratches on the zirconium sheets caused by complex processing environment have a negative impact on the performance, e.g., working life and fatigue fracture resistance. Therefore, it is necessary to detect the defect of zirconium sheets. However, it is difficult to detect such scratch images due to lots of scattered additive noise and complex interlaced structural texture. Hence, we propose a framework for adaptively detecting scratches on the surface images of zirconium sheets, including noise removing and texture suppressing. First, the noise removal algorithm, i.e., an optimized threshold function based on dual-tree complex wavelet transform, uses selected parameters to remove scattered and numerous noise. Second, the texture suppression algorithm, i.e., an optimized relative total variation enhancement model, employs selected parameters to suppress interlaced texture. Finally, by connecting disconnection based on two types of connection algorithms and replacing the Gaussian filter in the standard Canny edge detection algorithm with our proposed framework, we can more robustly detect the scratches. The experimental results show that the proposed framework is of higher accuracy.
锆板已广泛应用于各个领域，例如化学和航空航天领域。复杂加工环境导致锆板表面出现划痕，这对其性能产生负面影响，例如使用寿命和抗疲劳断裂性能。因此，有必要检测锆板的缺陷。然而，由于存在大量分散的附加噪声和复杂的交错结构纹理，很难检测到此类划痕图像。因此，我们提出了一个用于自适应检测锆板表面图像划痕的框架，包括去噪和纹理抑制。首先，去噪算法，即基于双树复小波变换的优化阈值函数，使用选定参数去除分散且大量的噪声。其次，纹理抑制算法，即优化的相对全变差增强模型，采用选定参数抑制交错纹理。最后，通过基于两种连接算法连接断开部分，并将标准Canny边缘检测算法中的高斯滤波器替换为我们提出的框架，我们可以更稳健地检测划痕。实验结果表明，所提出的框架具有更高的准确性。
