基于极大图像熵的均质材料内部缺陷ICT诊断

INNER DEFECTS ICT DIAGNOSIS OF HOMOGENEOUS MATERIAL BASED ON MAXIMUM IMAGE-ENTROPY

ICT的待检材料如木材、铸件和钢件等,它们的密度一般都比较均匀或相近,因此它们的ICT断层扫描图像近似于二值化图像。利用这一先验信息,ICT的图像重建算法采用了一种基于极大图像熵和神经网络优化的重建方法,改造了其神经元输出特性,并假设图像的总照度在图像重建前后维持不变。模拟试验结果表明,在6个ICT投影角条件下重建出了高分辨率的均质材料内部缺陷图,从而为提高ICT的检查效率和减少设备造价提供一种有效途径。

The materials such as wood, cast and steel products, because their density are more homogeneous, so their image profiles which are inspected by ICT device must be binary-value images approximately. Based on this prophetic knowledge, an optimization strategy of maximum image-entropy and neural networks is adopted in image reconstruction algorithms, the output functions of neural cells is modified too. Moreover, the image illumination is fixed before and after image reconstruction. The results of experimentation show that a high resolution defects image of homogeneous material can be reconstructed under only 6 projection angles of ICT device. So, there will be a good approach to improve the work efficiency and reduce the cost of ICT devices.