Gao Yenan, Fu Jian, Chen Xiaolong
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China.
Jiangxi Research Institute, Beihang University, Nanchang 330000, China.
Sensors (Basel). 2024 Mar 21;24(6):2001. doi: 10.3390/s24062001.
Aero engines are the key power source for aerospace vehicles. Cermet turbine blades are the guarantee for the new-generation fighters to improve aero-engine overall performance. X-ray non-destructive reconstruction can obtain the internal structure and morphology of cermet turbine blades. However, the beam hardening effect causes artifacts in objects and affects the reconstruction quality, which is an issue that needs to be solved urgently. This study proposes a hardening-correction framework for industrial computed tomography (ICT) images based on iterative linear fitting. First, an iterative binarization was performed to improve the penetration length accuracy of the forward projection. Then, the proposed linear fitting technology combined with the Hermite function model is derived and analyzed to obtain suitable parameters of blade data. Finally, the fitting curves of the blade data, using the proposed method and the traditional polynomial fitting method, were analyzed and compared and were used to correct the engine turbine blade projection data to reconstruct different groups of tomographic images. Different groups of tomographic images were analyzed using three quantitative image quality evaluation indicators. The results show that the root-mean-square error (RMSE) of the tomographic image obtained by the proposed framework is 0.0133, which is lower than that of the compared method. The peak signal-to-noise ratio (PSNR) is 37.7050 dB and the feature structural similarity (FSIM) is 0.9881, which are both higher than that of the compared method. The proposed method improves the hardening-artifact-correction capability and can obtain higher-quality images, which provides new ideas for the development of imaging and detection of new-generation aero-engine turbine blades.
航空发动机是航空航天器的关键动力源。金属陶瓷涡轮叶片是新一代战斗机提升航空发动机整体性能的保障。X射线无损重建能够获取金属陶瓷涡轮叶片的内部结构和形态。然而，束硬化效应会在物体中产生伪影并影响重建质量，这是一个亟待解决的问题。本研究提出了一种基于迭代线性拟合的工业计算机断层扫描（ICT）图像硬化校正框架。首先，进行迭代二值化以提高正投影的穿透长度精度。然后，推导并分析了所提出的结合埃尔米特函数模型的线性拟合技术，以获得叶片数据的合适参数。最后，使用所提出的方法和传统多项式拟合方法对叶片数据的拟合曲线进行分析和比较，并用于校正发动机涡轮叶片投影数据以重建不同组的断层图像。使用三个定量图像质量评估指标对不同组的断层图像进行分析。结果表明，所提出框架获得的断层图像的均方根误差（RMSE）为0.0133，低于比较方法。峰值信噪比（PSNR）为37.7050 dB，特征结构相似度（FSIM）为0.9881，均高于比较方法。所提出的方法提高了硬化伪影校正能力，能够获得更高质量的图像，为新一代航空发动机涡轮叶片的成像与检测发展提供了新思路。
