摘要
利用锥束CT检测系统对多孔陶瓷试样进行扫查与重建,讨论滤波板位置、透照管电压、旋转轴倾斜校正和投影张数等工艺参数对CT重建图像质量的影响。结果表明:在探测器侧进行滤波可以减少试样的散射,提高图像的信噪比和对比度;与85、140 kV透照管电压下的图像相比,透照管电压为130 kV时CT重建的图像噪声低、对比度和清晰度高;对旋转轴进行−1.06°校正可以减少CT重建图像的伪影和几何畸变;CT重建投影数量增加,重建图像的信噪比、对比度和清晰度等随之提高。调整工艺参数可以改善CT重建图像质量,保证多孔陶瓷缺陷检测和微观形貌分析的准确性,拓展CT技术在陶瓷材料检测领域的应用。
With the employment of cone-beam CT detection system to scan and reconstruct porous ceramic samples,the influence of process parameters such as filter plate position,tube voltage,rotation axis tilt correction and number of projection on the quality of reconstructed CT images was discussed.The results show that filtering on the detector side can reduce the scattering of the sample and improve the signal-to-noise ratio and contrast of the images.Compared with the images reconstructed at 85 and 140 kV,the images at 130 kV have the lower noise and higher contrast and clarity.Correcting the rotation axis by−1.06°can reduce the artifacts and geometric distortion of the reconstructed CT images.In addition,with the number of CT reconstruction increases,the signal-to-noise ratio,contrast and clarity of the reconstructed image are improved.Adjusting the process parameters can improve the quality of CT reconstructed images,ensure the accuracy of defect detection and micro-morphology analysis on porous ceramics,expanding the application of CT technology in the field of ceramic material detection.
作者
张尤
张士晶
朱秀森
赵清海
王树鹏
刘海强
张晓峰
邬冠华
ZHANG You;ZHANG Shi-jing;ZHU Xiu-sen;ZHAO Qing-hai;WANG Shu-peng;LIU Hai-qiang;ZHANG Xiao-feng;WU Guan-hua(Key Laboratory of Nondestructive Testing(Ministry of Education),Nanchang Hangkong University,Nanchang 330063,China;Dalian Changfeng Industrial Co.,Ltd.,Liaoning Dalian 116038,China;AECC Shenyang Liming Aero-Engine Co.,Ltd.,Shenyang 110043,China;Nuclear Industry Research and Engineering Co.,Ltd.,Beijing 101300,China)
出处
《失效分析与预防》
2021年第6期374-379,391,共7页
Failure Analysis and Prevention
基金
国家自然科学基金(AA202108033)
无损检测技术教育部重点实验室开放基金(EW202108228)。
关键词
多孔陶瓷
射线检测
CT技术
质量优化
porous ceramics
X-ray detection
CT technology
quality optimization
