期刊文献+

基于改进ECT的隔热材料胶层无损检测研究 被引量:12

Study on the non-destructive detection of the adhesive layer of thermal insulation material based on improved ECT
下载PDF
导出
摘要 电容层析成像(ECT)技术是能显示被测物场的二维或三维介质分布图像的实时检测技术,基于平面阵列传感器的ECT系统为陶瓷多孔隔热材料缺陷检测提供一种新的技术途径。本文针对陶瓷多孔隔热材料粘结胶层的缺陷无损检测问题,提出了一种基于改进的电容层析成像方法。首先在分析平面阵列传感器ECT检测系统模型及成像原理的基础上,提出了一种改进初值的Landwebe迭代图像重建算法;进一步将该算法应用到基材表层与隔热材料之间的粘结胶层的缺陷检测领域,并通过实验验证了采用基于改进ECT的无损检测方法在陶瓷多孔隔热材料粘结胶层缺陷检测中应用的有效性;同时与采用传统ECT成像算法的检测实验进行比较。结果表明本文提出的改进ECT算法对胶层缺陷图像重建质量具有较大幅度的提高。 Electrical capacitance tomography( ECT) technique is a real time detection technique,which could display the 2D or 3D medium distribution image of the target field to be detected. The ECT system based on planar array sensor provides a new method for the defect detection of ceramic porous thermal insulation material. Aiming at the problem of adhesive layer defect non-destructive detection of ceramic porous thermal insulation material,this paper puts forward a detection method based on improved Electrical Capacitance Tomography. First of all,on the basis of analyzing the model and ECT imaging principle of planar array sensor ECT detection system,a Landweber iterative image reconstruction algorithm with improved initial value is proposed. Then,the proposed algorithm is used to the defect detection of the bonding layer between the spacecraft surface base material layer and thermal insulation material. Experiments were conducted to verify the effectiveness of the proposed algorithm. Furthermore,compared with traditional ECT imaging algorithm,the improved ECT algorithm proposed in this paper greatly improves the image reconstruction quality of the adhesive layer defect.
出处 《仪器仪表学报》 EI CAS CSCD 北大核心 2016年第7期1596-1602,共7页 Chinese Journal of Scientific Instrument
基金 国家自然科学基金(61403333)项目资助
关键词 电容层析成像 陶瓷多孔隔热材料 无损检测 迭代算法 electrical capacitance tomography ceramic porous thermal insulation material nondestructive testing iterative algorithm
  • 相关文献

参考文献15

二级参考文献117

共引文献248

同被引文献86

引证文献12

二级引证文献38

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部