基于同面電容成像的航天隔熱復合材料粘接缺陷檢測方法
發(fā)布時間:2018-11-19 12:03
【摘要】:為了實現(xiàn)對航天隔熱復合材料粘接缺陷的可視化檢測,在分析同面電容成像(CPCI)系統(tǒng)模型及圖像重建原理的基礎上,提出了一種基于Kalman濾波的CPCI算法,并通過對估計電容值和測量電容值依賴程度的不斷調整來實現(xiàn)最優(yōu)估計。構建了仿真實驗,驗證了采用基于Kalman濾波的CPCI算法在缺陷檢測中的可行性和有效性。與采用常規(guī)CPCI算法的檢測實驗結果進行了對比,結果表明,所提圖像重建算法獲得的粘接缺陷圖像精度具有較大的提升。
[Abstract]:In order to detect the adhesion defects of spaceflight insulating composites visually, a CPCI algorithm based on Kalman filter is proposed based on the analysis of the model of coplanar capacitive imaging (CPCI) system and the principle of image reconstruction. The optimal estimation is realized by adjusting the dependence of the estimated capacitance value and the measured capacitance value. The simulation results show that the CPCI algorithm based on Kalman filter is feasible and effective in defect detection. The experimental results are compared with those of the conventional CPCI algorithm. The results show that the proposed image reconstruction algorithm can improve the precision of the adhesive defect image.
【作者單位】: 燕山大學電氣工程學院;燕山大學國防科學技術學院;
【基金】:國家自然科學基金項目(61573302) 河北省自然科學基金項目(E2017203240)
【分類號】:TP391.41;V250.2
本文編號:2342248
[Abstract]:In order to detect the adhesion defects of spaceflight insulating composites visually, a CPCI algorithm based on Kalman filter is proposed based on the analysis of the model of coplanar capacitive imaging (CPCI) system and the principle of image reconstruction. The optimal estimation is realized by adjusting the dependence of the estimated capacitance value and the measured capacitance value. The simulation results show that the CPCI algorithm based on Kalman filter is feasible and effective in defect detection. The experimental results are compared with those of the conventional CPCI algorithm. The results show that the proposed image reconstruction algorithm can improve the precision of the adhesive defect image.
【作者單位】: 燕山大學電氣工程學院;燕山大學國防科學技術學院;
【基金】:國家自然科學基金項目(61573302) 河北省自然科學基金項目(E2017203240)
【分類號】:TP391.41;V250.2
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1 金鈺;同面電極電容在復合材料結構粘接缺陷檢測中的應用研究[D];燕山大學;2016年
2 賈瑤;基于ECT的航天隔熱材料粘接層缺陷檢測研究[D];燕山大學;2016年
3 王健健;隔熱瓦材料與基體黏接缺陷檢測的實驗研究[D];燕山大學;2015年
4 李志鵬;基于X射線圖像的軟軸缺陷檢測技術[D];中北大學;2017年
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