基于截面SEM数据特征的微尘三维形貌建模方法

doi:10.7527/S1000-6893.2021.26201

Abstract

Abstract:

The performance of aerospace equipment in dusty environment is seriously affected by dust particles， such as military helicopters and transport planes taking off and landing in the desert and Mars rovers used on the dusty surface of Mars. To strengthen the dustproof design of aerospace equipment， the 3D morphology of dust particles is very important， and affects the aerodynamic and adhesion characteristics of dust particles. However， due to the wide distribution of particle sizes， complex compositions and irregular shapes， it is very difficult to obtain accurate 3D morphology of dust particles. In this paper， a novel method for modeling the 3D morphology of dust particles is proposed based on cross-sectional SEM data characteristics. The tomographic images with high resolution are obtained by layers peeling of dust particle samples. Based on the radius variation of the embedded steel ball in the fault image， the problem of accurate measurement of fault image spacing is solved. The 3D morphology reconstruction of fine dust based on the fault image is realized. The proposed method is used to reconstruct and analyze the 3D morphology of the dust particle samples with a particle size of 100 μm. The accurate 3D morphologies of 500 dust particles are obtained. In this paper， the 3D morphology of dust particle is quantitatively characterized， and the analysis method of the shape characteristics of dust particle is developed. The morphological data of dust particles is provided for studying the aerodynamic， rebound and adsorption characteristics of dust particles， promoting the research on aero-engine erosion protection， aero-engine aerodynamics and space probe， as well as dustproof design of aerospace equipment.

Key words: aerospace equipment, dust particle, geometric feature, image processing, three-dimensional morphology

CLC Number:

V233

Linhong ZHOU, Guangyu HE, Shunlai ZANG. A method for modeling three-dimensional morphology of dust particle based on cross-sectional SEM data characteristics[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(4): 426201.

Figures/Tables 17

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References 26

1	何光宇，李应红，柴艳，等. 航空发动机压气机叶片砂尘冲蚀防护涂层关键问题综述［J］. 航空学报， 2015， 36（6）：1733-1743.
	HE G Y， LI Y H， CHAI Y， et al. Review of key issues on coating against sand erosion of aero-engine compressor blade［J］. Acta Aeronautica et Astronautica Sinica， 2015， 36（6）：1733-1743 （in Chinese）.
2	HE G Y， SUN D Y， CHEN J， et al. Key problems affecting the anti-erosion coating performance of aero-engine compressor： a review［J］. Coatings， 2019， 9（12）： 821.
3	PEPI M， SQUILLACIOTI R， PFLEDDERER L， et al. Solid particle erosion testing of helicopter rotor blade materials［J］. Journal of Failure Analysis and Prevention， 2012， 12（1）： 96-108.
4	CAO X， HE W F， HE G Y， et al. Sand erosion resistance improvement and damage mechanism of TiAlN coating via the bias-graded voltage in FCVA deposition［J］. Surface and Coatings Technology， 2019， 378： 125009.
5	NAVEED M， SCHLAG H， KÖNIG F， et al. Influence of the erodent shape on the erosion behavior of ductile and brittle materials［J］. Tribology Letters， 2017， 65（1）： 18.
6	SUN Z P， HE G Y， MENG Q J， et al. Corrosion mechanism investigation of TiN/Ti coating and TC4 alloy for aircraft compressor application［J］. Chinese Journal of Aeronautics， 2020， 33（6）： 1824-1835.
7	LI Y R， CHEN F Y， LI R N， et al. Research on aerodynamic characteristics of wind turbine airfoil and blade in sand-wind environment［J］. International Transactions on Electrical Energy Systems， 2021， 31（11）：e12541.
8	石瑞芳，林建忠. 气固两相湍流场纳米颗粒演变特性综述［J］. 航空学报， 2021， 42（12）： 625825.
	SHI R F， LIN J Z. A review on evolution characteristics of nanoparticles in gas-solid two-phase turbulent flow field［J］. Acta Aeronautica et Astronautica Sinica， 2021， 42（12）： 625825 （in Chinese）.
9	王萍，郑晓静. 风沙两相流数值模拟研究进展［J］. 航空学报， 2021， 42（9）： 625767.
	WANG P， ZHENG X J. Advances in numerical simulation of wind-blown sand［J］. Acta Aeronautica et Astronautica Sinica， 2021， 42（9）： 625767 （in Chinese）.
10	牛佳佳，王锁芳，李鹏飞. 非球形粒子反弹分布特性试验探究［J］. 推进技术， 2018， 39（3）： 638-644.
	NIU J J， WANG S F， LI P F. Experimental research on rebound distribution characteristics of non-spherical particles［J］. Journal of Propulsion Technology， 2018， 39（3）： 638-644 （in Chinese）.
11	赵聪敏，何清，杨兴华，等. 巴丹吉林沙漠风沙流输沙沙粒形貌特征分析［J］. 沙漠与绿洲气象， 2012， 6（2）： 25-29.
	ZHAO C M， HE Q， YANG X H， et al. Analysis of sand shape characteristics from the wind-sand flows in Badanjilin desert［J］. Desert and Oasis Meteorology， 2012， 6（2）： 25-29 （in Chinese）.
12	王红芸，李岩，赵丽丽，等. 激光粒度分析仪分析方法的研究［J］. 科技资讯， 2014， 12（19）： 213-214.
	WANG H Y， LI Y， ZHAO L L， et al. Study on analysis method of laser particle size analyzer［J］. Science ＆ Technology Information， 2014， 12（19）： 213-214 （in Chinese）.
13	倪寿亮. 粒度分析方法及应用［J］. 广东化工， 2011， 38（2）： 223-224， 227.
	NI S L. Particle size analysis method and its application［J］. Guangdong Chemical Industry， 2011， 38（2）： 223-224， 227 （in Chinese）.
14	KOMBA J J， ANOCHIE-BOATENG J K， VAN DER MERWE STEYN W. Analytical and laser scanning techniques to determine shape properties of aggregates［J］. Transportation Research Record： Journal of the Transportation Research Board， 2013， 2335（1）： 60-71.
15	ALSHIBLI K A， DRUCKREY A M， AL-RAOUSH R I， et al. Quantifying morphology of sands using 3D imaging［J］. Journal of Materials in Civil Engineering， 2015， 27（10）： 04014275.
16	SUN Y， INDRARATNA B， NIMBALKAR S. Three-dimensional characterisation of particle size and shape for ballast［J］. Géotechnique Letters， 2014， 4（3）： 197-202.
17	JIA X D， GARBOCZI E J. Advances in shape measurement in the digital world［J］. Particuology， 2016， 26： 19-31.
18	LIANG H， SHEN Y， XU J H， et al. Multiscale three-dimensional morphological characterization of calcareous sand particles using spherical harmonic analysis［J］. Frontiers in Physics， 2021， 9： 744319.
19	ZHOU X W， LIU J Z， ZHU J， et al. Shape characterization of sand particles based on digital image processing technology［J］. Journal of Southeast University， 2020， 36（3）： 313-321.
20	万成，张肖宁，贺玲凤，等. 基于真实细观尺度的沥青混合料三维重构算法［J］. 中南大学学报（自然科学版）， 2012， 43（7）： 2813-2820.
	WAN C， ZHANG X N， HE L F， et al. 3D reconstruction algorithm of asphalt concrete based on real microscopic scale［J］. Journal of Central South University （Science and Technology）， 2012， 43（7）： 2813-2820 （in Chinese）.
21	PENG Y P， WU Z B， CAO G Z， et al. Three-dimensional reconstruction of wear particles by multi-view contour fitting and dense point-cloud interpolation［J］. Measurement， 2021， 181： 109638.
22	ZHOU B， WANG J， WANG H. Three-dimensional sphericity， roundness and fractal dimension of sand particles［J］. Géotechnique， 2018， 68（1）： 18-30.
23	张永弟，岳彦芳，杨光，等. 提高CT图像手骨模型重建精度的方法［J］. 计算机辅助设计与图形学学报， 2017， 29（10）： 1802-1806.
	ZHANG Y D， YUE Y F， YANG G， et al. A method of increasing precision for hand bone models reconstruction of CT images［J］. Journal of Computer-Aided Design ＆ Computer Graphics， 2017， 29（10）： 1802-1806 （in Chinese）.
24	吕继淮，刘守慎，尹万力，等. 军用直升机防砂尘要求［S］. 1991.
	LV J H， LIU S S， YIN W L， et al. Requirements for sand and dust control of military helicopters ［S］. 1991 （in Chinese）.
25	KIM H， AHN E， CHO S， et al. Comparative analysis of image binarization methods for crack identification in concrete structures［J］. Cement and Concrete Research， 2017， 99： 53-61.
26	LORENSEN W E. History of the marching cubes algorithm［J］. IEEE Computer Graphics and Applications， 2020， 40（2）： 8-15.

拟合方法	不同粒径微尘占比/%
拟合方法	<25 μm	25~40 μm	40~55 μm	55~70 μm	70~85 μm	85~100 μm	100~125 μm	>125 μm
最小二乘圆（直径）	2.007	5.351	11.037	29.431	26.756	18.395	5.351	1.672
最小二乘椭圆（长轴）	0.334	3.344	4.682	11.371	28.428	18.060	22.074	11.706
最小二乘椭圆（短轴）	5.686	17.391	27.090	31.438	13.712	3.679	1.003	0
最小外接圆（直径）	0	3.344	4.348	6.689	21.405	26.421	25.753	12.040
最大内接圆（直径）	9.365	24.415	38.462	22.074	5.017	0.334	0.334	0

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A method for modeling three-dimensional morphology of dust particle based on cross-sectional SEM data characteristics

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