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CLC number: TP301

On-line Access: 2022-04-20

Received: 2020-10-25

Revision Accepted: 2022-05-04

Crosschecked: 2021-02-22

Cited: 0

Clicked: 4497

Citations:  Bibtex RefMan EndNote GB/T7714


Xuegang HUANG


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Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.4 P.530-541


Variational Bayesian multi-sparse component extraction for damage reconstruction of space debris hypervelocity impact

Author(s):  Xuegang HUANG, Anhua SHI, Qing LUO, Jinyang LUO

Affiliation(s):  Hypervelocity Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China

Corresponding email(s):   emei-126@126.com

Key Words:  Hypervelocity impact, Variational Bayesian, Sparse representation, Damage assessment

Xuegang HUANG, Anhua SHI, Qing LUO, Jinyang LUO. Variational Bayesian multi-sparse component extraction for damage reconstruction of space debris hypervelocity impact[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(4): 530-541.

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%T Variational Bayesian multi-sparse component extraction for damage reconstruction of space debris hypervelocity impact
%A Xuegang HUANG
%A Anhua SHI
%A Qing LUO
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A1 - Xuegang HUANG
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A1 - Qing LUO
A1 - Jinyang LUO
J0 - Frontiers of Information Technology & Electronic Engineering
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2000575

To improve the survivability of orbiting spacecraft against space debris impacts, we propose an impact damage assessment method. First, a multi-area damage mining model, which can describe damages in different spatial layers, is built based on an infrared thermal image sequence. Subsequently, to identify different impact damage types from infrared image data effectively, the variational Bayesian inference is used to solve for the parameters in the model. Then, an image-processing framework is proposed to eliminate variational Bayesian errors and compare locations of different damage types. It includes an image segmentation algorithm with an energy function and an image fusion method with sparse representation. In the experiment, the proposed method is used to evaluate the complex damages caused by the impact of the secondary debris cloud on the rear wall of the typical Whipple shield configuration. Experimental results show that it can effectively identify and evaluate the complex damage caused by hypervelocity impact, including surface and internal defects.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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