基于振动的超高速碰撞识别与定位

包姣; 刘力夫; 曹九稳

doi:10.1631/FITEE.2000483

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基于振动的超高速碰撞识别与定位

人工智能在空间环境和航天器中的应用专题 | Updated：2022-05-19

- 基于振动的超高速碰撞识别与定位
- Vibration-based hypervelocity impact identification and localization
- 信息与电子工程前沿（英文） 2022年23卷第4期页码：515-529
- Affiliations：
  
  1.Department of Computer Engineering, Chengdu Technological University, Chengdu611730, China
  2.Machine Learning and I-health International Cooperation Base of Zhejiang Province, Hangzhou Dianzi University, Hangzhou310018, China
  3.Artificial Intelligence Institute, Hangzhou Dianzi University, Hangzhou310018, China
- Author bio：
  
  ‡Corresponding author
- Funds：
  
  National Natural Science Foundation of China(U1909209;61503104);Open Foundation of Hypervelocity Impact Research Center of China Aerodynamics Research and Development Center, and the Research Start-up Funding, China(2019RC020)
- DOI：10.1631/FITEE.2000483
  中图分类号： TP391.4
- 收稿：2020-09-16，
  
  录用：2021-04-09，
  
  网络出版：2022-03-04，
  
  纸质出版：2022-04
- Accepted：
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包姣, 刘力夫, 曹九稳. 基于振动的超高速碰撞识别与定位[J]. 信息与电子工程前沿（英文）, 2022,23(4):515-529.

Jiao BAO, Lifu LIU, Jiuwen CAO. Vibration-based hypervelocity impact identification and localization[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(4): 515-529.
包姣, 刘力夫, 曹九稳. 基于振动的超高速碰撞识别与定位[J]. 信息与电子工程前沿（英文）, 2022,23(4):515-529. DOI： 10.1631/FITEE.2000483.

Jiao BAO, Lifu LIU, Jiuwen CAO. Vibration-based hypervelocity impact identification and localization[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(4): 515-529. DOI： 10.1631/FITEE.2000483.

摘要

超高速碰撞（HVI）振动源识别与定位在载人航天器防护、机床碰撞损伤检测与定位等领域有着广泛应用。本文研究了基于同步压缩变换（SST）和纹理颜色分布（TCD）的冲击图像HVI源识别和定位算法。提出基于SST和TCD图像特征融合的HVI图像表示方法。为实现更精确的检测和定位，通过关联和评估样本标签与特征维度之间的相似性，获得最优选择性特征OS

SST+TCD

。将常用的分类和回归模型通过投票和堆叠融合，实现最终的检测和定位。基于所采集的3种高速子弹撞击铝合金板产生的HVI数据，验证了所提算法的有效性。实验结果表明本文提出的HVI识别与定位算法具有更高精准度。最后基于传感器分布，提出一种精确的四圆质心定位算法用于HVI源坐标定位。

Abstract

Hypervelocity impact (HVI) vibration source identification and localization have found wide applications in many fields

such as manned spacecraft protection and machine tool collision damage detection and localization. In this paper

we study the synchrosqueezed transform (SST) algorithm and the texture color distribution (TCD) based HVI source identification and localization using impact images. The extracted SST and TCD image features are fused for HVI image representation. To achieve more accurate detection and localization

the optimal selective stitching features

are obtained by correlating and evaluating the similarity between the sample label and each dimension of the features. Popular conventional classification and regression models are merged by voting and stacking to achieve the final detection and localization. To demonstrate the effectiveness of the proposed algorithm

the HVI data recorded from three kinds of high-speed bullet striking on an aluminum alloy plate is used for experimentation. The experimental results show that the proposed HVI identification and localization algorithm is more accurate than other algorithms. Finally

based on sensor distribution

an accurate four-circle centroid localization algorithm is developed for HVI source coordinate localization.

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