Vibration-based hypervelocity impact identification and localization  

作　　者：Jiao BAO Lifu LIU Jiuwen CAO 

机构地区：[1]Department of Computer Engineering,Chengdu Technological University,Chengdu,611730,China [2]Machine Learning and I-health International Cooperation Base of Zhejiang Province,Hangzhou Dianzi University,Hangzhou,310018,China [3]Artificial Intelligence Institute,Hangzhou Dianzi University,Hangzhou,310018,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》2022年第4期515-529,共15页信息与电子工程前沿（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(Nos.U1909209 and 61503104);the Open Foundation of Hypervelocity Impact Research Center of China Aerodynamics Research and Development Center;the Research Start-up Funding,China(No.2019RC020)。

摘　　要：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 OSSST+TCD 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.

关 键 词：Ensemble learning Synchrosqueezied transform Gray-level co-occurrence matrix Image entropy Distance estimation 

分 类 号：V445.1[航空宇航科学与技术—飞行器设计] TP18[自动化与计算机技术—控制理论与控制工程] TP391.41[自动化与计算机技术—控制科学与工程]