Air Leak Material Identification in Pressurized Space Vehicles using a Convolutional Neural Network

被引：0
|
作者：
Bundy, Kenneth R. [1 ]
Abedi, Ali [1 ]
机构：
[1] Univ Maine, Dept Elect & Comp Engn, Wireless Sensor Networks WiSe Net Lab, Orono, ME 04473 USA
来源：
2017 IEEE INTERNATIONAL CONFERENCE ON WIRELESS FOR SPACE AND EXTREME ENVIRONMENTS (WISEE) | 2017年
基金：
美国国家航空航天局;
关键词：
D O I：
暂无
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
Pressurized space vehicles of all types are at risk of depressurization due to leaking air. Leaks may be caused by micro-meteor and orbital debris (MMOD) impact or structural aging and failure overtime. This paper addresses the issue of leak type detection by analyzing airborne ultrasonic waves using a Convolutional Neural Network. Depending on the vessel material, size of the leak, and pressure gradient, different waveforms are produced. Once a large number of samples have been recorded, the resulting data is used for the training of a Convolutional Neural Network for leak classification.
引用
收藏
页码：150 / 152
页数：3
相关论文
共 50 条
  • [41] On Estimating Air Pollution from Photos Using Convolutional Neural Network
    Zhang, Chao
    Yan, Junchi
    Li, Changsheng
    Rui, Xiaoguang
    Liu, Liang
    Bie, Rongfang
    MM'16: PROCEEDINGS OF THE 2016 ACM MULTIMEDIA CONFERENCE, 2016, : 297 - 301
  • [42] A convolutional neural network for pipe crack and leak detection in smart water network
    Zhang, Chi
    Alexander, Bradley J.
    Stephens, Mark L.
    Lambert, Martin F.
    Gong, Jinzhe
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2023, 22 (01): : 232 - 244
  • [43] Convolutional Neural Network Applied to Traversability Analysis of Vehicles
    Li Linhui
    Wang Mengmeng
    Ding Xinli
    Lian Jing
    Zong Yunpeng
    ADVANCES IN MECHANICAL ENGINEERING, 2013,
  • [44] Intention inference for space targets using deep convolutional neural network
    Li, Jiasheng
    Yang, Zhen
    Luo, Yazhong
    ADVANCES IN SPACE RESEARCH, 2025, 75 (02) : 2184 - 2200
  • [45] Classifying Vehicles with Convolutional Neural Network and Feature Encoding
    Wang, Shuang
    Li, Zhengqi
    Zhang, Haijun
    Ji, Yuzhu
    Li, Yan
    2016 IEEE 14TH INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN), 2016, : 784 - 787
  • [46] Prediction of Paravalvular Leak Post Transcatheter Aortic Valve Replacement Using a Convolutional Neural Network
    Wang, Zih Huei
    Lahoti, Geet
    Wang, Kan
    Liu, Shizhen
    Zhang, Chuck
    Wang, Ben
    Wu, Chien-Wei
    Vannan, Mani
    Qian, Zhen
    2018 IEEE 15TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2018), 2018, : 1088 - 1091
  • [47] Automatic Identification of Mantle Seismic Phases Using a Convolutional Neural Network
    Garcia, J. A.
    Waszek, L.
    Tauzin, B.
    Schmerr, N.
    GEOPHYSICAL RESEARCH LETTERS, 2021, 48 (18)
  • [48] Finger-vein biometric identification using convolutional neural network
    Ahmad Radzi, Syafeeza
    Khalil-Hani, Mohamed
    Bakhteri, Rabia
    TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2016, 24 (03) : 1863 - 1878
  • [49] Germinative paddy seed identification using deep convolutional neural network
    Islam, Mohammad Aminul
    Hassan, Md. Rakib
    Uddin, Machbah
    Shajalal, Md
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (25) : 39481 - 39501
  • [50] Identification of Glioma from MR Images Using Convolutional Neural Network
    Saxena, Nidhi
    Sharma, Rochan
    Joshi, Karishma
    Rana, Hukum Singh
    PROCEEDINGS OF THE FUTURE TECHNOLOGIES CONFERENCE (FTC) 2018, VOL 1, 2019, 880 : 589 - 597
12345