Anomaly Location Model for Aircraft Intensity Detection Based on Multi-source Data Fusion

被引:0
|
作者
Chen, Jiaojiao [1 ]
Chang, Liang [1 ]
Nie, Xiaohua [1 ]
Luo, Lilong [1 ]
机构
[1] Aircraft Strength Res Inst China, Natl Key Lab Strength & Struct Integr, Xian 710065, Shaanxi, Peoples R China
关键词
Abnormal location; Information fusion; Strength test big data; Data mining;
D O I
10.1007/978-981-97-4010-9_115
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
An anomaly localization model for aircraft intensities is built using multi-source information fusion in order to completely utilize the enormous data of aircraft intensity and realize their data value. To increase the accuracy and reliability of information, the multi-source strength data from the entire machine level in the "building block" test verification system is first evaluated, cleaned, redundant data, and noise are removed. Then, we can achieve unified integration, efficient access to multi-source data, and improve information integrity and consistency by integrating full spatio-temporal, full-dimensional, and full-factor data and designing a logical architecture for a multi-source heterogeneous intensity testing data cloud platform. Finally, using the three-layer information fusion, it is possible to implement deep analysis and the fusing of intensity test data to accurately identify anomalous positions.
引用
收藏
页码:1478 / 1489
页数:12
相关论文
共 50 条
  • [31] Multi-source data-based precipitation fusion model for small mountainous watersheds∗
    Zhan C.
    Zhang T.
    Jiang J.
    Shuikexue Jinzhan/Advances in Water Science, 2024, 35 (01): : 74 - 84
  • [32] Key Data Source Identification Method Based on Multi-Source Traffic Data Fusion
    Li, Shuo
    Zhang, Mengmeng
    Chen, Yongheng
    CICTP 2020: TRANSPORTATION EVOLUTION IMPACTING FUTURE MOBILITY, 2020, : 364 - 375
  • [33] Multi-source data fusion in detection of blast furnace burden surface
    Miao, Liang-Liang
    Chen, Xian-Zhong
    Hou, Qing-Wen
    Bai, Zhen-Long
    Wang, Zheng-Peng
    Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2014, 22 (09): : 2407 - 2415
  • [34] MIND: A Multi-Source Data Fusion Scheme for Intrusion Detection in Networks
    Anjum, Naveed
    Latif, Zohaib
    Lee, Choonhwa
    Shoukat, Ijaz Ali
    Iqbal, Umer
    SENSORS, 2021, 21 (14)
  • [35] The robust fusion of multi-source gravity data based on the spherical cap harmonic model
    Wang, Yi
    Jiang, Xiaodian
    Li, Deyong
    Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 2015, 44 (09): : 952 - 957
  • [36] Multi-source Information Fusion for Depression Detection
    Wang, Rongquan
    Wang, Huiwei
    Hu, Yan
    Wei, Lin
    Ma, Huimin
    PATTERN RECOGNITION AND COMPUTER VISION, PRCV 2023, PT V, 2024, 14429 : 517 - 528
  • [37] Multi-source data fusion for economic data analysis
    Li, Menggang
    Wang, Fang
    Jia, Xiaojun
    Li, Wenrui
    Li, Ting
    Rui, Guangwei
    NEURAL COMPUTING & APPLICATIONS, 2021, 33 (10): : 4729 - 4739
  • [38] A Multi-Source Data Feature Fusion and Expert Knowledge Integration Approach on Lithium-Ion Battery Anomaly Detection
    Wang, Yudong
    Bai, Xiwei
    Liu, Chengbao
    Tan, Jie
    JOURNAL OF ELECTROCHEMICAL ENERGY CONVERSION AND STORAGE, 2022, 19 (02)
  • [39] Multi-source data fusion for economic data analysis
    Menggang Li
    Fang Wang
    Xiaojun Jia
    Wenrui Li
    Ting Li
    Guangwei Rui
    Neural Computing and Applications, 2021, 33 : 4729 - 4739
  • [40] Multi-Source Data Fusion Study in Scientometrics
    Xu, Hai-Yun
    Wang, Chao
    Pang, Hong-shen
    Ru, Li-jie
    Fang, Shu
    QUALITATIVE & QUANTITATIVE METHODS IN LIBRARIES, 2016, : 611 - 626