Application and Development of Flight Data Monitoring System in Aviation Safety Management
DOI:
https://doi.org/10.54097/7aftuwigKeywords:
Flight data monitoring system, Aviation security management, Application, DevelopmentAbstract
Safety is the eternal theme of civil aviation. With the progress of society and the development of economy, the development of general aviation is imperative, and people's attention to navigation safety is getting higher and higher. Modern and effective safety management methods and tools need to be adopted to improve general aviation safety production levels. The application of the successful application of flight aviation quality monitoring to general aviation is an effective way to effectively improve the general aviation safety production level.
References
Guo Chaochao; Zhao Huibing. Controlled flight risk analysis and countermeasures based on the QAR over -limit incident [J]. Journal of Anyang Institute of Technology,2020
Chen Liwei; Zhu Fan; Liu Xi; Yang Nan. Electric light and control, flight control system visualization simulation platform design [J]. Electric light and control,2012(01)
Dong Gongjun. Aerospace aircraft track and posture control visual simulation system research [D].Chokuhoku University,2022
Wei Lin. Ningyan's design and realization of the flight quality monitoring system based on QAR Aviation Big Data [J]Computer knowledge and technology. 2023,19 (08)
Zhukang. Research on the health state data management method based on artificial intelligence technology [J]. Mechanical Management Development. 2022,37(05)
ZhengWei based on the land risk assessment and prediction research based on QAR data [D].China Civil Aviation University.2017 (03)
Xie Jiayi. Research and early warning technology based on the unstable approach of QAR flight big data [D].Wuhan University.2023
Wang Lei; Sun Ruishan; Wu Changxu; Cui Zhenxin; Lu Zheng; Hydential Risk of Flying QAR data, quantitative evaluation model [J].Journal of Chinese Safety Science. 2014,24(02)
Wang C , Sun L , Wei J ,et al.A new Trojan horse detection method based on negative selection algorithm[J].IEEE, 2012.DOI:10.1109/OMEE.2012.6343580.
Wang C , Yang H , Chen Y ,et al.Identification of image-spam based on SIFT image matching algorithm[J]. 2010.
Wang C , Yang H , Chen Y ,et al.Identification of Image-spam Based on Perimetric Complexity Analysis and SIFT Image Matching Algorithm[J].Journal of information and computational science, 2012, 9(4):p.1073-1081.
Sun, Li. "Protecting the supply chain in the open source ecosystem: ways to determine the component version number without package management documents."Journal of Computing and Electronic Information Management 12.1 (2024): 32-36.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
