At present, the airlines have made some achievements in event analysis and investigation by using their quick access record (QAR) data. But where each airline’s flight quality is in the industry, and whether there is a problem in itself, the airline can’t find. In order to help airlines discover the existing flight quality problems, this article uses the QAR big data of the flight operational quality assurance (FOQA) Station of CAAC, and compares the industry-wide QAR data with the QAR data of individual airlines, and founds that the take-off pitch angle of a certain aircraft of A321 models is too small, by using mathematical statistics t test to verify, found the airline’s the take-off pitch angle and the industry’s the take-off pitch angle exist significant difference. The correlative speed at rotation and the speed at liftoff are also analyzed, and the significant difference is found. The FOQA Station of CAAC feeds back the problem to the airline and the authority. After the investigation of the airline and the authority, there are problems with the airline. And the airline immediately starts to rectify it.


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    Titel :

    Data Mining on the Flight Quality of an Airline based on QAR Big Data


    Beteiligte:
    Wang, Xin (Autor:in) / Zhao, Xinbin (Autor:in) / Yu, Liling (Autor:in)


    Erscheinungsdatum :

    2020-10-14


    Format / Umfang :

    257468 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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