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

被引:1
|
作者
Wang, Xin [1 ]
Zhao, Xinbin [1 ]
Yu, Liling [1 ]
机构
[1] China Acad Civil Aviat Sci & Technol, Engn & Tech Res Ctr Civil Aviat Safety Anal & Pre, Aviat Safety Res Div, Beijing, Peoples R China
来源
PROCEEDINGS OF 2020 IEEE 2ND INTERNATIONAL CONFERENCE ON CIVIL AVIATION SAFETY AND INFORMATION TECHNOLOGY (ICCASIT) | 2020年
关键词
flight quality; pitch; QAR data; normal distribution; t test;
D O I
10.1109/ICCASIT50869.2020.9368701
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
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 arc 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.
引用
收藏
页码:955 / 958
页数:4
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