DocumentCode
113881
Title
Analysis & fault diagnosis of cockpit voice signals based on information fusion
Author
Daolai Cheng ; Shoupeng Wan ; Linzhang Ji
Author_Institution
Inst. of Energy & Power Eng., Shanghai Inst. of Technol., Shanghai, China
fYear
2014
fDate
26-28 April 2014
Firstpage
106
Lastpage
109
Abstract
Aircraft cockpit voice signals recorded by aircraft black boxes are one of the key evidences to analyze and diagnose the flight faults. Firstly, the paper describes information fusion principle, and constructs three-level information fusion model. Then, many typical cockpit voice signals as examples (such as wind shear, ground proximity warning, take off form warning, fire alarm, background sound of stick shaker, over speed warning, background ground of high speed with translation, and so on), their characteristic warehouse have been set up. Thirdly, the new analysis and diagnosis methods for cockpit voice signals has been put forward according to production rule and information fusion principle. Finally, binary system diagnostic trees on cockpit voice signals are formed and some analysis and diagnosis results are obtained.
Keywords
aircraft communication; aircraft displays; alarm systems; fault diagnosis; trees (mathematics); aircraft black boxes; aircraft cockpit voice signals; background sound; binary system diagnostic trees; characteristic warehouse; fire alarm; flight fault diagnosis; ground proximity warning; over speed warning; stick shaker; take off form warning; three-level information fusion model; wind shear; Aircraft; cockpit voice; fault diagnosis; information fusion; production rule;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Technology (ICIST), 2014 4th IEEE International Conference on
Conference_Location
Shenzhen
Type
conf
DOI
10.1109/ICIST.2014.6920342
Filename
6920342
Link To Document