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ISSN: 2168-9792

Journal of Aeronautics & Aerospace Engineering
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Research Article

Cockpit Voice Analysis and Diagnostic Based on Conditional Rules & Fault Tree Analysis

Lin Zhang JI1,2, Dao Lai Cheng2*, Chui Jie YI3 and Hong Yu Yao4
1School of Energy & Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
2College of Urban Construction & Safety Engineering, Shanghai Institute of Technology, Shanghai, 201418, China
3Qingdao Technological University, Qingdao R&D Center of Energy Equipment, Qingdao, 266033, China
4China Academy of Civil Aviation Science and Technology, Beijing 100028, China
*Corresponding Author : Dao Lai Cheng
College of Urban Construction & Safety Engineering
Shanghai Institute of Technology
Shanghai 201418, China
E-mail: [email protected]
Received July 16, 2012; Accepted October 29, 2012; Published November 01, 2012
Citation: Lin Zhang JI, Cheng DL, Chui Jie YI, Yao H (2013) Cockpit Voice Analysis and Diagnostic Based on Conditional Rules & Fault Tree Analysis. J Aeronaut Aerospace Eng 2:104. doi: 10.4172/2168-9792.1000104
Copyright: © 2013 Lin Zhang JI, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

The characteristics of cockpit voices (sounds) recorded by Cockpit Voice Recorder (CVR) are key evidences in investigating accident causes for wrecked airplane. In order to analyzing and diagnosing wrecked airplane causes through cockpit voices in CVR, some researchers are made as followings in this paper: Firstly, some typical background sounds of cockpit voices, such as wind shear audio, near-earth audio warning, take-off form of audio warning, fire alarm and so on, are obtained and classified through listening and distinguishing by adobe audition audio software in laboratory. Then, the characteristics of these background sounds are extracted by signal analyses methods such as Fourier Transform (FT), Wavelet Transform (WT), and so on. Through these methods, the special characteristics are depurated, such as frequency value, spectral density, and frequency line numbers. Thirdly, as the key part of the paper, conditional rules and fault trees principles focuses on and applied in order to distinguish and diagnose these special characteristics for approximate or different background sounds of cockpit voices. And some available results are obtained finally. Through all these above researches, new analyzing and diagnosing approaches are put forward, which are suitable for accurate grasping the cause of flight accident and analyses and diagnose flight accident. All the researches and conclusions have a certain reference for analysis and diagnosis of flight accidents, and protect flight security.

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