Title :
Comparative Analyses and Experiment Verification on Cockpit Background Sound´ Characteristic Frequency
Author :
Cheng Daolai ; Yi Chuijie ; Zhang Zhiqiang ; Xiao Xianbo ; Yao Hongyu
Author_Institution :
Sch. of Constr. & Safety Eng., Shanghai Inst. of Technol., Shanghai, China
Abstract :
Because the characteristic frequencies of cockpit background sound recorded by cockpit voice recorder (CVR) is the key evidence in investigating accident causes for wrecked airplane. And it is crucial for investigator to verify the characteristic frequencies through different methods. To obtain exact characteristic frequencies for cockpit background sound, systematic research are made. Firstly,the CVR signals is classified into speech signals, non-speech signals; then, cockpit voice decoding system (CVDS) is developed according to the audio principles. Through the CVDS,the cockpit background sounds are differentiated & heard, and as an example of a background sound signal, an overspread warning signal initial spectrum characteristics are obtained. At the same time,to get more exact spectrum characteristics of the signal, three algorithm methods (wavelet transform-WT, chirp Z- transform-CZT, correlation analyses-PSD) are applied to the signal respectively, their characteristics frequency (maximum frequency) are acquired and almost identical. Finally, to prove the algorithm results, the experiment verification to characteristic frequency of over speed warning signal and other three kinds cockpit background sounds from airplane cockpits are checked out and analyzed in whole anechoic room with the aid of LMS SC305 instrument and its software. Research indicates that the experiment characteristic frequency spectrums of the cockpit background sounds are identical with the three algorithm methods. The concludes of the paper provides better approaches for civil aviation experts to comprehend the cockpit sound signals characteristics and reveal wreckage aircraft causes.
Keywords :
Z transforms; aerospace accidents; aircraft instrumentation; correlation methods; recorders; signal classification; spectral analysis; speech coding; wavelet transforms; CVR signal classification; LMS SC305 instrument; anechoic room; chirp Z- transform; cockpit background sound characteristic frequency; cockpit voice decoding system; cockpit voice recorder; correlation analyses; frequencies spectrum analysis; nonspeech signals; overspread warning signal initial spectrum characteristics; speech signals; wavelet transform; wrecked airplane; Air accidents; Airplanes; Algorithm design and analysis; Chirp; Decoding; Frequency; Signal analysis; Software algorithms; Speech; Wavelet analysis;
Conference_Titel :
Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4244-5543-0
DOI :
10.1109/ICICIC.2009.142