Research on quick access recorder data preprocessing based on kernel extreme learning machine and wavelet transform

Yutong Liu; Jie Bai

doi:10.1117/12.3033058

5 July 2024 Research on quick access recorder data preprocessing based on kernel extreme learning machine and wavelet transform

Yutong Liu, Jie Bai

Author Affiliations +

Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131843K (2024) https://doi.org/10.1117/12.3033058
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia

Abstract

At present, the Quick Access Recorder (QAR) is the most widely used device for storing aircraft recording data. QARdata contains a wealth of valuable and unexplored information, detailing the true state of the aircraft. Therefore, the mining and development of QAR data is particularly crucial. The decoded QAR data contains a large number of outliers, and is always doped with nonlinear and non-stationary noise signals, and the wavelet denoising method is widely used in the signal field because of its simple algorithm and small amount of calculation, which improves the accuracy and efficiency of data processing. The extreme learning machine has strong learning ability and good generalization performance. In order to further improve the noise reduction effect of the sensor signal, a hybrid noise reduction method based on Kernel Extreme Learning Machine (KELM) and wavelet algorithm is proposed, which designs a filter based on the KELM algorithm to reduce the noise of the sensor signal on the one hand, and further smooths the KELM noise reduction signal by using the classical wavelet transform on the other hand, so as to further improve the noise reduction effect under the premise of ensuring that the signal is not distorted. Simulation results show that the noise reduction effect of the proposed hybrid noise reduction method is better than that of the single noise reduction method.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yutong Liu and Jie Bai "Research on quick access recorder data preprocessing based on kernel extreme learning machine and wavelet transform", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131843K (5 July 2024); https://doi.org/10.1117/12.3033058

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KEYWORDS

Denoising

Wavelets

Interference (communication)

Sensors

Extreme learning machines

Neurons

Signal processing

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