This study presents the empirical mode decomposition method (EMD) for vehicle vibration and a correlation detection approach for input from road and vehicle body vibration using the Hilbert-Huang transform (HHT). Although the magnitude squared coherence is commonly used to examine the correlation of vehicle vibration with road input, it is not suitable for non-stationary vibration. On the other hand, the Hilbert-Huang transform (HHT) which consists of EMD and the Hilbert transform is proposed. This method is suitable for transient vibration analysis, while the drawbacks to intermittence signals are suggested. Vehicle vibration signals include intermittence signals in some cases. In this study, the masking EMD which adapts the mask signal to the amplitude of the target signal was applied to vehicle vibration to alleviate the drawbacks. By this method, the correlation analysis by HHT demonstrates higher temporal resolution compared to the continuous wavelet transform. Thus, it becomes possible to identify the components that caused vibrations at the moments when the passengers felt comfortable or uncomfortable, and to analyze the characteristics of the vibrations.
Temporal and Frequency Analysis with Empirical Mode Decomposition for Vehicle Vibration Signals
Lect.Notes Mechanical Engineering
Advanced Vehicle Control Symposium ; 2024 ; Milan, Italy September 01, 2024 - September 05, 2024
04.10.2024
6 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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