Xintao Zhou, Na Ma, Jiamin Liu, Jialing Zhang, Longlong Li
This study addresses the challenge of reducing the transmission of low-frequency road excitation vibrations to the cab of mining dump trucks to enhance ride comfort. Given the harsh working conditions of these vehicles, a novel methodology combining experimental data collection and advanced signal processing techniques was developed. The research established a comprehensive vibration testing program aligned with earth-moving machinery standards, collecting vibration acceleration data under both idling and full-load operation at 35 km/h. To improve data accuracy, Singular Value Decomposition (SVD) was employed to denoise the experimental vibration data, effectively mitigating environmental interference. Subsequent Fourier transform analysis revealed the vibration energy transfer patterns of the vehicle suspension system in the frequency domain. The results indicated a significant vibration isolation rate of 89 % for the frame suspension system, contrasting with only 7 % for the cab suspension system. Notably, the cab seat suspension system was found to amplify low-frequency road excitations. Compared to previous methods, this study innovatively integrates SVD and Fourier transform techniques to provide a more accurate and detailed understanding of vibration transmission. The key result of achieving an 89 % vibration isolation rate for the frame suspension system demonstrates the effectiveness of the proposed methodology. This study offers practical optimization directions for improving suspension system performance and ride comfort in mining dump trucks, outperforming traditional approaches by providing a more comprehensive analysis and actionable insights for vibration isolation. The findings also serve as valuable references for addressing similar engineering challenges in heavy machinery.