期刊文献+

Modelling and Wavelet-Based Identification of 3-DOF Vehicle Suspension System 被引量:1

Modelling and Wavelet-Based Identification of 3-DOF Vehicle Suspension System
下载PDF
导出
摘要 In this paper, a three Degrees Of Freedom (DOF) model of a quarter vehicle suspension system is proposed including the seat driver mass. The modal parameters of this system, which indicate the comfort and the safety of the suspension, are identified using Wavelet analysis. Two applications of wavelet analysis are presented: signal denoising based on the Discrete Wavelet Transform (DWT) and modal identification based on the Continuous Wavelet Transform (CWT). It is shown that the CWT analysis of the system response, initially denoised using DWT, allows the estimation of the natural pulsations and the damping ratios. The usefulness of the DWT in denoising and the accuracy of the CWT in modal identification are tested and confirmed by applying them to the proposed model. The complete modeling and identification of a 3-DOF vehicle suspension system is developed and the simulation results verify these statements and are satisfactory. In this paper, a three Degrees Of Freedom (DOF) model of a quarter vehicle suspension system is proposed including the seat driver mass. The modal parameters of this system, which indicate the comfort and the safety of the suspension, are identified using Wavelet analysis. Two applications of wavelet analysis are presented: signal denoising based on the Discrete Wavelet Transform (DWT) and modal identification based on the Continuous Wavelet Transform (CWT). It is shown that the CWT analysis of the system response, initially denoised using DWT, allows the estimation of the natural pulsations and the damping ratios. The usefulness of the DWT in denoising and the accuracy of the CWT in modal identification are tested and confirmed by applying them to the proposed model. The complete modeling and identification of a 3-DOF vehicle suspension system is developed and the simulation results verify these statements and are satisfactory.
机构地区 不详
出处 《Journal of Software Engineering and Applications》 2011年第12期672-681,共10页 软件工程与应用(英文)
关键词 SUSPENSION System Discrete and Continuous WAVELET Transform Signal DENOISING MODAL IDENTIFICATION Suspension System Discrete and Continuous Wavelet Transform Signal Denoising Modal Identification
  • 相关文献

参考文献1

二级参考文献19

  • 1Segawa, R., Yamamoto, S., Sone, A., Masuda, A.: Cumulative damage estimation using wavelet transform of structural response. In: Proceedings of 12th World Conference on Earthquake Engineering. Auckland, New Zealand, January 30-February 4, pp. 1212-1220 (2000).
  • 2Yua, K.E, Yea, J.Y., Zoua, J.X., Yang, B.Y., Yang, H.: Missile flutter experiment and data analysis using wavelet transform. J. Sound Vib. 269, 899-912 (2004).
  • 3Le, T.E, Argoul, E: Continuous wavelet transform for modal identification using free decay response. J. Sound Vib. 277, 73- 100 (2004).
  • 4Shen, E, Zheng, M., Shi, D.E, Xu, E: Using the cross-correlation technique to extract modal parameters on response-only data. J. Sound Vib. 259(5), 1163-1179 (2003).
  • 5Yana, B.E, Miyamotoa, A., Bruhwiler, E.: Wavelet transform-based modal parameter identification considering uncertainty. J. Sound Vib. 291(1-2), 285-301 (2006).
  • 6Chakrabortya, A., Basua, B., Mitrab, M.: Identification of modal parameters of a mdof system by modified L-P wavelet packets. J. Sound Vib. 295, 827-837 (2006).
  • 7Sone, A., Yamamoto, S., Masuda, A.: Detection of inelastic excursions in hysteretic systems for cumulative damage estimation using wavelet transform of response time histories. In: Proceedings of 12th World Conference on Earthquake Engineering. Auckland, New Zealand, January 30-February 4, pp. 1220-1228 (2000).
  • 8Qina, S.R., Zhong, Y.M.: A new envelope algorithm of Hilbert- Huang Transform. Mech. Syst. Signal Process. 20, 1941-1952 (2006).
  • 9Penga, Z.K., Tsea, RW., Chu, EL.: A comparison study of improved Hilbert-Huang transform and wavelet transform: Application to fault diagnosis for rolling bearing. Mech. Syst. Signal Process. 19, 974-988 (2005).
  • 10Huang, N.E., Wu, M.L., Qu, W.D., Steven, R.L., Samuel, S.E: Applications of Hilbert-Huang transform to non-stationary finan- cial time series analysis. Appl. Stoch. Models Bus. Ind. 19, 245- 268 (2003).

共引文献6

同被引文献81

引证文献1

  • 1JRE Editorial Office,Maria Chiara Cavalli,De Chen,Qian Chen,Yu Chen,Augusto Cannone Falchetto,Mingjing Fang,Hairong Gu,Zhenqiang Han,Zijian He,Jing Hu,Yue Huang,Wei Jiang,Xuan Li,Chaochao Liu,Pengfei Liu,Quantao Liu,Guoyang Lu,Yuan Ma,Lily Poulikakos,Jinsong Qian,Aimin Sha,Liyan Shan,Zheng Tong,B.Shane Underwood,Chao Wang,Chaohui Wang,Di Wang,Haopeng Wang,Xuebin Wang,Chengwei Xing,Xinxin Xu,Min Ye,Huanan Yu,Huayang Yu,Zhe Zeng,You Zhan,Fan Zhang,Henglong Zhang,Wenfeng Zhu.Review of advanced road materials, structures, equipment, and detection technologies[J].Journal of Road Engineering,2023,3(4):370-468. 被引量:2

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部