Kurtosis transfer in MDOF systems under amplitude-modulated Non-Stationary Non-Gaussian Excitations: A Frequency-Domain decomposition approach
Non-stationary non-Gaussian random vibrations, frequently encountered in aerospace, mechanical, and civil systems, often induce transient structural responses with complex and unpredictable dynamics. Kurtosis, a key statistical measure of signal impulsiveness, plays a dual role in characterizing such transient behaviors and assessing vibration fatigue damage. This study develops a kurtosis transfer model for multi-degree-of-freedom (MDOF) systems under amplitude-modulated non-stationary non-Gaussian excitations, assuming the excitation spectrum sufficiently covers the system’s modal frequencies to induce resonance-dominated responses. The proposed framework reveals how kurtosis is selectively transmitted through specific modal pathways by establishing a mathematical relationship between frequency-domain excitation substructures and the resulting response kurtosis. In addition, a phase modulation strategy is introduced to adjust the non-Gaussian properties of decomposed excitation signals, thereby enabling active control of the system’s response kurtosis. Numerical simulations and experimental validations confirm the model’s predictive accuracy. The resulting methodology offers a physically interpretable and computationally efficient framework for known vibration systems, supporting both dynamic analysis and the design of excitation signals with targeted kurtosis levels for accelerated vibration fatigue testing.
Authors
- Wuyang Lei (ORCID: https://orcid.org/0000-0003-1573-3744)
- Yu Jiang (ORCID: https://orcid.org/0000-0003-0398-2938)
- Jinhao Zhang (ORCID: https://orcid.org/0000-0002-3661-1845)
- Yawen Tian
- Hongbo Tang (ORCID: https://orcid.org/0000-0003-1568-0013)
Institutions
- National University of Defense Technology (CN)
Publication Details
- Journal
- Mechanical Systems and Signal Processing
- Published
- 2025-07-05
- DOI
- https://doi.org/10.1016/j.ymssp.2025.113059
- Primary Topic
- Image and Signal Denoising Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00