An amplitude probability density function model under broadband multimodal stochastic vibration fatigue response宽带多峰随机振动疲劳响应下的振幅概率密度函数模型
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Zhu YH, Li P, Wu YT, Fu DK, Pan Y, 2024. An amplitude probability density function model under broadband multimodal stochastic vibration fatigue response. Probabilistic Engineering Mechanics, 77: 103640.DOI: 10.1016/j.probengmech.2024.103640
本文提出了一种基于振幅概率密度函数的宽带多峰随机振动响应下疲劳寿命预测模型。提出了一种分析方法来解决雨流振幅分布三阶和四阶归一化矩的色散问题。建立了雨流振幅分布的前四阶归一化矩与谱参数之间的统一关系，以确定模型参数。通过与其他频域方法的比较，基于雨流振幅的尾部概率密度分布，所提模型在宽带多峰响应功率谱下可给出更精确稳定的拟合结果。关键词: 宽带功率谱, 多峰 Gauss 过程, 概率密度函数, 随机振动疲劳, 频域方法In this paper, a fatigue life prediction model based on the amplitude probability density function under broadband multimodal stochastic vibration response is presented. An analysis method is proposed to address the dispersion of the third- and fourth-order normalized moments of rain-flow amplitude distributions. The unified relationships between the first four-order normalized moments of rain-flow amplitude distributions and the spectral parameters are established to determine the model parameters. Through comparison with other frequency-domain methods and based on the tail probability density distribution of rain-flow amplitude, the proposed model offers more precise and stable fitting results under broadband multimodal response power spectra.Keywords: Broadband power spectrum; Multimodal Gaussian process; Probability density function; Stochastic vibration fatigue; Frequency-domain method.![]()
Fig. 1. Analysis framework
Fig. 2. Realistic multimodal bending moment response power spectra
Fig. 3. Schematic diagrams of ideal broadband multimodal response power spectra
图 4: 指数分布、两类 Rayleigh 分布与归一化雨流振幅分布的对比Fig. 4. Comparisons between exponential, two Rayleigh, and normalized rain-flow amplitude distributions
图 5: 不同功率谱下参数 w 与归一化平均频率的关系Fig. 5. Relationship between w and χ_m under different power spectra
图 6: 雨流幅值分布二阶归一化矩近似值与数值模拟值的对比Fig. 6. Comparisons between approximate and numerical simulation values of the second-order normalized moment of rain-flow amplitude distributions
图 7: 不同功率谱下零点 (参数 v 与 u) 与归一化平均频率的关系Fig. 7. Relationships between zero points (v and u) and χ_m under different power spectra
图 8: 不同功率谱下零点 (参数 a_1 与 a_2) 与归一化平均频率的关系Fig. 8. Relationships between zero points (a_1 and a_2) and χ_m under different power spectra
图 9: 雨流幅值分布三阶与四阶归一化矩近似值与数值模拟值的对比Fig. 9. Comparisons between approximate and numerical simulation values of the third- and fourth-order normalized moments of rain-flow amplitude distributions
Fig. 10. Comparisons with rain-flow amplitude distributions under four representative power spectra
Fig. 11. Six constructed broadband multimodal power spectra
Fig. 12. Comparisons with rain-flow amplitude distributions in the six cases
Fig. 13. Constructed broadband response power spectra
Fig. 14. Deviations of the seven models under other types of broadband spectra
作者信息 | Authors
南京航空航天大学 (Nanjing University of Aeronautics & Astronautics) 航空学院
李飘 Piao Li, 通讯作者 (Corresp.)宁波大学 (Ningbo University) 机械工程与力学学院Email: lipiao@nuaa.edu.cn
上海航天精密机械研究所 (Shanghai Spaceflight Precision Machinery Institute)
南京航空航天大学 (Nanjing University of Aeronautics & Astronautics) 航空学院
南京航空航天大学 (Nanjing University of Aeronautics & Astronautics) 航空学院
律梦泽 M.Z. Lyu | 编辑 (Ed)
P.D. Spanos | 审校 (Rev)
陈建兵 J.B. Chen | 审校 (Rev)
彭勇波 Y.B. Peng | 审校 (Rev)
