脉动疲劳加载下振动信号的建模及损伤演化  

Modelling of vibration signals and damage evolution under cyclic fatigue loading

作　　者：张二亮[1] 王会康 刘璞 高肖雨 ZHANG Erliang;WANG Huikang;LIU Pu;GAO Xiaoyu(School of Mechanical and Power Engineering,Zhengzhou University,Zhengzhou 450001,China)

机构地区：[1]郑州大学机械与动力工程学院,郑州450001

出　　处：《重庆理工大学学报（自然科学）》2024年第7期174-179,共6页Journal of Chongqing University of Technology：Natural Science

基　　金：国家自然科学基金项目(61873244)。

摘　　要：围绕脉动加载下的疲劳损伤演化,基于振动信号的测量数据,应用非线性常微分方程建立周期振动信号的参数化建模与损伤演化检测方法。采用多项式逼近非线性函数的策略,给出非线性常微分方程模型的最小二乘辨识方法;针对测量数据中的噪声导致参数估计偏差的问题,采用谱分析算法剔除数据中的噪声干扰;基于辨识得到的非线性常微分方程模型,建立疲劳损伤的非线性特征参数;通过脉动疲劳试验,验证了所提出方法的有效性。To investigate the fatigue damage evolution under cyclic fatigue loading,based on measured vibration data,a nonlinear ordinary differential equation(ODE)is applied to build a parametric model for periodic vibration signals,and then is applied for fatigue damage detection.First,the polynomial approximation of nonlinear function is employed to yield the least squares estimator of the nonlinear ODE.Second,the spectral analysis method is adopted to eliminate the disturbing noise of vibration data to reduce parameter estimation bias caused by the measurement noise;and then,the nonlinear characteristic parameters of fatigue damage are built by using the identified nonlinear ODE.Finally,the effectiveness of the proposed method is verified through a cyclic fatigue test.

关 键 词：脉动疲劳 周期信号 非线性常微分方程 损伤演化 

分 类 号：TB535[理学—物理]