结合面非线性特性对法兰螺栓连接动态性能的影响

Effects of Non-Linear Characteristics of Joint Surface on Dynamic Performance of Flange Bolt Connection

关键词:  结合面  非线性特性  动力学分析  预应力模态

Key words:  Joint surface  Nonlinear characteristics  Dynamics analysis  Pre-stressed modal

摘要:

为研究结合面非线性特性对法兰螺栓连接结构动态性能的影响，基于有限元分析与试验相结合的方法，首先，针对“L”型连接梁建立了完全bonded(绑定)、螺栓位置bonded和全摩擦三种模型并进行模态分析和动力学响应分析，研究发现后两种模型的结果比较接近且具有阻尼非线性特征。然后，建立了较复杂的薄壁机匣模型，研究了摩擦非线性和预紧力对其结构响应的影响，发现摩擦非线性因素对激励方向响应的影响较小，但对非激励方向响应的影响较大；加大预紧力可使完全bonded模型和全摩擦模型之间的误差减少到10%左右。最后，采用预应力模态法研究了结合面摩擦系数对薄壁机匣动力学特性的影响，结果表明摩擦系数对结构固有频率影响显著。模态试验结果与预应力模态计算结果误差在5.1%以内，验证了预应力模态法处理结合面非线性因素的有效性。

Abstract:

To study the influences of the nonlinear characteristics in the joint surface for dynamic performance of bolted flange connections， a method based on the combination of finite element analysis and experiment was proposed. Three models of complete bonded， bolt position bonded and complete friction were established for the L type connection beam， and modal analysis and dynamic response analysis were carried out. It was found that the responses of the latter two models are consistent and have damping nonlinear characteristics. Then， a more complex thin-walled casing model was established. The effects of the friction nonlinearity and the preload on the structural response were studied. It was found that the friction nonlinearity has little effect on the excitation direction， but the effect on the non-excitation direction was greater. Increasing the preload can reduce the error between the complete bonded model and the complete friction model to about 10%. Finally， influences of the friction coefficient of the joint surface on the dynamic characteristics of the thin-walled casing were studied by the pre-stressed modal method. The results show that the friction coefficient has a significant effect on the natural frequency of the structure. The error of the modal test results and the pre-stressed modal is less than 5.1%， which verifies the effectiveness of the pre-stressed modal method in dealing with the non-linear factors.