scholarly journals Model Updating of Spindle Systems Based on the Identification of Joint Dynamics

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Hongrui Cao ◽  
Songtao Xi ◽  
Wei Cheng
Keyword(s):  
Machine Tool ◽  
Degrees Of Freedom ◽  
Model Updating ◽  
Joint Stiffness ◽  
Iteration Process ◽  
Fe Model ◽  
Receptance Coupling ◽  
Joint Dynamics ◽  
The Difference ◽  
Fe Model Updating

In order to simulate the cutting performance of a spindle mounted in the machine tool, the finite element (FE) model of spindles is required to be coupled with machine tool. However, the unknown joint dynamics (e.g., bolts) between the spindle and machine tool column limit the accuracy of the model. In this paper, an FE model updating method is proposed based on the identification of joint dynamics in both translational and rotational degrees-of-freedom (DOF). The receptance coupling (RC) technique is enhanced to estimate frequency response functions (FRFs) corresponding to rotational DOFs. The joint stiffness is identified through the iteration process by minimizing the difference between the simulated FRF and the measured FRF of the assembly. The proposed method is verified with a machine-tool spindle system. The good agreement between simulation and experiment shows the effectiveness of the method.

Finite Element Model Updating of Machine-Tool Spindle Systems

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Hongrui Cao ◽  
Bing Li ◽  
Zhengjia He
Keyword(s):  
Finite Element ◽  
Machine Tool ◽  
Model Updating ◽  
Joint Stiffness ◽  
Coupled Model ◽  
Iteration Process ◽  
Element Model ◽  
Fe Model ◽  
Machine Tool Spindle ◽  
Fe Model Updating

The unknown joint dynamics are the main obstacle that limits the accuracy of the finite element (FE) model of a machine-tool spindle assembly. In this paper, an FE model updating method is proposed to assist industrial engineers in achieving a reliable model that can accurately represent the dynamic characteristics of machine-tool spindle systems. In the proposed FE model updating procedure, the iterative algorithm based on frequency response functions (FRFs) is applied. The joint stiffness parameters are identified through the iteration process, while the FE model is updated simultaneously. The proposed method was applied to update an existing coupled model of a machine-tool spindle system. The experimental results show that the identified joint stiffness parameters are acceptable and the dynamic behavior of the spindle mounted in the machine tool column is predicted reliably.

scholarly journals Vision-Based Structural FE Model Updating Using Genetic Algorithm

2021 ◽  
Vol 11 (4) ◽  
pp. 1622
Author(s):  
Gun Park ◽  
Ki-Nam Hong ◽  
Hyungchul Yoon
Keyword(s):  
Genetic Algorithm ◽  
Model Updating ◽  
Structural Parameters ◽  
Fe Model ◽  
Structural Members ◽  
Stiffness Reduction ◽  
Before And After ◽  
Scale Test ◽  
Fe Model Updating ◽  
Story Building

Structural members can be damaged from earthquakes or deterioration. The finite element (FE) model of a structure should be updated to reflect the damage conditions. If the stiffness reduction is ignored, the analysis results will be unreliable. Conventional FE model updating techniques measure the structure response with accelerometers to update the FE model. However, accelerometers can measure the response only where the sensor is installed. This paper introduces a new computer-vision based method for structural FE model updating using genetic algorithm. The system measures the displacement of the structure using seven different object tracking algorithms, and optimizes the structural parameters using genetic algorithm. To validate the performance, a lab-scale test with a three-story building was conducted. The displacement of each story of the building was measured before and after reducing the stiffness of one column. Genetic algorithm automatically optimized the non-damaged state of the FE model to the damaged state. The proposed method successfully updated the FE model to the damaged state. The proposed method is expected to reduce the time and cost of FE model updating.

A Method for FE Model Updating of Coupled Vibro-Acoustic Systems Using Constrained Optimization

2013 ◽  
Author(s):  
D. V. Nehete ◽  
S. V. Modak ◽  
K. Gupta
Keyword(s):  
Finite Element ◽  
Constrained Optimization ◽  
Model Updating ◽  
Numerical Study ◽  
Element Model ◽  
Rectangular Cavity ◽  
Mode Shapes ◽  
Fe Model ◽  
Structural Dynamic ◽  
Fe Model Updating

Finite element (FE) model updating is now recognized as an effective approach to reduce modeling inaccuracies present in an FE model. FE model updating has been researched and studied well for updating FE models of purely structural dynamic systems. However there exists another class of systems known as vibro-acoustics in which acoustic response is generated in a medium due to the vibration of enclosing structure. Such systems are commonly found in aerospace, automotive and other transportation applications. Vibro-acoustic FE modeling is essential for sound acoustic design of these systems. Vibro-acoustic system, in contrast to purely structural system, has not received sufficient attention from FE model updating perspective and hence forms the topic of present paper. In the present paper, a method for finite element model updating of coupled structural acoustic model, constituted as a problem of constrained optimization, is proposed. An objective function quantifying error in the coupled natural frequencies and mode shapes is minimized to estimate the chosen uncertain parameters of the system. The effectiveness of the proposed method is validated through a numerical study on a 3D rectangular cavity attached to a flexible panel. The material property and the stiffness of joints between the panel and rectangular cavity are used as updating parameters. Robustness of the proposed method under presence of noise is investigated. It is seen that the method is not only able to obtain a close match between FE model and corresponding ‘measured’ vibro-acoustic characteristics but is also able to estimate the correction factors to the updating parameters with reasonable accuracy.

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