Frequency Response Function Based Updating of a Laser Spot Welded Structure using Synthesised Frequency Response Function

被引:3
|
作者
Zin, M. S. Mohd [1 ]
Rani, M. N. Abdul [1 ]
Yunus, M. A. [1 ]
Mirza, W. I. I. Wan Iskandar [1 ]
Ayub, M. A. [1 ]
Omar, R. [2 ]
机构
[1] Univ Teknol MARA UiTM, SDAV, Fac Mech Engn, Shah Alam 40450, Selangor, Malaysia
[2] SIRIM Ind Res, Machinery Technol Ctr, Hulu Selangor 44200, Selangor, Malaysia
来源
1ST SOUTH ACEH INTERNATIONAL CONFERENCE ON ENGINEERING AND TECHNOLOGY (SAICOET) | 2019年 / 506卷
关键词
frequency response function; model updating; synthesised FRF; laser spot weld; MODEL; DYNAMICS;
D O I
10.1088/1757-899X/506/1/012012
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Accurate analytical models of engineering structures are of paramount importance for dynamicists to be used in predicting the dynamic behaviour (frequency response function) of the structures. The finite element method (FEM) and the experimental modal analysis (EMA) have been known as powerful and useful methods that can be used to determine the frequency response function (FRF) of the structures. However, the finite element FRF are often not in good agreement with experimental FRF due to assumption properties in finite element (FE) model. Therefore, in order to have a reliable FE model of a structure, measured FRF obtained from the experimental modal analysis can be integrated with finite element FRF to reconcile the FE model and the procedures involved in the reconciliation is a model updating process. Prior performing the updating process, the experimental FRF must be in good quality to obtain accurate FE model results. One way to reduce noise data and eliminate suspicious modes in FRF data is to use the FRF synthesised method. The main goal of this study is to use frequency response function based updating to minimise the error of a laser spot welded structure by using FRF synthesised data. In this work, MSC Software and LMS Test Lab were used to predict and measured the FRF of laser spot welded structure. The results revealed that FRF based updating method is successfully reduced the correlation gap between synthesised FRF and predicted FRF.
引用
收藏
页数:7
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