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| Content Provider | Springer Nature Link |
|---|---|
| Author | Sohn, Jeong Hyun Lee, Seung Kyu Ok, Jin Kyu Yoo, Wan Suk |
| Copyright Year | 2007 |
| Abstract | Since bushing components have highly nonlinear characteristics according to the amplitude and the frequency, it is hard to derive a mathematical modeling of the bushing. In this paper, a semi-physical bushing model and a black-box bushing model are derived and compared. A Bouc-Wen hysteretic model is employed to derive a semi-physical model and an artificial neural network algorithm is used to make a black-box bushing model. A 3-axes MTS rubber test machine is used to capture the bushing characteristics. Sine excitation tests based on the different frequencies and different amplitudes are performed to find out the bushing characteristics. Random test results are also used to generate the coefficients of a semi-physical model and weighting factors of the black-box model. Random simulations are carried out to verify the bushing models and the results are compared with each other according to the numerical efficiency and accuracy. |
| Starting Page | 264 |
| Ending Page | 271 |
| Page Count | 8 |
| File Format | |
| ISSN | 1738494X |
| Journal | Journal of Mechanical Science and Technology |
| Volume Number | 21 |
| Issue Number | 2 |
| Language | English |
| Publisher | Korean Society of Mechanical Engineers |
| Publisher Date | 2007-01-01 |
| Publisher Place | Seoul |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Bushing Semi-Physical Model Black-Box Model Artificial Neural Network Mechanical Engineering Vibration, Dynamical Systems, Control Industrial and Production Engineering |
| Content Type | Text |
| Resource Type | Article |
| Subject | Mechanics of Materials Mechanical Engineering |
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