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Force analysis of bearings on a modified mechanism using proposed recurrent hybrid neural networks
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  • Force analysis of bearings on a modified mechanism using proposed recurrent hybrid neural networks
  • Force analysis of bearings on a modified mechanism using proposed recurrent hybrid neural networks
저자명
Yildirim. Sahin,Eski. Ikbal,Kalkat. Menderes
간행물명
Journal of mechanical science and technology
권/호정보
2008년|22권 7호|pp.1323-1329 (7 pages)
발행정보
대한기계학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Due to different load conditions on four-bar mechanisms, it is necessary to analyze force distribution on the bearing systems of mechanisms. A proposed neural network was developed and designed to analyze force distribution on the bearings of a four bar mechanism. The proposed neural network has three layers: input layer, output layer and hidden layer. The hidden layer consists of a recurrent structure to keep dynamic memory for later use. The mechanism is an extended version of a four-bar mechanism. Two elements, spring and viscous, are employed to overcome big force problem on the bearings of the mechanism. The results of the proposed neural network give superior performance for analyzing the forces on the bearings of the four-bar mechanism undergoing big forces and high repetitive motion tracking. This continuation of simulation analysis of bearings should be a benefit to bearing designers and researchers of such mechanisms.