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RISS 인기검색어
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- 저자 : Chris K. Mechefske (검색결과 2 건)
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Hanjun Jiang,Yimin Shao,Chris K. Mechefske,Xiaohui Chen 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.11
Due to either elastic deformations or errors in the manufacturing or assembling of gears, shafts, bearings and their housings, it is an inevitableconsequence that mesh misalignment between teeth occurs. The change in length of the contact line or the change in load distributionalong the length of the contact line induced by mesh misalignment causes changes in the dynamic characteristics of helical gears. There is currently no satisfactory solution for the modeling and calculation of the internal excitation in helical gears with mesh misalignmentand sliding friction that would reveal the changes in the dynamic characteristics. In this study, an improved calculation method offriction excitation is proposed based on the time-varying length of the contact line and the time-varying friction coefficient model in helicalgears. By considering the change in the mesh position and the change in the length of the contact line or the change of the displacementerror along the contact line induced by mesh misalignment, the time-varying sliding friction force and the dynamic mesh force maybe obtained. An eight degree-of-freedom analytical helical gear pair model is developed by incorporating the time-varying sliding frictionforce and dynamic mesh force and considering the mesh misalignment. By assuming a constant mesh stiffness density along the contactline, the rules governing the variation of the dynamic response are obtained using simulations of helical gear pair examples with differentfriction coefficient models and mesh misalignment. The developed analytical model provides a new method for the study of excitationcharacteristics in helical gears with mesh misalignment.
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Yimin Shao,Xiao Deng,Yilin Yuan,Chris K. Mechefske,Zaigang Chen 대한기계학회 2014 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.28 No.6
Detecting chatter mark vibration in rolling mills operating under normal working conditions is difficult. A novel characteristic recognitionmethod of chatter mark vibration, where the non-dimensional parameters are calculated with time varying signals and kurtosis undernormal rolling mill operating conditions, is presented in this paper. The character of the chatter mark vibration signal is obtained by calculatingthe kurtosis value of each vibration signal segment obtained by subdividing the raw time varying vibration signal. The probabilitydensity function is utilized to reveal obvious differences between signals with respect to the normal and chatter conditions. Themethod overcomes the limitation of traditional spectrum analysis, which is sensitive to working conditions. Numerical simulation andexperimental results show that the proposed method has better recognition capability than traditional spectrum analysis.
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