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Prediction of vibration characteristics of a planar mechanism having imperfect joints using neural network
Selçuk Erkaya
The Journal of Mechanical Science and Technology, vol. 26, no. 5, pp.1419-1430, 2012
Abstract : "Clearance is inevitable in the joints of mechanisms due primarily to the design, manufacturing and assembly processes or a wear effect.
Excessive value of joint clearance plays a crucial role and has a significant effect on the kinematic and dynamic performances of the
mechanism. In this study, effects of joint clearances on bearing vibrations of mechanism are investigated. An experimental test rig is set
up, and a planar slider-crank mechanism having two imperfect joints with radial clearance is used as a model mechanism. Three accelerometers
are positioned at different points to measure the bearing vibrations during the mechanism motion. For the different running
speeds and clearance sizes, this work provides a neural model to predict and estimate the bearing vibrations of the mechanical systems
having imperfect joints. The results show that radial basis function (RBF) neural network has a superior performance for predicting and
estimating the vibration characteristics of the mechanical system."
Keyword : Bearing vibration; Gaussian function; Joint clearance; Planar mechanism; RBF neural network |
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