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Entropy 2017, 19(2), 49;

Entropy-Based Method for Evaluating Contact Strain-Energy Distribution for Assembly Accuracy Prediction

School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Authors to whom correspondence should be addressed.
Academic Editor: Dawn E. Holmes
Received: 6 December 2016 / Revised: 12 January 2017 / Accepted: 19 January 2017 / Published: 24 January 2017
(This article belongs to the Special Issue Maximum Entropy and Its Application II)
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Assembly accuracy significantly affects the performance of precision mechanical systems. In this study, an entropy-based evaluation method for contact strain-energy distribution is proposed to predict the assembly accuracy. Strain energy is utilized to characterize the effects of the combination of form errors and contact deformations on the formation of assembly errors. To obtain the strain energy, the contact state is analyzed by applying the finite element method (FEM) on 3D, solid models of real parts containing form errors. Entropy is employed for evaluating the uniformity of the contact strain-energy distribution. An evaluation model, in which the uniformity of the contact strain-energy distribution is evaluated in three levels based on entropy, is developed to predict the assembly accuracy, and a comprehensive index is proposed. The assembly experiments for five sets of two rotating parts are conducted. Moreover, the coaxiality between the surfaces of two parts with assembly accuracy requirements is selected as the verification index to verify the effectiveness of the evaluation method. The results are in good agreement with the verification index, indicating that the method presented in this study is reliable and effective in predicting the assembly accuracy. View Full-Text
Keywords: evaluation; entropy; assembly accuracy; contact strain energy evaluation; entropy; assembly accuracy; contact strain energy

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Fang, Y.; Jin, X.; Huang, C.; Zhang, Z. Entropy-Based Method for Evaluating Contact Strain-Energy Distribution for Assembly Accuracy Prediction. Entropy 2017, 19, 49.

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