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Rheological Characteristics and Behavior Prediction of Lubricating Grease for an RV Reducer Across a Wide Temperature Range
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  • Benchi Jiang,
  • yansheng zhou,
  • Jiabao Pan,
  • Zhijian Tu
Benchi Jiang
Anhui Polytechnic University
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yansheng zhou
Anhui Polytechnic University
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Jiabao Pan
Anhui Polytechnic University

Corresponding Author:[email protected]

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Zhijian Tu
Wuhu Sai bao Robot Industry Technology Research Institute Co, Ltd
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Abstract

Grease in the normal operation of the RV reducer has a role that can not be ignored, for the variable working conditions of the RV reducer, the performance of the lubricant changes directly affect its reliable operation. Therefore, the study of the rheological properties of the grease has become the focus of the study of RV reducer performance.In this paper, SK-1A grease is taken as the research object, and its rheological characteristics under wide temperature range working conditions (-20℃~40℃) are investigated through rheological experiments, to analyze the potential influence of SK-1A grease on the performance of RV reducer.In addition, to better study the rheological properties of grease under different working conditions, the Elman neural network model was used to predict the rheological properties of grease based on the rheological experiments of grease, and the results were compared with those of the BP neural network and the RBF neural network.The prediction accuracy of the Elman neural network model was assessed using Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) in a cross-validation approach.The results show that the viscoelastic properties of SK-1A grease generally show a decreasing trend as the temperature rises in a wide temperature range, and the degree of entanglement of soap fibers decreases more obviously, but its fluidity is more stable.The results of the three neural network prediction models show that the Elman neural network model used for the prediction of grease rheological properties shows high prediction accuracy, and the model can provide a valuable theoretical reference for the accurate prediction of the rheological properties of grease affected by complex multifactor.
19 Aug 2023Submitted to The Journal of Engineering
23 Aug 2023Assigned to Editor
23 Aug 2023Submission Checks Completed
25 Aug 2023Reviewer(s) Assigned
14 Sep 2023Review(s) Completed, Editorial Evaluation Pending
15 Sep 2023Editorial Decision: Revise Major
19 Oct 20231st Revision Received