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Prediction of Leakage from an Axial Piston Pump Slipper with Circular Dimples Using Deep Neural Networks

《中国机械工程学报:英文版》2020年 第2期 | Ozkan Ozmen Cem Sinanoglu Abdullah Caliskan Hasan Badem   Tribology Laboratory Industrial Design Engineering Faculty of Engineering Erciyes University Kayseri 38039 Turkey Biomedical Engineering Faculty of Engineering and Natural Sciences Iskenderun Technical University Hatay Turkey Computer Engineering Faculty of Engineering and Architecture KahramanmaraşSutcu Imam University Kahramanmaraş Turkey
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摘 要:Oil leakage between the slipper and swash plate of an axial piston pump has a significant effect on the efficiency of the pump.Therefore,it is extremely important that any leakage can be predicted.This study investigates the leakage,oil film thickness,and pocket pressure values of a slipper with circular dimples under different working conditions.The results reveal that flat slippers suffer less leakage than those with textured surfaces.Also,a deep learning-based framework is proposed for modeling the slipper behavior.This framework is a long short-term memory-based deep neural network,which has been extremely successful in predicting time series.The model is compared with four conventional machine learning methods.In addition,statistical analyses and comparisons confirm the superiority of the proposed model.
【分 类】【工业技术】 > 机械、仪表工业 >
【关键词】 Slipper LEAKAGE Circular dimpled Long short-term memory Deep neural network
【出 处】 《中国机械工程学报:英文版》2020年 第2期 111-121页 共11页
【收 录】 中文科技期刊数据库