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Grindability Evaluation of Ultrasonic Assisted Grinding of Silicon Nitride Ceramic Using Minimum Quantity Lubrication Based SiO_(2)Nanofluid

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Chinese Journal of Mechanical Engineering 2024年第2期37卷 115-136页

作者： yusuf suleiman dambatta Changhe Li Mohd Sayuti Ahmed A D Sarhan Min Yang Benkai Li Anxue Chu Mingzheng Liu Yanbin Zhang Zafar Said Zongming Zhou School of Mechanical and Automotive Engineering Qingdao University of TechnologyQingdao 266520China Mechanical Engineering Department Ahmadu Bello UniversityZaria 810106Nigeria Mechanical Engineering Department University of Malaya50603 Kuala LumpurMalaysia Department of Mechanical Engineering King Fahd University of Petroleum&Minerals31261 DhahranSaudi Arabia State Key Laboratory of Ultra-Precision Machining Technology Department of Industrial and Systems Engineer-ingThe Hong Kong Polytechnic UniversityHong KongChina College of Engineering University of Sharjah27272 SharjahUnited Arab Emirates Hanergy(Qingdao)Lubrication Technology Co. Ltd.Qingdao 266100China

Minimum quantity Lubrication(MQL)is a sustainable lubrication system that is famous in many machining *** involve the spray of an infinitesimal amount of mist-like lubricants during machining *** MQL system is affirmed to exhibit an excellent machining performance,and it is highly *** nanofluids are understood to exhibit excellent lubricity and heat evacuation capability,compared to pure oil-based MQL *** have shown that the surface quality and amount of energy expended in the grinding operations can be reduced considerably due to the positive effect of these *** work presents an experimental study on the tribological performance of SiO_(2)nanofluid during grinding of Si_(3)N_(4)*** effect different grinding modes and lubrication systems during the grinding operation was also *** concentrations of the SiO_(2)nanofluid was manufactured using canola,corn and sunflower *** quantitative evaluation of the grinding process was done based on the amount of grinding forces,specific grinding energy,frictional coefficient,and surface *** was found that the canola oil exhibits optimal lubrication performance compared to corn oil,sunflower oil,and traditional lubrication ***,the introduction of ultrasonic vibrations with the SiO_(2)nanofluid in MQL system was found to reduce the specific grinding energy,normal grinding forces,tangential grinding forces,and surface roughness by 65%,57%,65%,and 18%***,regression analysis was used to obtain an optimum parameter *** observations from this work will aid the smooth transition towards ecofriendly and sustainable machining of engineering ceramics.

关键词： Minimum quantity lubrication(MQL) Ultrasonic assisted grinding(UAG) Eco-friendly lubricants Nanofluid Grinding Ceramic

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Material Removal Mechanism and Force Modeling in Ultrasonic Vibration-Assisted Micro-Grinding Biological Bone

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Chinese Journal of Mechanical Engineering 2023年第5期36卷 20-44页

作者： Jingang Sun Changhe Li Zongming Zhou Bo Liu Yanbin Zhang Min Yang Teng Gao Mingzheng Liu Xin Cui Benkai Li Runze Li yusuf suleiman dambatta Shubham Sharma School of Mechanical and Automotive Engineering Qingdao University of TechnologyQingdao 266520China Hanergy(Qingdao)Lubrication Technology Co. Ltd.Qingdao 266520China Sichuan Future Aerospace Industry LLC. Shifang 618400China Department of Biomedical Engineering University of Southern CaliforniaLos AngelesCA 90089USA Mechanical Engineering Department Ahmadu Bello UniversityZaria 810106Nigeria Department of Mechanical Engineering and Advanced Materials Science Regional Center for Extension and DevelopmentCouncil of Scientifc and Industrial Research(CSIR)-Central Leather Research Institute(CLRI)Jalandhar 144021India

Micro-grinding with a spherical grinding head has been deemed an indispensable method in high-risk surgeries, such as neurosurgery and spine surgery, where bone grinding has long been plagued by the technical bottleneck of mechanical stress-induced crack damage. In response to this challenge, the ultrasound-assisted biological bone micro-grinding novel process with a spherical grinding head has been proposed by researchers. Force modeling is a prerequisite for process parameter determination in orthopedic surgery, and the difculty in establishing and accurately predicting bone micro-grinding force prediction models is due to the geometric distribution of abrasive grains and the dynamic changes in geometry and kinematics during the cutting process. In addressing these critical needs and technical problems, the shape and protrusion heights of the wear particle of the spherical grinding head were frst studied, and the gradual rule of the contact arc length under the action of high-speed rotating ultrasonic vibration was proposed. Second, the mathematical model of the maximum thickness of undeformed chips under ultrasonic vibration of the spherical grinding head was established. Results showed that ultrasonic vibration can reduce the maximum thickness of undeformed chips and increase the range of ductile and bone meal removals, revealing the mechanism of reducing grinding force. Further, the dynamic grinding behavior of diferent layers of abrasive particles under diferent instantaneous interaction states was studied. Finally, a prediction model of micro-grinding force was established in accordance with the relationship between grinding force and cutting depth, revealing the mechanism of micro-grinding force transfer under ultrasonic vibration. The theoretical model’s average deviations are 10.37% in x-axis direction, 6.85% in y-axis direction, and 7.81% in z-axis direction compared with the experimental results. This study provides theoretical guidance and technical sup

关键词： Spherical grinding head Gradual contact arc length Maximum undeformed chip thickness Microgrinding force

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端面铣削工件表面粗糙度数学模型与实验验证

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表面技术 2024年第4期53卷 125-139页

作者：刘德伟许芝令李长河秦爱国刘波张彦彬 yusuf suleiman dambatta 安庆龙青岛理工大学机械与汽车工程学院山东青岛266520 青岛海空压力容器有限公司山东青岛266000 青岛卡沃斯智能制造有限公司山东青岛266109 四川新航钛科技有限公司四川什邡618400 香港理工大学超精密加工技术国家重点实验室中国香港999077 艾哈迈杜·贝洛大学机械工程学院卡杜纳810106尼日利亚上海交通大学机械与动力工程学院上海200240

目的针对多种表面粗糙度影响因素的耦合作用使轮廓形成机理不清,导致表面粗糙度数学模型存在表面质量智能管控工业应用预测精度不足的技术难题,建立端面铣削工件表面粗糙度数学模型。方法首先,基于加工运动学机理和刀具几何学分析端面... 详细信息

目的针对多种表面粗糙度影响因素的耦合作用使轮廓形成机理不清,导致表面粗糙度数学模型存在表面质量智能管控工业应用预测精度不足的技术难题,建立端面铣削工件表面粗糙度数学模型。方法首先,基于加工运动学机理和刀具几何学分析端面铣削工件表面轮廓形成机理,建立考虑刀具跳动的工件表面轮廓模型以及轮廓高度偏差关于铣削力的补偿函数,并通过卷积神经网络(Convolution Neural Network,CNN)进行解析。其次,建立端面铣削表面粗糙度数学模型。最后,进行可转位面铣刀端面铣削ZG32MnMo的实验验证,分别采集轮廓数据与铣削力信号,建立以铣削力为输入、轮廓高度偏差数据为输出的铣削数据集,训练卷积神经网络解析轮廓高度补偿值并验证理论模型的准确性,对比分析考虑刀具跳动的表面粗糙度数学模型与CNN优化考虑刀具跳动的表面粗糙度数学模型的精度。结果CNN优化考虑刀具跳动的表面粗糙度数学模型对加工重叠区与非重叠区内沿刀具进给方向的轮廓算术平均偏差Ra的预测误差分别为18.71%和14.14%,与考虑刀具跳动的表面粗糙度数学模型相比,精度分别提高了10.61%和32.83%,CNN优化考虑刀具跳动的表面粗糙度数学模型对轮廓单元的平均宽度R_(sm)和支承长度率R_(mr(c))的预测结果与实验值吻合。结论考虑刀具跳动以及动态铣削力耦合作用边界条件的表面粗糙度数学模型能够有效预测端面铣削表面粗糙度,可为在质量管控工程中的应用提供理论指导与技术支撑。

关键词：铣削轮廓形成机理表面粗糙度铣削力刀具跳动卷积神经网络

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纳米生物润滑剂微量润滑磨削性能研究进展

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表面技术 2023年第12期52卷 1-19,I0005页

作者：宋宇翔许芝令李长河周宗明刘波张彦彬 yusuf suleiman dambatta 王大中青岛理工大学机械与汽车工程学院山东青岛266520 青岛海空压力容器有限公司山东青岛266520 汉能(青岛)润滑科技有限公司山东青岛266100 四川新航钛科技有限公司四川什邡618400 香港理工大学超精密加工技术国家重点实验室中国香港999077 艾哈迈杜·贝洛大学机械工程学院扎里亚810106 上海工程技术大学航空运输学院上海200240

微量润滑是针对浇注式和干磨削技术缺陷的理想替代方案,为了满足高温高压边界条件下磨削区抗磨减摩与强化换热需求,进行了纳米生物润滑剂作为微量润滑的雾化介质探索性研究。然而,由于纳米生物润滑剂的理化特性与磨削性能之间映射关系... 详细信息

微量润滑是针对浇注式和干磨削技术缺陷的理想替代方案,为了满足高温高压边界条件下磨削区抗磨减摩与强化换热需求,进行了纳米生物润滑剂作为微量润滑的雾化介质探索性研究。然而,由于纳米生物润滑剂的理化特性与磨削性能之间映射关系尚不清晰,纳米生物润滑剂作为冷却润滑介质在磨削中的应用仍然面临着严峻的挑战。为解决上述需求,本文基于摩擦学、传热学和工件表面完整性对纳米生物润滑剂的磨削性能进行综合性评估。首先,从基液和纳米添加相的角度阐述了纳米生物润滑剂的理化特性。其次,结合纳米生物润滑剂独特的成膜和传热能力,分析了纳米生物润滑剂优异的磨削性能。结果表明,纳米生物润滑剂优异的传热和极压成膜性能显著改善了磨削区的极端摩擦条件,相比于传统微量润滑,表面粗糙度值(Ra)可降低约10%~22.4%。进一步地,阐明了多场赋能调控策略下,磨削区纳米生物润滑剂浸润与热传递增效机制。最后,针对纳米生物润滑剂的工程和科学瓶颈提出了展望,为纳米生物润滑剂的工业应用和科学研究提供理论指导和技术支持。

关键词：磨削微量润滑纳米生物润滑剂多场赋能表面完整性理化特性

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Topography Modeling of Surface Grinding Based on Random Abrasives and Performance Evaluation

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Chinese Journal of Mechanical Engineering 2024年第5期 145-167页

作者： Yanbin Zhang Peng Gong Lizhi Tang Xin Cui Dongzhou Jia Teng Gao yusuf suleiman dambatta Changhe Li Key Lab of Industrial Fluid Energy Conservation and Pollution Control Qingdao University of Technology Ministry of Education School of Materials Science and Engineering Xi'an University of Technology College of Mechanical Engineering and Automation Liaoning University of Technology Mechanical Engineering Department Ahmadu Bello University

The surface morphology and roughness of a workpiece are crucial parameters in grinding processes. Accurate prediction of these parameters is essential for maintaining the workpiece's surface integrity. However, the randomness of abrasive grain shapes and workpiece surface formation behaviors poses significant challenges, and accuracy in current physical mechanism-based predictive models is needed. To address this problem, by using the random plane method and accounting for the random morphology and distribution of abrasive grains, this paper proposes a novel method to model CBN grinding wheels and predict workpiece surface roughness. First, a kinematic model of a single abrasive grain is developed to accurately capture the three-dimensional morphology of the grinding wheel. Next, by formulating an elastic deformation and formation model of the workpiece surface based on Hertz theory, the variation in grinding arc length at different grinding depths is revealed. Subsequently, a predictive model for the surface morphology of the workpiece ground by a single abrasive grain is devised. This model integrates the normal distribution model of abrasive grain size and the spatial distribution model of abrasive grain positions,to elucidate how the circumferential and axial distribution of abrasive grains influences workpiece surface ***, by integrating the dynamic effective abrasive grain model, a predictive model for the surface morphology and roughness of the grinding wheel is established. To examine the impact of changing the grit size of the grinding wheel and grinding depth on workpiece surface roughness, and to validate the accuracy of the model, experiments are conducted. Results indicate that the predicted three-dimensional morphology of the grinding wheel and workpiece surfaces closely matches the actual grinding wheel and ground workpiece surfaces, with surface roughness prediction deviations as small as 2.3%.

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Topography Modeling of Surface Grinding Based on Random Abrasives and Performance Evaluation

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CHINESE JOURNAL OF MECHANICAL ENGINEERING 2024年第1期37卷 1-23页

作者： Zhang, Yanbin Gong, Peng Tang, Lizhi Cui, Xin Jia, Dongzhou Gao, Teng dambatta, yusuf suleiman Li, Changhe Qingdao Univ Technol Key Lab Ind Fluid Energy Conservat & Pollut Contro Minist Educ Qingdao 266520 Peoples R China Xian Univ Technol Sch Mat Sci & Engn Xian 710048 Peoples R China Liaoning Univ Technol Coll Mech Engn & Automation Jinzhou 121001 Peoples R China Ahmadu Bello Univ Mech Engn Dept Zaria 810106 Nigeria

The surface morphology and roughness of a workpiece are crucial parameters in grinding processes. Accurate prediction of these parameters is essential for maintaining the workpiece's surface integrity. However, the randomness of abrasive grain shapes and workpiece surface formation behaviors poses significant challenges, and accuracy in current physical mechanism-based predictive models is needed. To address this problem, by using the random plane method and accounting for the random morphology and distribution of abrasive grains, this paper proposes a novel method to model CBN grinding wheels and predict workpiece surface roughness. First, a kinematic model of a single abrasive grain is developed to accurately capture the three-dimensional morphology of the grinding wheel. Next, by formulating an elastic deformation and formation model of the workpiece surface based on Hertz theory, the variation in grinding arc length at different grinding depths is revealed. Subsequently, a predictive model for the surface morphology of the workpiece ground by a single abrasive grain is devised. This model integrates the normal distribution model of abrasive grain size and the spatial distribution model of abrasive grain positions, to elucidate how the circumferential and axial distribution of abrasive grains influences workpiece surface formation. Lastly, by integrating the dynamic effective abrasive grain model, a predictive model for the surface morphology and roughness of the grinding wheel is established. To examine the impact of changing the grit size of the grinding wheel and grinding depth on workpiece surface roughness, and to validate the accuracy of the model, experiments are conducted. Results indicate that the predicted three-dimensional morphology of the grinding wheel and workpiece surfaces closely matches the actual grinding wheel and ground workpiece surfaces, with surface roughness prediction deviations as small as 2.3%.

关键词： Surface topography prediction Grinding Grinding wheel model Random plane method

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