Investigation of the grinding temperature and subsurface quality of a novel point grinding wheel

Yin, Guoqiang; Gong, Yadong; Li, Youwei; Wang, Fei

doi:10.1007/s00170-018-2055-1

Cited by 6 publications

(5 citation statements)

References 19 publications

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“…The reward mechanism constructs a three-layer competitive neural network predictive sample clustering model. It then uses the improved stochastic gradient enhancement method [ 17 ] to train model parameters, update the clustering center, and finally, use the clustering center of the most competitive neuron as the base center.…”

Section: Prediction Model Of Surface Roughness Of Abrasive Belt Grinding Of Superalloy Materialsmentioning

confidence: 99%

“…They solved the coefficients through grinding experiments to obtain the relationship between processing parameters on roughness and topography. Yi et al [ 17 ] studied the surface quality of the new grinding wheel after grinding, analyzed the angle of the grinding zone and grinding parameters, and analyzed the surface quality after grinding. The optimal process parameters of surface quality were obtained.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Surface Roughness of Abrasive Belt Grinding of Superalloy Material Based on RLSOM-RBF

et al. 2021

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It is difficult to accurately predict the surface roughness of belt grinding with superalloy materials due to the uneven material distribution and complex material processing. In this paper, a radial basis neural network is proposed to predict surface roughness. Firstly, the grinding system of the superalloy belt is introduced. The effects of the material removal process and grinding parameters on the surface roughness in belt grinding were analyzed. Secondly, an RBF neural network is trained by reinforcement learning of a self-organizing mapping method. Finally, the prediction accuracy and simulation results of the proposed method and the traditional prediction method are analyzed using the ten-fold cross method. The results show that the relative error of the improved RLSOM-RBF neural network prediction model is 1.72%, and the R-value of the RLSOM-RBF fitting result is 0.996.

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Section: Prediction Model Of Surface Roughness Of Abrasive Belt Grinding Of Superalloy Materialsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction of Surface Roughness of Abrasive Belt Grinding of Superalloy Material Based on RLSOM-RBF

et al. 2021

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“…The quality of the surface of the machined part is determined, in addition to the cutting modes and the initial condition of the working surface of the grinding wheel, the conditions of editing the wheel, and the change of the working surface during operation [10].…”

Section: Literature Reviewmentioning

confidence: 99%

Influence of the Cutting Temperature on the Surface Layer Quality When Grinding Sintered Porous Materials

Zabolotnyi

Bozhko

Machado

et al. 2021

Lecture Notes in Mechanical Engineering

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One of the features of sintered materials is porosity. Depending on the application, this can be both a disadvantage and an advantage. The porosity geometry affects the propagation of heat during the grinding of the sintered material. An experimental study of the temperature in the cutting zone during the grinding of sintered porous materials was carried out. The relationship between the contact temperature in the cutting zone, the parameters of the cutting modes during grinding, and the porosity of the part is revealed. It was found that the use of process coolants is not always possible due to the presence of pores in the material. It is proved that the cutting temperature of porous materials is higher due to the deteriorated heat dissipation properties, but the cutting temperature does not affect the degree of compaction of the surface layers of the powder material. An adequate mathematical model is obtained, which describes the change of cutting temperature depending on the material's cutting depth, grinding speed, and porosity.

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“…According to the symmetry of (001) crystal plane, the elastic modulus of (001) crystal plane can be written as formula (13).…”

Section: Analysis Of Elastic Modulus On Nickel-based Single-crystal Smentioning

confidence: 99%

“…Zhu et al [12] proposed a new calculation model of grinding temperature based on the geometry and distribution of abrasives. Yin et al [13] used a novel point grinding wheel to simulate the grinding temperature and analyzed the influence of grinding parameters on the grinding temperature. Aimed at the existing limitations of calculating the grinding energy introduction lead-in ratio, Wang et al [14] proposed a new method of calculating grinding energy lead-in ratio.…”

Section: Introductionmentioning

confidence: 99%

Study on force and temperature characteristics of micro-grinding nickel-based single-crystal superalloy

Zhou

Gong

et al. 2019

J Braz. Soc. Mech. Sci. Eng.

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Aiming at the status of fewer researches on the anisotropy of single-crystal superalloy and micro-grinding temperature field, micro-grinding using the tool of < 1 mm in diameter to remove material is the final procedure of machining micro-parts. This paper firstly analyzes the anisotropy of surface-centered cubic structural material and establishes the theoretical model of elastic modulus and shearing modulus of single-crystal superalloy in the (001), (110) and (111) crystal plane. Afterward, it builds the three-dimensional simulation model of grinding temperature based on the Hill model, adopts any Lagrangian-Euler method to realize the simulation of micro-grinding temperature, gets the distribution of temperature field and changing situation during the micro-grinding through single-factor experiment and simulation analysis, and makes a study on the laws of different grinding depths, feeding rates, grinding velocities, different crystal planes {(001), (110) and (111)} and different crystal orientations in (001) crystal plane that affect the micro-grinding temperature, thus obtaining the crystal orientation which produces low grinding force and temperature. The result indicates that the grinding temperature increases with the increase in spindle speed, feeding rate and grinding depth; the grinding force and temperature are proportional to the elastic modulus and shearing modulus of the single-crystal material; the grinding temperature along (111) crystal plane is the highest, that of the (110) crystal plane is at the middle, and that along (001) is the lowest. When grinding in the (001) crystal plane, the normal grinding force and temperature along [110], [110] , [110] , [110] crystal orientations are the highest, and those along [100], [010], [100] , [010] crystal orientations are the lowest. And along with the aggravating of wear of abrasives on the grinding tool, the normal grinding force, tangential grinding force and grinding temperature all increase and the wear state of grinding tool can be judged online according to the signal of grinding force and temperature. These results provide an important evidence to do further research on the surface integrity of grinding single-crystal superalloy.

show abstract

Investigation of the grinding temperature and subsurface quality of a novel point grinding wheel

Cited by 6 publications

References 19 publications

Prediction of Surface Roughness of Abrasive Belt Grinding of Superalloy Material Based on RLSOM-RBF

Prediction of Surface Roughness of Abrasive Belt Grinding of Superalloy Material Based on RLSOM-RBF

Influence of the Cutting Temperature on the Surface Layer Quality When Grinding Sintered Porous Materials

Study on force and temperature characteristics of micro-grinding nickel-based single-crystal superalloy

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