Abrasive Belt Grinding Research Articles

Novel method for monitoring chip heat in abrasive belt grinding based on decision-making fusion of vision and sound information

Novel method for monitoring chip heat in abrasive belt grinding based on decision-making fusion of vision and sound information

Fabricating ultra wear-resistant surfaces on titanium alloy by combining laser-induced modification with abrasive belt grinding

A novel method combining laser-induced modification and abrasive belt grinding (LM&BG) was proposed to prepare wear-resistant surfaces of titanium alloys. Comprehensively investigated the evolution mechanism of material modification and wear resistance of LM&BG samples. It was found that an oxide-ceramic-modified layer with increasing hardness (10 times) was formed by laser modification on the titanium alloy, mainly composed of TiO2, with the two phases Rutile-TiO2 and Anatase-TiO2. Moreover, the surface roughness after abrasive belt grinding of the modified layer is less than Ra0.1, with a uniform subsurface microstructure. Interestingly, the wear modes of the modified layer shifted from adhesive and oxidative wear to brittle microdetachment, significantly reducing the coefficient of friction, material wear, and subsurface damage, thus improving the wear-resistant capability.

Use of machine learning models in condition monitoring of abrasive belt in robotic arm grinding process

AbstractAlthough the aspects that affect the performance and the deterioration of abrasive belt grinding are known, wear prediction of abrasive belts in the robotic arm grinding process is still challenging. Massive wear of coarse grains on the belt surface has a serious impact on the integrity of the tool and it reduces the surface quality of the finished products. Conventional wear status monitoring strategies that use special tools result in the cessation of the manufacturing production process which sometimes takes a long time and is highly dependent on human capabilities. The erratic wear behavior of abrasive belts demands machining processes in the manufacturing industry to be equipped with intelligent decision-making methods. In this study, to maintain a uniform tool movement, an abrasive belt grinding is installed at the end-effector of a robotic arm to grind the surface of a mild steel workpiece. Simultaneously, accelerometers and force sensors are integrated into the system to record its vibration and forces in real-time. The vibration signal responses from the workpiece and the tool reflect the wear level of the grinding belt to monitor the tool’s condition. Intelligent monitoring of abrasive belt grinding conditions using several machine learning algorithms that include K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and Decision Tree (DT) are investigated. The machine learning models with the optimized hyperparameters that produce the highest average test accuracy were found using the DT, Random Forest (RF), and XGBoost. Meanwhile, the lowest latency was obtained by DT and RF. A decision-tree-based classifier could be a promising model to tackle the problem of abrasive belt grinding prediction. The application of various algorithms will be a major focus of our research team in future research activities, investigating how we apply the selected methods in real-world industrial environments.

Evaluation of abrasive belt grinding performance in nickel-based superalloy robot grinding

ABSTRACT In order to evaluate the abrasive belt grinding performance, this paper proposes to conduct nickel-based superalloy robot abrasive belt grinding experiment based on different types of abrasive belts with multiple grit sizes. First, the single grinding performance evaluation is performed through five performance parameters: material removal rate, surface roughness, tangential force, specific grinding energy, and specific wear height. Then, based on the evaluation results of single grinding performance, a weighted evaluation function is established to comprehensively evaluate the grinding performance. It is found that the structured abrasive belt has relatively better grinding performance. The main factors affecting the abrasive belt grinding performance are identified through the evaluation results, with the effect of grit size being more significant. In addition, this paper analyzes the characteristics of material deformation based on the grinding subsurface microstructure, and discusses the effects of abrasive belts on material deformation.

Surface Roughness Prediction of Titanium Alloy during Abrasive Belt Grinding Based on an Improved Radial Basis Function (RBF) Neural Network.

Titanium alloys have become an indispensable material for all walks of life because of their excellent strength and corrosion resistance. However, grinding titanium alloy is exceedingly challenging due to its pronounced material characteristics. Therefore, it is crucial to create a theoretical roughness prediction model, serving to modify the machining parameters in real time. To forecast the surface roughness of titanium alloy grinding, an improved radial basis function neural network model based on particle swarm optimization combined with the grey wolf optimization method (GWO-PSO-RBF) was developed in this study. The results demonstrate that the improved neural network developed in this research outperforms the classical models in terms of all prediction parameters, with a model-fitting R2 value of 0.919.

Robotic abrasive belt grinding of complex curved blades based on a novel force control architecture integrating smooth trajectories

Constant force control and smooth trajectory planning are regarded as key strategies to improve the surface quality of blades in robotic abrasive belt grinding. However, some technical challenges still remain: (1) external normal grinding force with time-consuming sensing, large fluctuations, and force overshoot, and (2) lack of global C2 continuous grinding trajectories. In this paper, a unified architecture is proposed to concurrently address the above issues. The main contribution of this paper is to provide a complete solution for robots to automatically accomplish the grinding of complex curved blades. The grinding process is arranged as follows: Firstly, cubic B-spline and C2 continuous quaternion spline curves are used to generate the global C2 continuous trajectory, thereby avoiding vibrations and unexpected slowdowns during grinding. Secondly, the actual grinding force is sensed based on a low-speed Fourier series trajectory and the least square algorithm. Finally, a novel force control scheme consisting of an adaptive hybrid impedance (AHI) control scheme and two nonlinear tracking differentiator (NTD) modules is proposed to overcome the problems of large force fluctuations and force overshoot. Experimental results demonstrate that the proposed solution delivers better performance. Furthermore, the surface roughness Ra of the machined blade is controlled within 0.8 μm, which meets the requirements of real-world industrial applications.

Sensitivity Study of Surface Roughness Process Parameters in Belt Grinding Titanium Alloys

In order to obtain the optimum range of process parameters for abrasive belt grinding of titanium alloys to achieve a surface roughness within a given range, titanium alloy TC4 was selected as the research object, and experiments on abrasive belt grinding surface roughness were conducted. Firstly, an empirical formula for the surface roughness of titanium alloys after abrasive belt grinding was constructed based on the balanced weight analysis of the process parameters for titanium alloy surface roughness. Sensitivity analysis was carried out to identify the process parameters with the greatest effect on surface roughness, and the stable and unstable domains of the process parameters were determined. Combined with range analysis in orthogonal experiments, the influence curves of the process parameters on surface roughness were obtained, and the optimal parameter ranges were selected. The research results showed that surface roughness is the most sensitive to changes in abrasive grain size and the least sensitive to changes in abrasive belt linear speed. The optimal ranges of abrasive grain size, abrasive belt linear speed, and grinding pressure were determined to be 120# to 150#, 15 m/s to 20 m/s, and 10 N to 15 N, respectively. This study provides a theoretical method and experimental basis for the control of surface roughness in abrasive belt grinding of titanium alloys.

Two-Phase fatigue life prediction method based on scSE U-net algorithm for abrasive belt grinding of titanium alloy

Two-Phase fatigue life prediction method based on scSE U-net algorithm for abrasive belt grinding of titanium alloy

CAN-Net: A Multi-hidden Layer Attention Deep Learning Method for Surface Roughness Prediction During Abrasive Belt Grinding of Superalloy with Local Weights

Nickel-based superalloys are widely employed in aerospace due to their excellent high-temperature strength, good oxidation resistance, and hot corrosion resistance. Abrasive belt grinding can effectively solve the problems of excessive residual stress and tool wear during the processing of superalloys. However, due to the grinding process being complex and changeable, and a wide range of affecting factors, the surface roughness prediction of abrasive belt grinding has become a challenging topic. In this study, a CAN-Net multi-hidden layer deep learning prediction model is established. The concatenate path is utilized to fuse local weights to optimize the intermediate weights of network training. To increase the predictability of the model, the attention mechanism is included to distribute the weights of the grinding parameters, and the impact of the attention mechanism on the prediction is then carefully analyzed. The results demonstrate that the CAN-Net network model has outstanding parameter flexibility and prediction accuracy, with accuracy reaching 0.984 and a correlation coefficient of 0.981 between the anticipated value and the true value.

Subsurface damage inhibiting and synchronous removal behavior of Cf/SiC composites with laser-induced controllable ablation during abrasive belt grinding

Aiming at improving the machinability of Cf/SiC composites, this study proposed laser-induced controlled ablation grinding (LICAG) method. Cf/SiC composites samples with various ablating depths were prepared through picosecond laser, which were then ground by abrasive belt. The results showed that Cf/SiC composites were sublimated in laser ablating zone, resulting in dentate grooves covered with loose SiO2 oxides products. The grinding force and temperature during LICAG could be decreased by up to 64.0% and 58.8%, respectively, compared with conventional grinding (CG). Carbon fiber fracture was reduced, SiC matrix and carbon fibers were removed almost synchronously during LICAG; therefore, the surface quality was improved. Moreover, subsurface micro cracks were found near the grinding surface but did not propagate downward along the fibers. Grinding chips of CG were primarily broken fibers and broken SiC matrix; on the contrary, those generated during LICAG were mostly regular fiber bundles connected to SiC matrix.

Effects of feed direction on material removal behavior in belt grinding of titanium alloys

For abrasive belt grinding, although machine processing selection has been well studied to achieve good machinability, there is still a lack of understanding regarding the influence of feed direction and its mechanism, even though it is a common matter. This paper investigates the differences between up- and down-grinding in belt grinding of TC4, where the grinding forces, material removal performance, surface quality, and chip morphology are captured for the grinding process evaluation and mechanistic analysis In up grinding, it was observed that approximately 21.1 % more material removal can be achieved due to the larger penetration depth of scratching grains when maintaining a constant normal grinding force. Furthermore, the higher tangential grinding force resulting from increased cutting behavior and an additional sliding phase leads to more severe abrasive belt wear, as evidenced by a 22.7 % higher grinding ratio. Comparatively, down grinding mode generates a machined surface with lower roughness in the transverse and longitudinal direction, which can be explained by the minimum chip thickness effect and undeformed chip thickness model. The microscopic characteristics of chips and ground surface provide more evidence on the different chip formation mechanisms between two grinding modes.

Calculation of envelope area between grinding tool and curved surface

Typical aerospace curved surface parts have high contour accuracy, which directly affects the working performance and service life of the equipment. To improve the contour accuracy of these parts, the freestyle abrasive belt grinding technology can be employed, where the size of the envelope area determines the material removal volume. However, due to the complex contour of the curved surface and large contact deformation of the belt, the envelope area between the flexible belt and curved surface parts is complex and time-varying. The accurate calculation of the envelope area is still an open problem. To this end, a novel locally approximate distance fields-mass spring systems (LADF-MSS) method is proposed. Firstly, the improved distance field is established accurately: the octree is applied to search for the reference point where the curved surface is a local quadric approximation, and then the projection point is calculated based on the reference point. Secondly, the locally approximate distance field is combined with efficient mass-spring systems to extract the envelope area. The experimental results of grinding the curved surface show that the average area error and average centroid error of the envelope area are 0.7 mm2 and 1.08 mm respectively, and the average computing time is 7.5 min. Compared with the finite element method (FEM), the average calculation errors through utilizing the LADF-MSS method are reduced by 40.3% and 76.4% respectively, and calculation efficiency is increased by 166%. These results demonstrate that the proposed method offers both higher calculation accuracy and efficiency.

Multi-dimensional ultrasonic-assisted belt grinding on the surface integrity of Inconel 718

In order to meet the requirements of the isotropic high-performance machining of complex surfaces, this paper proposed three-dimensional ultrasonic assisted belt grinding (3D-UABG) method that integrates the advantages of surface strengthening and isotropic machining, analyzed the motion characteristics and surface formation laws. Then, the influence of ultrasonic vibrations on the surface integrity of Inconel 718 was studied by a self-designed 3D-UABG device. Finally, the surface formation mechanism was revealed combined with the surface integrity and abrasive grain motion characteristic. Results showed that compared with conventional abrasive belt grinding (CABG), the abrasive grain in normal-ultrasonic assisted belt grinding (N-UABG) reduced the height of texture peak formed an intermittent texture, which makes it have smallest surface roughness. At the same time, the high-frequency impact of abrasive grains not only increased the surface plastic deformation, but also realized the impact strengthening. Planar two-dimensional ultrasonic assisted belt grinding (2D-UABG) reduced the directionality difference of surface quality. However, the deflection characteristics of abrasive grains make it have a large surface roughness. The 3D-UABG surface has good comprehensive mechanical properties. The abrasive grains have three-dimensional dynamic characteristics in space, which effectively inhibit anisotropic stress state, promote uniform deformation, and helpful to obtain approximately isotropic surface texture and small surface roughness. On the one hand, the in-plane motion characteristics of planar two-dimensional ultrasonic vibration gave grinding surface more uniform surface integrity. On the other hand, the spatial motion trajectory of abrasive grains driven by three-dimensional ultrasonic vibration made it have a slow increased cutting depth, which avoided the tear damage caused by materials plastic accumulation and the large roughness caused by abrasive deflection under large cutting depth. In 3D-UABG, lower feed speed and amplitude and linear velocity matched to grinding parameters contribute to the improved surface integrity. This study has guiding significance for the development and engineering application of ultrasonic-assisted belt grinding technology.

Modeling and Experimental Verification of Time-Controlled Grinding Removal Function for Optical Components.

As a flexible grinding method with high efficiency, abrasive belt grinding has been widely used in the machining of mechanical parts. However, abrasive belt grinding has not been well applied in the field of ultra-precision optical processing, due to the lack of a stable and controllable removal function. In this paper, based on the idea of deterministic machining, the time-controlled grinding (TCG) method based on the abrasive belt as a machining tool was applied to the deterministic machining of optical components. Firstly, based on the Preston equation, a theoretical model of the TCG removal function was established. Secondly, removal function experiments were carried out to verify the validity and robustness of the theoretical removal model. Further, theoretical and actual shaping experiments were carried out on 200 mm × 200 mm flat glass-ceramic. The results show that the surface shape error converged from 6.497 μm PV and 1.318 μm RMS to 5.397 μm PV and 1.115 μm RMS. The theoretical and experimental results are consistent. In addition, the surface roughness improved from 271 to 143 nm Ra. The results validate the concept that the removal function model established in this paper can guide the actual shaping experiments of TCG, which is expected to be applied to the deterministic machining of large-diameter optical components.

Modeling and analysis of material removal depth contour for curved-surfaces abrasive belt grinding

Modeling and analysis of material removal depth contour for curved-surfaces abrasive belt grinding

Research on the Analysis and Prediction Model of Machining Parameters of Titanium Alloy by Abrasive Belt

As a high-performance and difficult-to-machine material for the manufacture of blades, titanium alloys are increasingly being used in high-end manufacturing industries such as aerospace and aircraft. As engineering applications become more demanding, so do the requirements for precision. However, to date, the choice of blade grinding parameters is still mainly dependent on the traditional “trial cut” and “experience” method, making the processing efficiency low and the quality of processing difficult to be guaranteed. In order to achieve the requirements of high precision and low surface roughness of the workpiece, to get rid of the status quo of relying on manual decision-making, and to achieve reasonable prediction and control of surface quality, this paper proposes to establish a theoretical prediction model for surface roughness of titanium alloy by abrasive belt grinding, and to analyze the influence of the main process parameters on surface roughness during the grinding process through experiments. A theoretical prediction model for surface roughness was developed. The experimental results show that the model has certain accuracy and reliability, and can provide guidance for the high-precision prediction of the surface roughness of ground titanium alloy blades, which has strong practical significance in engineering.

Study on the grinding force of single grain in rail grinding based on open-type belt grinding

In the realm of machining, there exists a heightened demand for improved surface integrity of workpieces. Abrasive belt grinding presents several advantages, including a high grinding ratio, superior surface finish quality, and lower grinding temperature. Additionally, the precision placement of abrasive grains in the form of triangular pyramids further enhances the efficacy of this method. It has played an important role in the field of precision machining. Accurately predicting its grinding force is vital for improving its processing quality. In this study, an open-type belt grinding method was developed, the grinding force of triangular pyramid-shaped abrasive grains in rail grinding was analyzed and calculated using oblique cutting theory, the accuracy of the proposed model was verified experimentally, and the effects of abrasive rotation angle, wear height, cutting depth, grinding speed, and rake angle on the grinding force were analyzed, and the relevant laws were obtained. According to the findings, the grinding force displays an initial rise followed by a decline as the triangular pyramid abrasive particles' rotational angle increases. The grinding force demonstrates a linear growth in tandem with an increase in grinding depth. Furthermore, the grinding force rises proportionally with an increase in abrasive wear height. The proposed model can be used for the prediction and calculation of grinding forces of other shape abrasive grains as well.

Modeling of material removal depth in robot abrasive belt grinding based on energy conversion

Accurate material removal is of great significance to ensure the machining accuracy of robot abrasive belt grinding (RABG). In this paper, a material removal depth (MRD) model for RABG of superalloy is proposed based on the energy conversion in grinding. Based on the characteristics of the shape and protrusion height distribution of grits, the energy conversion equation is established through the force analysis of the interference between grits and workpiece, and then the expression of material removal depth is derived by combining the Hertz elastic contact theory. In addition, in view of the change of belt coverage ratio caused by the structured belt wear, the expression of grit distribution density considering belt wear is obtained through the Archard wear model and applied to the MRD model. The MRD model is evaluated by the experiment, and the results show that the proposed model has good prediction ability. Furthermore, the effects of grinding parameters on MRD are analyzed, and the grinding parameters that take into account both the MRD and surface quality are discussed. This research provides a theoretical reference for material removal research in RABG.

Modeling and analysis of tangential force in robot abrasive belt grinding of nickel-based superalloy

Modeling and analysis of tangential force in robot abrasive belt grinding of nickel-based superalloy

Effect of flexible machining on subsurface damage and recrystallization of single crystal superalloy

Single crystal superalloy has gradually become the primary manufacturing material of advanced aero-engine turbine blades. However, it is easy to introduce subsurface damage and recrystallization to worsen the high-temperature service performance during the precision machining process. To investigate the effect of abrasive belt grinding on the subsurface damage and recrystallization of single crystal superalloy, a flexible adaptive continuous feed analysis model was established, which was confirmed by a series of flexible and rigid scratching experiments. The experimental results showed that the plastic deformation area generated by flexible scratch was smaller, but the slip area was larger. The recrystallization depth of flexible scratch was about 35 % lower than that of rigid scratch. The effective material removal rate of the flexible scratch was larger. The flexible reciprocating scratch verified the feasibility of the adaptive continuous feed model. And the recrystallization depth of flexible reciprocating scratch was about 47 % lower than that of rigid scratch. It indicates that the flexible machining method can not only reduce the recrystallization depth but also ensure material processing efficiency. It is expected to provide a theoretical basis and technical support for the high efficiency and low-damage machining of single crystal superalloy.