Abrasive Belt Wear Research Articles

Prediction of Abrasive Belt Wear Height for Screw Rotor Belt Grinding Based on BP Neural Network with Improved Skyhawk Algorithm

Prediction of Abrasive Belt Wear Height for Screw Rotor Belt Grinding Based on BP Neural Network with Improved Skyhawk Algorithm

Analysis of abrasive belt wear effect on residual stress distribution in robotic belt grinding of GH4169

Analysis of abrasive belt wear effect on residual stress distribution in robotic belt grinding of GH4169

Research on abrasive belt wear monitoring for the rail grinding

Research on abrasive belt wear monitoring for the rail grinding

On Energy Assessment of Titanium Alloys Belt Grinding Involving Abrasive Wear Effects

Improved energy utilisation, precision, and quality are critical in the current trend of low-carbon green manufacturing. In this study, three abrasive belts were prepared at various wear stages and characterised quantitatively. The effects of abrasive belt wear on the specific grinding energy partition were investigated by evaluating robotic belt grinding of titanium plates. A specific grinding energy model based on subdivided tangential forces of cutting and sliding was developed for investigating specific energy and energy utilisation coefficient EUC. The surface morphology and Abbott–Firestone curves of the belts were introduced to analyse the experimental findings from the perspective of the micro cutting behaviour. The specific grinding energy increased with abrasive belt wear, especially when the belt was near the end of its life. Moreover, the belt wear could lead to a predominance change of sliding and chip formation energy. The highest EUC was observed in the middle of the belt life because of its retained sharp cutting edge and uniform distribution of the grit protrusion height. This study provides guidance for balancing the energy consumption and energy utilization efficiency of belt grinding.

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.

Wear behavior of alumina abrasive belt and its effect on surface integrity of titanium alloy during conventional and creep-feed grinding

Abrasive belt grinding is commonly used in the surface processing of key components of major equipment, such as blade, blisk and rail, due to its cold and flexible processing characteristics. Creep feed belt grinding (CFBG) can effectively improve the processing efficiency; however, it will result in severe abrasive belts wear and low grinding quality. This study comparatively investigated the abrasive belt wear behavior and its effect on surface integrity of titanium alloy during CFBG and conventional belt grinding (CBG), It was revealed that CFBG led to more severe abrasive belt wear than CBG, and the main wear form of abrasive belt was abrasive grain fracture (account for more than 40%) during CFBG, while that was abrasive grain attrition during CBG. Besides, the grinding temperature and grinding force in CFBG were more significant than those in CBG. With the increase of the abrasive belt wear, the grinding temperature and grinding force gradually decreased. Furthermore, as the abrasive belt worn, the ground surface was gradually flattened, and the roughness of CFBG reduced from 1.16 to 0.50 μm, while that in CBG reduced from 0.704 to 0.560 μm. Compared with CBG, an apparent plastic flow and oxidation of titanium alloy occurred due to the temperature effect during CFBG, and the surface residual stress transformed from compressive to tensile as abrasive belt wore.

Material removal and belt wear in laser assisted grinding TC17

ABSTRACT Titanium alloys have high hardness and low plasticity, there will be large cutting force and serious tool wear during machining. Laser-assisted grinding can significantly improve its machinability, but the wear mechanism of abrasive tools and its influence on material removal during machining have not been well revealed. In this paper, the variation of cutting force under different laser power, laser scanning speed and feed speed were studied. In addition, the influences of different laser powers on material removal was also investigated. At the same time, the abrasive belt wear in laser-assisted grinding and conventional grinding was compared. The results indicated that increasing the laser power can reduce the cutting force. When the laser power increased from 7.2W to 9.6W, the cutting force showed the maximum change trend, which decreased by 46%. Enhanced material removal and increased plastic flow with increasing laser power. Increasing the laser scanning speed and workpiece feeding rate will also increase the cutting force. In addition, laser-assisted grinding can reduce belt wear compared with conventional grinding under the same grinding parameters. Therefore, laser-assisted grinding has an important potential role in the field of grinding.

Wear evolution of electroplated diamond abrasive belt and corresponding surface integrity of Inconel 718 during grinding

Serious wear can easily occur in traditional abrasive belts during grinding nickel-based superalloy components. To find an abrasive belt with excellent wear resistance and surface finishing, this study uses electroplated diamond abrasive belt (EDAB) to grind Inconel718, and investigates its wear evolution and corresponding grinding surface integrity. It was revealed that EDAB showed stable grinding performance, and the wear mechanism in initial, steady, and final wear stage was primarily micro cleavage fracture, macro cleavage fracture and adhesive wear, respectively. As EDAB wore, ground surface roughness gradually decreased and reached a minimum of Ra0.5 µm, and subsurface crystalline grains of Inconel718 were refined. Furthermore, the abrasive belt wear was significantly reduced and the surface integrity was improved using low-hardness contact wheels.

Influence mechanism of abrasive belt wear on fatigue resistance of TC17 grinding surface

Abrasive belt grains morphology and wear process have direct effect on grinding surface quality and service performance of titanium alloys. In order to increase fundamental understanding of abrasive belt wear on service performance of grinding surfaces, further provide targeted guidance for anti-fatigue surface grinding, this paper analyzed the surface characteristics and fatigue failure mechanism of the TC17 samples ground before and after abrasive belt wear. Results showed that for zirconium corundum abrasive belt with relatively independent abrasive grains, the fatigue failure of machined surface before abrasive belt wear is dominated by roughness. After zirconium corundum abrasive belt was worn, grinding surface roughness is reduced and surface mechanical properties are strengthened, which promotes the initiation of fatigue cracks from the subsurface and the improvement of fatigue life. Although the wear of electroplated diamond abrasive belt can reduce the surface roughness of grinding surface, the embedding and accumulation of abrasive grains hindered the chip removal and heat dissipation in material removal process, making the grinding surface easy to form heterogeneous ablative layer, and fatigue cracks initiated from the subsurface ablation area. The heterogeneous areas formed by surface burns will exacerbate surface stress concentration, which in turn will greatly reduce surface fatigue performance, it needs to be avoided as much as possible. Sharp electroplated diamond belts and worn zirconium corundum belts have excellent advantages in improving surface anti-fatigue performance.

Experimental and numerical characterization of abrasive belt wear and debris formation during dry grinding of nickel-based superalloys with diamond abrasive belts

Nickel-based superalloys are the constituent materials of critical components of aero engines. Abrasive belt grinding is an effective method for the precision machining of such difficult-to-machine materials. However, the wear of the abrasive belt greatly affects the quality and integrity of the machined surface. In this study, a physical simulator of abrasive belt grinding was used to carry out diamond belt grinding experiments. The wear behavior of abrasive belts and the shape of debris at different temperatures were mainly investigated. In addition, a three-dimensional finite element model of single abrasive grain grinding was established to analyze the formation of debris. The variations of abrasive belt wear and debris morphology with temperature within the experimental temperature range were obtained. There are four types of wear behavior of diamond abrasive belts: grain flattening, grain shed, dependency blockage, and adhesion blockage. The self-sharpening of the abrasive belt plays an important role in improving the quality of the machined surface. The finite element model accurately simulates the shape of debris at different temperatures and the shape of debris changes apparently with temperature. The critical temperature for the formation of good surface quality is obtained. The research results provide guidance for the selection of abrasive belt grinding process parameters.

Robust under-liquid dual super-lyophobicity cement material for anti-fouling and oily wastewater treatment

Materials of under-liquids (water/oil) dual super-lyophobicity require special micro/nano morphology. However, such material surfaces are mechanically weak and readily worn, which restricts their practical applications. Herein, we report a robust self-similar under-liquid dual super-lyophobicity anti-fouling cement which demonstrates stable underwater super-oleophobicity (θo/w > 150°) and under oil super-hydrophobicity (θw/o > 150°) via a simply mixed cement and water, without other organic reagents and professional preparation technology. The obtained material not only owns good under-liquids mechanical robustness but also has very excellent anti-fouling property. This surface material still has the anti-oil-fouling property once its surface is mechanically damaged, due to its surface self-similar functionality. Importantly, the surface maintained their excellent super-lyophobic functionality due to the similar property after turbulent jets (5 m range), abrasive belt wear, blade cutting (transverse cutting), highly-viscous tape peeling (VHB, 3 M), and ASTM standard adhesion (scratch spacing and cutting spacing). Cement could separate from oil/water mixtures, the separation efficiency for oil was above 97.5% at 30 cycles. Our study provides an eco-friendly, green, simple, low-cost, and easily mass-produced strategy to the fabrication of super-lyophobic materials in oil/water systems dual functional materials, which will benefit applications in diverse fields.

A deep transfer learning method for monitoring the wear of abrasive belts with a small sample dataset

The wear state of abrasive belts is directly related to the final processing quality and accuracy. Therefore, the accurate prediction of the replacement time of abrasive belts can help not only improve the product quality but also reduce the cost. According to the analysis of displacement data, a new method for the prediction of abrasive belt wear states using a multiscale convolutional neural network based on transfer learning is proposed. Initially, first-order difference preprocessing is ingeniously performed on displacement data. Then, the network parameters of the model are obtained by pretraining the fault dataset and are directly transferred or fine-tuned according to the preprocessed displacement data. Finally, the preprocessed displacement data corresponding to different abrasive belt wear states are accurately classified. This method verifies the application of transfer learning between cross-domain data in industry and resolves the contradiction between the large sample size required for deep learning and the difficulty of obtaining a large amount of sample data in actual production. The experimental results show that this method can accurately predict the wear status of abrasive belts, with an average prediction accuracy of 93.1%. This method has the advantages of low cost and easy operation, and can be applied to guide the replacement time of abrasive belts in production.

Prediction of Abrasive Belt Wear Based on BP Neural Network

Abrasive belt grinding is the key technology in high-end precision manufacturing field, but the working condition of abrasive particles on the surface of the belt will directly affect the quality and efficiency during processing. Aiming at the problem of the inability to monitor the wearing status of abrasive belt in real-time during the grinding process, and the challenge of time-consuming control while shutdown for detection, this paper proposes a method for predicating the wear of abrasive belt while the grinding process based on back-propagation (BP) neural network. First, experiments are carried out based on ultra-depth-of-field detection technology, and different parameter combinations are used to measure the degree of abrasive belt wear. Then the effects of different grinding speeds, different contact pressures, and different work piece materials on the abrasive belt wear rate are obtained. It can be concluded that the abrasive belt wear rate gradually increases as the grinding speed of the abrasive belt increases. With the increase of steel grade, the hardness of the steel structure increases, which intensifies the abrasive belt wear. As the contact pressure increases, the pressure on a single abrasive particle increases, which ultimately leads to increased wear. With the increase of contact pressure, the increase of the wear rate of materials with higher hardness is greater. By utilizing the artificial intelligence BP neural network method, 18 sets of experiment data are used for training BP neural network while 9 sets of data are used for verification, and the nonlinear mapping relationship between various process parameter combinations such as grinding speed, contact pressure, workpiece material, and wear rate is established to predict the wear degree of abrasive belt. Finally, the results of verification by examples show that the method proposed in this paper can fulfill the purpose of quickly and accurately predicting the degree of abrasive belt wear, which can be used for guiding the manufacturing processing, and greatly improving the processing efficiency.

Analysis of abrasive belt wear effect on residual stress distribution on a grinding surface

Owing to elastic grinding and other favorable processing characteristics, belt grinding has been widely used in many industrial applications, including machining titanium alloys of difficult-to-cut metals. Abrasive belt wear inevitably occurs in the grinding process, but its mechanism and effects have not been fully understood, especially its effect on the residual stress (RS). To overcome this shortcoming, this study experimentally investigates the abrasive wear influence on the surface RS distribution of titanium plate belt grinding through a synthetic cause analysis. First, abrasive belts with different wear stages are prepared according to the wear law throughout the abrasive belt life cycle, and their wear degrees are quantitatively evaluated. Then, comparative grinding experiments of the TC4 flat plate are conducted using the prepared abrasive belts. Finally, the surface RS distribution of the grinding traces and stress differences induced by the abrasive belt wear are analyzed and discussed comprehensively. The results indicate that the more severe the abrasive belt wear is, the greater the accumulation of grinding heat and the greater the ratio of the grinding energy will be, which will further lead to residual tensile stress (RTS) generation, especially in the grinding direction. In addition, owing to the fast heat dissipation on both sides of the contact wheel, the surface RS along the grinding traces' vertical direction obeys an approximately symmetrical distribution, having low values on the sides and a peak in the middle. The strong accumulation of grinding heat caused by severe wear makes the difference between the stress distribution extremums increase with the abrasive belt wear.

Investigation of conditions leading to critical transitions between abrasive belt wear modes for rail grinding

In abrasive belt rail grinding, understanding the abrasive belt wear mechanisms is important for improving grinding accuracy and abrasive belt service life. Taking a single ceramic grit in a stable grinding state as an example, this study investigated the critical transition conditions and recognition methods between the different wear modes. Based on the crack growth equation, the critical transition condition from abrasion to fracture was modeled by calculating the stress around the cracks hiding in the grit tip. The transition condition between fracture and pull-off was determined by comparing the external stress around the grit root and the bonding strength of the resin binder. These critical conditions were verified by single grit scratching experiments and the improved Sc wear map method.

Novel monitoring method for material removal rate considering quantitative wear of abrasive belts based on LightGBM learning algorithm

Wear is an inevitable problem in abrasive belt grinding, and the material removal rate decreases with continuous wear of the abrasive belt. This indicates that the grinding control force is affected by two dynamic factors, namely the actual material removal and abrasive belt wear state. To obtain an accurate force-control model to achieve uniform material removal, a new method for online monitoring of abrasive belt material removal rates and their corresponding wear statuses is proposed herein using only the grinding sound signals. By performing material removal rate and abrasive belt wear experiments, the grinding sound signals during processing are obtained. The wear states of the abrasive belt are quantified using the newly defined gray-mean values of the topographical images of the belt into different levels. The grinding sound signals are quantitatively described via the statistical features of their sound wavelet signals. The statistical features related to material removal rates or belt wear states are selected on the basis of the Pearson correlation coefficients. The prediction models for material removal rate and wear levels of the abrasive based on the selected features are then established using the LightGBM learning algorithm. Experimental datasets are used to train and validate the established model. The test results show that the evaluation parameters of the prediction model of the material removal rate are all within 5%. Further, the accuracy of the wear levels of the abrasive belt can exceed 91%. Compared with other prediction models, the new LightGBM models exhibit superiority in terms of time factor without loss of accuracy of the model. It is thus proved that the proposed method can provide a good basis for monitoring the material removal rate and belt wear in the abrasive belt grinding process.

Feasibility study of minimum quantity lubrication assisted belt grinding of titanium alloys

ABSTRACT In order to investigate the feasibility of minimum quantity lubrication technique in precision machining titanium alloys using abrasive belt grinding method, theoretical calculations and a series of detailed experimental studies were conducted in this paper. Material removal rate, grinding force, grinding temperature, abrasive belt wear, and machined surface quality were determined as the corresponding evaluation indicators. The signals of force and temperature in the grinding process were continuously collected by dynamometer and infrared thermal imager, respectively. The surface topography of the abrasive belt and workpiece were detected by a scanning electron microscope, and the machined surface roughness was measured by a surface profiler. The experimental results showed that the minimum quantity lubrication technology had obvious advantages in reducing abrasive wear and improving machined surface quality with suitable lubricating and grinding parameters. The observation result indicated that the compact microstructure and preferable fatigue strength can be obtained by using this assisted technique. Moreover, the addition of carbon nanotubes in grinding fluids was proven to be an effective way to further improve the effect of minimum quantity lubrication on assisted abrasive belt grinding of titanium alloys.

An online belt wear monitoring method for abrasive belt grinding under varying grinding parameters

Abrasive belt grinding has attracted attention in recent years in both industry and academia due to the rapid development of abrasive belts; however, online monitoring of abrasive belt wear under varying grinding parameters is challenging. In this paper, the multi-sensor fusion of sound and current signals is used to resolve the abovementioned problem. First, the characteristics of the grinding sound and current are investigated in the time-domain and frequency-domain, and then their differences under various belt wear states and grinding parameters are discussed; based on the investigation, several features are extracted that indicate the belt wear state. The abovementioned discussion demonstrated that grinding sound signals have an abundance of information at high frequencies (6–20 kHz); in contrast, grinding current signals contain information at low frequencies. Furthermore, the grinding sound and current signals have different sensitivities to the grinding parameters and belt wear. Finally, a Bayesian network is proposed to identify the wear state; moreover, its adaptability under changing parameters and the effect of multi-sensor fusion are discussed. The results show that the accuracy reaches 100% with enough training data; additionally, when the training data only covers a limited range of grinding parameters, the fusion of the sound and current substantially improves the accuracy of the prediction results from 86% to 95%.

Feature extraction method of abrasive belt wear state for rail grinding

Abrasive belt has the advantages of high removal efficiency and high waste collection; furthermore, it does not easily damage the rail when applied in rail grinding. However, the poor wear consistency and short service life restrict its development in this field. It is important to explore the theory and technology of monitoring the abrasive belt wear condition to evaluate the means of improving the grinding performance of the belt. This article discusses the contact stress state between the belt and the rail surface. In addition, the study establishes the belt rail grinding force model during operation using the abrasive grain distribution function. The analysis of the force model proposes that the belt abrasion condition be monitored by using the force ratio parameter of the abrasive belt in the grinding process. The extraction method of the force ratio information is proposed in accordance with the grinding environment. The results of experiments successfully verified the validity of the method.

Single-grain cutting based modeling of abrasive belt wear in cylindrical grinding

A systematic wear model of the cylindrical grinding process with an alumina abrasive belt from the perspective of single grain sliding wear was established in this study. The model consists of three parts: a single cutting force model derived by applying a stress integration method, a single grain wear height analysis based on the wear rate of alumina, and a grinding mileage prediction of multiple grains with Gaussian distributed protrusion heights. Cutting force, single grain wear height and full-size grinding mileage verification experiments were conducted. The results indicated that the established model was in reasonable agreement with the experimental outcomes, which suggests that this model could be useful in the industry to predict the wear process of abrasive belts.