Grinding Accuracy Research Articles

A compact compliant robot for the grinding of spherical workpieces with high force control accuracy

A robotic grinding system requires a force-controlled grinding module to provide a consistent surface roughness and a robot arm to position the grinding module to reach a wide range of surface area on a workpiece. Existing pneumatic grinding modules are heavy and bulky and cannot provide very accurate force control. Articulated 6-axis robot arms are often used for positioning the grinding module, but they require a large accommodation space and have limited access to the surface of a spherical workpiece. This paper proposes a compact 3-axis grinding robot with no grinding surface limitations on spherical workpieces. The robot employs torque-controlled actuators so that a human operator can easily teach grinding paths to the robot. The proposed grinding module uses series elasticity to generate very low reflected inertia and friction. Hence, accurate grinding force control can be achieved. The grinding module also has a small size and low noise. Experimental results verify the high accuracy of grinding force control when compared with existing counterparts. Through an illustration of removing the parting line of a helmet hardshell, the grinding robot can effectively reduce the surface roughness of workpieces that are sensitive to the grinding force. It is expected that the proposed robot can be easily reconfigured to grind workpieces of different geometries.

Process Optimization of Robotic Grinding to Guarantee Material Removal Accuracy and Surface Quality Simultaneously

Abstract Simultaneously guaranteeing material removal accuracy and surface quality of robotic grinding is crucial. However, existing studies of robotic grinding process optimization have mainly focused on a single indicator that solely considers contour error or surface roughness, while studies that simultaneously investigate the impact of contact force, spindle speed, feed rate, inclination angle, and path space on the material removal profile (MRP) and the surface roughness are lacking. This paper proposes a hybrid optimization method that considers dimensional accuracy and surface quality constraints. First, an MRP model that considers the coupling influence of the contact force, spindle speed, feed rate, and inclination angle is presented. Then, a surface roughness model that considers the inclination angle is established. Finally, the contact force, feed rate, inclination angle, and path space are simultaneously optimized to satisfy the hybrid constraints of MRP accuracy and surface roughness. The proposed method ensures maximum grinding efficiency while satisfying dimensional accuracy and surface quality constraints. The proposed method is verified on an industrial robotics grinding system with a pneumatic force-controlled actuator. The results show that the proposed method has higher profile accuracy and lower surface roughness than traditional methods.

Research on Grinding Force Prediction of Flexible Abrasive Disc Grinding Process of TC17 Titanium Alloy

Abrasive disc grinding is currently a key manufacturing process to achieve better accuracy and high-quality surfaces of TC17 components. Grinding force, which results from the friction and elastic–plastic deformation during the contact and interaction between the abrasive grains and the workpiece, is a critical parameter that represents the grinding accuracy and efficiency. In order to understand the influence factors of grinding force, the characteristics of the flexible abrasive disc grinding process were studied. Considering the contact state between the abrasive tool and the workpiece, the theoretical model of normal grinding force was established in detail, from macro- and micro-perspectives. By conducting single-factor and orthogonal grinding experiments of TC17 components, the influence of different process parameters on the normal grinding force was revealed. The normal grinding force prediction models of the abrasive disc grinding process were developed based on the Box–Behnken design (BBD) and particle swarm optimization–back propagation (PSO-BP) neural networks, respectively. The results showed that the normal grinding force was negatively correlated with the disc rotational speed, and positively correlated with the contact angle, grinding depth, and feed rate, and the interaction of the factor feed rate and grinding depth was the more influential factor. Both the BBD and PSO-BP force models had good reliability and accuracy, and the mean absolute error (MAE) and mean relative error (MRE) of the above two prediction models were 0.22 N and 0.16 N, and 13.3% and 10.9%, respectively.

Collaborative improvement of profile accuracy and aerodynamic performance in robotic grinding of transonic compressor blade leading edge

Blade machining accuracy is critical to engine service performance. However, the intricate curvature characteristics and exceedingly thin dimensions of the leading edge present formidable challenges in achieving precise grinding. This study introduces a novel robotic belt grinding framework aimed at collaboratively enhancing the profile accuracy and aerodynamic performance of the leading edge. The irregular contact area and pressure distribution of the narrow rigid-flexible grinding interface are calculated based on the Semi-Hertz model. Additionally, a time-varying material removal contour (MRC) model is developed for precision grinding with the pyramid-structured abrasive belt. The non-linear equations governing dwell time are transformed into a convex quadratic optimization problem, and the solution is obtained using the fastest gradient method with constraints. Subsequently, the dwell time vector is converted into a feed rate value for robot programming. Experimental results demonstrate that the size and shape accuracy at three typical sections of the leading edge are effectively controlled within the desired range. The mean value of the line profile error is reduced to 0.019 mm, and the standard deviation of the surface profile error shows a noteworthy 32% improvement compared to the previous method. Furthermore, aerodynamic performance analyses are conducted for the ground airfoils using NUMECA. Numerical simulation results reveal that shape accuracy significantly influences the flow field state within the channel, given the precondition of qualified dimensional error. The isentropic efficiency is increased most by 4.67% by this dwell time control grinding.

A new grinding trajectory adaptive adjustment algorithm for circular-arc end mill flank based on grinding contact zone control

As one of the key structural features of the circular-arc end mill, the flank directly affects its service performance such as tool life and milling efficiency. Due to the curvature discontinuity of the flank edge curves and the inflexible posture of the grinding wheel, the existing grinding trajectory algorithms are difficult to accurately control the important end mill parameters such as the relief angle and flank width, and grinding interference is easy to occur. Therefore, this paper proposes a new grinding trajectory adaptive adjustment algorithm for circular-arc end mill flanks based on grinding contact zone control. Firstly, the edge curve equations are constructed through structural feature decomposition of the end mill, and the second flank is modeled based on uniform offset densification of edge curves. Then, the grinding wheel posture model is established and the contact zone between the grinding wheel and the first flank of the end mill is calculated. A grinding trajectory adaptive adjustment algorithm is then proposed, which iteratively modifies the lifting angle and swing angle of the grinding wheel and can avoid the abrupt change of grinding postures and the grinding interference, thus realizing accurate flank grinding. Finally, the corresponding algorithm module is developed on the VC++ platform, and the effectiveness of the proposed algorithm is verified by machining simulation and grinding experiments, therefore providing technical support for the accurate grinding of circular-arc end mills.

Vision Sensing-Based Online Correction System for Robotic Weld Grinding

The service cycle and dynamic performance of structural parts are affected by the weld grinding accuracy and surface consistency. Because of reasons such as assembly errors and thermal deformation, the actual track of the robot does not coincide with the theoretical track when the weld is ground offline, resulting in poor workpiece surface quality. Considering these problems, in this study, a vision sensing-based online correction system for robotic weld grinding was developed. The system mainly included three subsystems: weld feature extraction, grinding, and robot real-time control. The grinding equipment was first set as a substation for the robot using the WorkVisual software. The input/output (I/O) ports for communication between the robot and the grinding equipment were configured via the I/O mapping function to enable the robot to control the grinding equipment (start, stop, and speed control). Subsequently, the Ethernet KRL software package was used to write the data interaction structure to realize real-time communication between the robot and the laser vision system. To correct the measurement error caused by the bending deformation of the workpiece, we established a surface profile model of the base material in the weld area using a polynomial fitting algorithm to compensate for the measurement data. The corrected extracted weld width and height errors were reduced by 2.01% and 9.3%, respectively. Online weld seam extraction and correction experiments verified the effectiveness of the system’s correction function, and the system could control the grinding trajectory error within 0.2 mm. The reliability of the system was verified through actual weld grinding experiments. The roughness, Ra, could reach 0.504 µm and the average residual height was within 0.21 mm. In this study, we developed a vision sensing-based online correction system for robotic weld grinding with a good correction effect and high robustness.

Robotic compliant grinding of curved parts based on a designed active force-controlled end-effector with optimized series elastic component

High-accuracy, fast-response, and low-overshoot force control are important to guarantee the material removal accuracy and surface quality of robotic compliant grinding. In order to achieve the above target, this study develops an active compliant force-controlled end-effector based on a series elastic actuator for the robotic grinding of curved parts. Firstly, a decoupled robotic grinding system composed of an industrial robot and an end-effector is developed, and a novel force-controlled end-effector is designed by adding an elastic component between the servo motor and the load to improve compliance. Secondly, the influences of the elastic component and grinding tool stiffness on the stability of the force-controlled end-effector system are analyzed by establishing a contact model of the compliant end-effector and the transfer function of the entire force control system. Then, the stiffness of the grinding tool and the elastic component are optimized with full consideration of the system cutoff frequency and the end-effector compliance. To improve the force tracking accuracies of the developed compliant end-effector, a proportional-integral (PI) controller with first-order differential force feedforward control is designed. Finally, grinding experiments are conducted for verification. The effects of spring stiffness and grinding tool stiffness on the force control system are tested, which match well with the theoretical analysis. Grinding results show that the maximum force control error of the compliant force-controlled end-effector is decreased by 70% compared to that of the rigid force-controlled end-effector, and the overshoot of the force control is reduced from 30% to almost 0 under the same response speed. The maximum and average absolute grinding depth errors using the designed end-effector are reduced by 57.2% and 58.6%, respectively, compared with those of the traditional rigid end-effector, and the average surface roughness of the finished part is reduced by 19.2%. Which demonstrates the effectiveness and advantages of the proposed compliant force-controlled end-effector.

INVESTIGATING THE MECHANISM OF DIAMOND GRINDING STONE DISCHARGE IN MIST ENVIRONMENT

The study investigates the mechanism of electrical discharge machining in a mist environment for grinding diamond stones. The mist-assisted diamond grinding technology shows great promise, with advantages such as environmental protection and high efficiency. Additionally, utilizing a mist environment for grinding diamond stones reduces the dependence on working fluids and allows for direct grinding in highly accurate grinding machines.

Gear evaluation deviations-based crucial geometric error identification of five-axis CNC gear form grinding process

The gear form grinding accuracy is significantly affected by crucial geometric errors. The gear form grinding process is a special line contact forming method. There are exclusive evaluation standards for gear grinding accuracy. While the existing sensitivity analysis for spatial point errors cannot meet the final gear report requirements. Hence, a novel method for analysis of geometric error influence on the key gear evaluation deviations (GED) is proposed. First, the actual digital tooth surface considering geometric errors and gear form grinding mechanism was constructed according to the homogeneous transformation matrix (HTM) and multi-body system theory (MBS). Second, the GED of the digital tooth surface was gained according to the modified gear meshing equations. Third, the analytic mapping relationship between the GED and machine tool geometric errors was first established. Then, the crucial geometric errors affecting the GED were identified based on a proposed Morris method. Finally, the identification results were compared to the existing publications, and the compensation discussions of crucial errors were demonstrated to validate the advantages of the proposed method. It can be found that the compensation results of GED-oriented key errors are better than those of the traditional methods, which is beneficial to the improvement of evaluation reports.

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.

Dynamic force modeling and mechanics analysis of precision grinding with microstructured wheels

The application of structured surfaces on advanced tools is an effective method for enhancing the machining performance. The modeling of dynamic grinding force is of great significance for improving tool surface structure design and improving grinding accuracy. In this paper, a novel dynamic force modeling and mechanics analysis of precision grinding with microstructured wheels was put forward. A grinding wheel topography model was established by considering the non-simplified position-posture-shape-size multiple random grains morphological characteristics. On this basis, the material removal pattern of the microstructured multiple random abrasive grains was identified based on grinding kinematics and undeformed chip thickness. The grain diameter, average bearing width, flat surface area, friction coefficient and total number of active abrasive grains in the grinding area were considered. Their effects on the amplitude and frequency of grinding force were discussed in detail, and the precision grinding experiment was carried out. The results show that the dynamic force model proposed could accurately evaluate the influence of microstructure tools on forces with an error rate of 6.7% or less. Compared with the original grinding wheel, the addition of microstructure reduces the grinding force by 49.6%− 94.3%. By controlling the force components, the force frequency is more concentrated, and the disorder of the grinding force signal is suppressed. Furthermore, the carbon emission model was calculated, and it can be seen that microstructured wheels can obviously reduce carbon emission, which is a novel processing technology to realize low-carbon manufacturing.

Metrological Aspects of Assessing Surface Topography and Machining Accuracy in Diagnostics of Grinding Processes

The paper presents probabilistic aspects of diagnostics of grinding processes with consideration of metrological aspects of evaluation of topography of machined surfaces and selected problems of assessment of machining accuracy. The processes of creating the geometric structure of the ground surface are described. It was pointed out that the distribution of features important for process diagnostics depends on the mechanism of cumulative effects of random disturbances. Usually, there is a multiplicative mechanism or an additive mechanism of the component vectors of relative displacements of the tool and workpiece. The paper describes a method for determining the classification ability of specific parameters used to evaluate stereometric features of ground surfaces. It is shown that the ability to differentiate the geometric structure of a certain set of surfaces using a selected parameter depends on the geometric mean of the differences in normalized and sorted, consecutive values of this parameter. A methodology is presented for evaluating the ability of various parameters to distinguish different geometric structures of surfaces. Further, on the basis of analyses of a number of grinding processes, a methodology was formulated for proceeding leading to a comprehensive evaluation of machining accuracy and forecasting its results. It was taken into account that in forecasting the accuracy of grinding, it is necessary to determine the deviations, arising under the conditions of multiplicative interaction of the effects of various causes of inaccuracy. Examples are given of processes in which, due to the deformation of the technological system, dependent on the position of the zone and machining force, varying temperature fields and tool wear, the distributions of dimensional deviations are not the realization of stationary processes. It was emphasized that on the basis of the characteristics of the dispersion of the deviation value in the sum set of elements, it is not possible to infer its causes. Only the determination of the "instantaneous" values of the deviation dispersion parameters allows a more complete diagnosis of the process.

Influence of the Compliance of a Technological System on the Machining Accuracy of Low-Stiffness Shafts in the Grinding Process

This paper reports the results of research on the influence of the compliance of the technological system used in grinding low-stiffness shafts on the shape accuracy of the workpieces. The level of accuracy achieved using passive compliance compensation was assessed, and technological assumptions were formulated to further increase the shape accuracy of the low-stiffness shafts obtained in the grinding process. Taking into account the limitations of passive compliance compensation, a method for the active compensation of the compliance of the elastic technological system during the machining process was developed. The experiments showed that the accuracy of grinding was most effectively increased by adjusting the compliance and controlling the bending moments, depending on the position of the cutting force (grinding wheel) along the part. The experimental results were largely consistent with the results of the theoretical study and confirmed the assumptions made. Adjusting the compliance in the proposed way allows for the significant improvement in the accuracy and productivity of machining of low-stiffness shafts.

A Study of an Online Tracking System for Spark Images of Abrasive Belt-Polishing Workpieces.

During the manual grinding of blades, the workers can estimate the material removal rate based on their experiences from observing the characteristics of the grinding sparks, leading to low grinding accuracy and low efficiency and affecting the processing quality of the blades. As an alternative to the recognition of spark images by the human eye, we used the deep learning algorithm YOLO5 to perform target detection on spark images and obtain spark image regions. First the spark images generated during one turbine blade-grinding process were collected, and some of the images were selected as training samples, with the remaining images used as test samples, which were labelled with LabelImg. Afterwards, the selected images were trained with YOLO5 to obtain an optimisation model. In the end, the trained optimisation model was used to predict the images of the test set. The proposed method was able to detect spark image regions quickly and accurately, with an average accuracy of 0.995. YOLO4 was also used to train and predict spark images, and the two methods were compared. Our findings show that YOLO5 is faster and more accurate than the YOLO4 target detection algorithm and can replace manual observation, laying a specific foundation for the automatic segmentation of spark images and the study of the relationship between the material removal rate and spark images at a later stage, which has some practical value.

Dimensional Error Compensation Based on Data-Driven Sliding Mode Terminal Iterative Learning Control for CNC Batch Grinding

Dimensional error of workpiece is an important index that indicts the grinding accuracy of machine tools. Conventional error compensation strategies focus on modeling one or several error factors for a particular CNC machining type, which are time consuming and costly. Based on data-driven sliding mode terminal iterative learning control, a new dimensional error compensation method is proposed in this paper. The compensation algorithm based on an iterative sliding surface and an objective function is established using the terminal experimental data. A modified NC program is fed to the machine tool to push the workpiece dimension towards desired. The theoretical analysis and experimental results show the proposed compensation method can effectively improve the batch grinding accuracy of the machine tool, which shows good perspective in manufacturing industry.

A Fuzzy Adaptive PID Control Method for Novel Designed Rail Grinding Equipment

Rail defects appear in a greater variety and frequency with the rapid development of High-Speed Rail (HSR), which seriously affects the safe operation of trains. Rail grinding is one of the common methods used to eliminate these defects. However, the quality of rail grinding is often limited by the constant power control method. This paper presents a fuzzy adaptive PID control method based on PID control. In this method, a fuzzy rule library of input and output is established according to the experience of experts and grinding operators, and the PID control parameters can be adjusted in real time through the library to achieve the purpose of constant power grinding. Compared with classical PID, the effectiveness of the proposed method was verified by simulation and the rail grinding experiment with the designed equipment. Experimental results showed that the power data of fuzzy adaptive PID control had less fluctuation, which could be basically stabilized at 5KW±0.1KW, and the curve tracking error was reduced by 60.9%. It is concluded that this method can greatly improve the power accuracy and stability of rail grinding.

Trajectory planning method with grinding compensation strategy for robotic propeller blade sharpening application

A propeller is the main part of a water-borne carrier's drive system. Geometrical shape accuracy and sharpness on the cutting side of the propeller's blade play vital roles to minimize fluid resistance and improve transmission efficiency. For Jet Ski and small boats, the significant thickness variation along the blade edge is embedded in the lost-wax casting process. The automatic trajectory planning for the robotic propeller blade's sharpening operation is challenging due to its complicated curved shape and the tiny gaps between two connected blades. The trajectory planning for robotic grinding based on the edge thickness distribution of the standard model may result in over- or under-cutting due to the highly inconsistent shape deformation caused by the casting process. To address the aforementioned challenges, this study proposes a fully automated robot grinding system. The proposed method combines a novel trajectory planning approach based on a parametric and point cloud model with a 3D scanning on edge-based trajectory adjustment approach. Moreover, to improve the grinding accuracy, a laser-vision sensor-based detection algorithm is also developed for grinding compensation to counteract the geometrical variation caused by the casting process. The effectiveness of the proposed system is validated through numerous experimental trials using a 6-DOF industrial robot. The research findings showcase that the proposed technique is feasible, stable, and effective for robotic propeller blade edge sharpening operations.

Research on Generating Gear Grinding Machining Error Based on Mapping Relationship between Grinding Wheel Surface and Tooth Flank

This paper proposes a method to study the machining error when one is generating gear grinding based on the mapping relationship between the grinding wheel surface and the tooth flank. The profile of the grinding wheel after grinding is collected, and the theoretical tooth flank is derived according to a model of generating gear grinding. By comparing the normal deviation of the theoretical tooth flank with the measured tooth flank, the machining error characteristics are identified. Firstly, the mathematical model of generating gear grinding is established according to a multi-body theory and coordinate transformation. Secondly, the experiments of the lead modification for helical gear were performed on a YW7232 CNC gear grinding machine. The tooth flank twist compensation function was turned off in experiments No. 1–No. 3, and it was turned on in experiments No. 4–No. 6, while the other process parameters kept the same. Then, the corresponding theoretical tooth flank data were derived from the grinding wheel surface which were measured using the laser profilometer LJ-V7000. Finally, the machining error characteristics were obtained by analyzing the difference between the theoretical and measured tooth flank deviations. The result of this paper can provide theoretical and practical references for the improvement of the gear grinding accuracy and gear modification design.

An indirect flow measurement based high-precision slide valve grinding mechanism for hydraulic servo valve

As a crucial power amplifying component for electro-hydraulic servo valves, the servo-valve spool valve largely determines the overall performance of an electro-hydraulic servo system. Due to the machining errors during the servo-valve manufacturing process, however, it is extremely difficult to characterize such response characteristics in engineering practice, and thus, there may exist certain nonlinearity between the flow rate and valve spool displacement caused by the spool and valve sleeve overlap. To accurately characterize the relationship between the flow rate and spool displacement to facilitate servo-valve production, an indirect flow measurement-based servo-valve spool valve grinding (FM-SVG) scheme is proposed in this study. Specifically, a valve spool overlap measurement mechanism is presented first based on the valve spool grinding principle, and then a data processing method is devised to eliminate the errors introduced by the fluctuations of differential pressure at the valve ports. Meanwhile, a closed-loop control system is also devised to maintain a constant differential pressure at the servo-valve ports. Finally, the FM-SVG scheme is embedded onto a lab-customized electro-hydraulic servo valve platform, and experiments are conducted to verify the feasibility and effectiveness of the FM-SVG scheme. Results show that, by utilizing the devised control scheme to maintain a differential pressure around 2.00 MP, the proposed grinding scheme helps achieve a grinding accuracy of 2.0 μm. With only grinding process needed, such a grinding scheme helps improve both grinding accuracy and production efficiency in practice.

Research on roundness error consistency model for crank journal cylindrical grinding

Cylindrical grinding is an important way to form the external shape error of the crank journal, and the accuracy consistency directly affects the interchangeability of products. To study the accuracy consistency of crank journal, a dynamic model of the grinding wheel-crankshaft grinding system based on Timoshenko beam is established, and the grinding transition process simulation algorithm with iterative convergence of grinding force-transient grinding amount cycle adapted to the model is proposed, which realizes the simulation of the roundness of the crank journal coupled with the process parameters of the grinding system. Aiming at the grinding position of each crank journal, the grinding roundness of five crank journals is simulated, respectively. On this basis, the crank journal roundness consistency prediction model is established, and the effectiveness of the prediction model is verified by field experiments. Finally, the influence of grinding parameters on the consistency of the roundness of crank journal is studied. The research conclusion can provide a reference for the grinding accuracy consistency design of this type of crank journal.