Search Results (11)

In precision gear manufacturing, longitudinal crowning on tooth flanks is commonly produced by applying diagonal feed in worm-type generating processes using tools such as variable-tooth-thickness hobs and dressable grinding worms. However, precise twist control remains difficult because the geometric parameters of the generating tool are strongly coupled with the machine feed settings in the underlying generating kinematics. In addition, direct numerical optimization becomes unreliable near the standard tool state, where the sensitivity of the diagonal-feed coefficient degenerates and conventional linearized solvers may lose effectiveness. To address these issues, this study proposes a multi-variable optimization framework for twist-constrained worm-type gear generation. An iterative singular value decomposition (SVD) scheme is developed to construct and update the sensitivity matrix, while a warm-start continuation strategy is introduced to overcome the local singularity and improve numerical robustness. Two closed-form expressions for the diagonal-feed coefficient are also proposed as practically useful initial estimates, corresponding respectively to the minimum SVD topographic residual and the minimum tooth-flank twist. Numerical validation over a 60-case parameter sweep shows maximum relative errors below 1.6% within the tested range. The proposed framework coordinates the tool-geometry design and diagonal-feed selection to generate tooth flanks with prescribed crowning characteristics while satisfying a specified twist requirement and limiting the required diagonal shift. Numerical examples show that the iterative framework reduces the root-mean-square (RMS) topographic error from 1.14 μm to 0.027 μm relative to the analytical setting of Hsu and Fong. These results indicate that the proposed method provides a reliable computational basis for twist control and process-parameter design in advanced CNC gear generation. From a manufacturing standpoint, because the three design criteria are accessed by adjusting only the diagonal-feed ratio on the machine, a single generating-tool design can serve a range of crowning and twist requirements without retooling, reducing setup and tooling efforts in production. Full article

Plunge shaving is a widely used finishing process for high-precision gears due to its high productivity and cost-effectiveness. However, manufacturing the plunge-shaving cutter itself remains challenging, particularly for modified tooth profiles. Because the theoretical cutter flank exhibits a hyperboloid-like geometry in the lead direction, conventional disk-wheel grinding tends to introduce systematic twist-like topographic bias. To overcome this limitation, a comprehensive mathematical framework is developed for the generative grinding of plunge-shaving cutters using an involute-helicoid grinding worm. Based on envelope theory and homogeneous coordinate transformations, the theoretical cutter surface is first derived, followed by the establishment of a complete kinematic grinding model. A linear least-squares optimization algorithm is then formulated to determine the optimal center-distance compensation parameter for minimizing the normal deviation between the generated and theoretical surfaces. Numerical simulations demonstrate that the proposed method significantly suppresses twist-related topographic errors. In a benchmark moderate-helix case, the maximum residual deviation is controlled to approximately 2 µm. For a more demanding large-helix configuration, a two-level optimization strategy—combining machine-setting compensation and grinding-worm helix-angle adjustment—reduces the peak deviation from about 5.5 µm to 4.7 µm, corresponding to an improvement of approximately 15%. This confirms that worm-geometry tuning provides an additional, effective degree of freedom for high-helix cutter applications. Full article

The gears of helicopter transmission system have strict requirements on machining accuracy, and the accurate prediction of tooth surface grinding force is the key to its manufacturing. The existing model simplifies the micro-contact behavior of the abrasive-workpiece, which limits the accuracy of the grinding load solution. In this paper, the stress state of single abrasive grain at different stages is refined from the micro level, and the grinding force mechanism model of contact area superposition is established. A mechanism-constrained data-driven grinding force prediction algorithm (MCDDP) is proposed. The algorithm integrates the microscopic force mechanism as a physical constraint into the neural network. The experimental results show that the R² of the model for predicting the normal and tangential grinding forces under multiple working conditions is higher than 0.98, and the average error is reduced by about 17% compared with the traditional model. This study reveals the non-uniform force mechanism of abrasive-workpiece, realizes the integration of mechanism model and data-driven method, and provides engineering theoretical and technical support for grinding force prediction and process parameter optimization of aviation precision gears. Full article

As one of the most important finishing machining means of internal helical gear, the residual stress that appears during profile grinding plays an important role in transmission performance and the service internal helical gear. In this research, the residual stress simulation model of internal helical gear profile grinding is established to optimize and predict grinding parameters by means of a neural network. The grinding process parameters (including grinding depth, grinding feed speed, and grinding wheel linear speed) are taken as variable factors. Through experimental verification, the maximum error of the simulation value is 12.8%. The radial basis function (RBF) neural network is introduced, and simulation data samples are used to train and test the residual stress prediction model. Three groups of unknown grinding parameters are predicted, and the relative errors between the predicted and measured values are 5.16%, 1.63%, and 3.39%, respectively. The results demonstrate that the RBF neural network residual stress prediction model proposed in this paper is accurate and feasible. At the same time, the residual stress prediction method provides a theoretical basis for optimizing and controlling the precision of internal helical gear profile grinding. Full article

In the process of herringbone gear grinding, excessive grinding force leads to a large increase in grinding specific energy. A large increase in the specific grinding energy can easily lead to an increase in the transient cutting load. It leads to grinding burn, tooth surface crack and other undesirable phenomena, which ultimately affect the surface quality and service performance of the workpiece. This paper is based on the contact mechanics of workpiece materials. The number of dynamic effective abrasive particles is considered. Combined with the mechanism of grinding force, the model is developed. Based on the consideration of the wear characteristics of the grinding wheel and the structure parameters of the gear itself, the grinding force model was modified. The accuracy of grinding force model is improved by dividing the effective contact angle of grinding grains into four cases. The experimental results show that the normal grinding force error reaches 10.73% and the tangential grinding force error reaches 10.34%. The model reveals the grinding mechanism, optimizes grinding parameters and improves grinding efficiency. It provides a new way for high-precision machining of aerospace precision herringbone gear. Full article

The wheel-side electric drive system is a melding of a vehicle powertrain and suspension system, which saves chassis space and can adapt to different models. To achieve the goal of highly modularized development, the system is supposed to meet the requirements of various working conditions without changing the interface state. The electric motor drives the wheel through two-stage fixed axis helical gears, so the transmission is short in path and acts as the suspension arm at the same time. As a result, the gears are critical to output robustness and NVH performance. The modeling accuracy is decisive for simulations and tests, so it is necessary to build a precise geometric model instead of the data-fitting estimation. The gears are manufactured by a hobbing and form grinding process, which is described functionally along with the relationship between the tooling parameters and tooth profile curves. Based on the rain flow methodology and extrapolation theory, a comprehensive load spectrum with nine stages is formulated, which can cover the working conditions of a basic version, a NVH version, and a durability version. According to the Miner cumulative damage hypothesis, the equivalent durability mileage of 150,000 km is converted. The prototype machine is simulated and verified on the test bench, and the test results show that the wheel-side electric drive system has a reliable output performance. The equivalent damage of the comprehensive load spectrum is 63.27%, where the 2# stage driving gear is the most vulnerable component of the whole system. The research in this paper can provide data support for damage calculation and lightweight optimization with modularized development and applications in the future. Full article

In order to resolve the issues of low efficiency and poor precision in the traditional finishing process of hardened internal gears, a method is proposed for calculating the profile curves of a drum-shaped grinding tool suitable for mass finishing of hardened internal gears. Additionally, the impact of drum-shaped grinding tool installation errors on the tooth surface deviation of internal gears is analyzed. Firstly, the processing principle for the generation grinding of internal gears by the drum-shaped grinding tool is introduced. Based on differential geometry, meshing theory, and two-degree-of-freedom enveloping method, a mathematical model is developed for the generation grinding of internal gears. Profile curves of the drum-shaped grinding tool are obtained by solving the meshing equation between the drum-shaped grinding tool and the internal gear. Then, the tooth surface equation for the internal gear is derived in the presence of drum-shaped grinding tool installation errors. By discretizing the error tooth surface of the internal gear, the average normal deviation of the tooth surface is calculated. In the end, the distribution of normal deviation on the tooth surface of the internal gear with different drum-shaped grinding tool installation errors is acquired, and the influence of four kinds of installation errors on the tooth surface of the internal gear is analyzed. The sensitive direction is identified for drum-shaped grinding tool installation errors on the tooth surface of the internal gear. Consequently, this research provides a calculation method for the drum-shaped grinding tool fit for high-precision and high-efficiency finishing of mass-produced hardened internal gear and offers a reference for correcting deviation in the tooth surface of internal gear with installation errors of the drum-shaped grinding tool. Full article

Due to the existence of machining and installation errors, axis parallelism error of gear pairs occurs, which causes eccentric load and mesh in-out impact, thus weakening loaded transmission character. To solve this problem, the axis parallelism error of gear pairs was equated with tooth axial inclination error based on the gear-meshing principle. On this basis, we established the tooth modification model with tooth axial inclination error as the variable according to involute helical gear form-grinding process. Then, the degradation of loaded transmission character caused by axis parallelism error of gear pairs was quantitatively analyzed. The gear grinding, gear measuring, and gearbox vibration measuring were, respectively, performed on high-precision CNC horizontal gear form-grinding machine tool L300G, Gleason 350 GMS, and JWY-II multifunctional gearbox loading test bench. The results show that the proposed method can effectively reduce eccentric load and mesh in-out impact and significantly improve loaded transmission character. Therefore, it can provide a theoretical and experimental basis for the research of high-performance gear-grinding technology of gear-grinder machines. Full article

In the manufacturing industry, grinding is used as a major process for machining difficult-to-cut materials. Grinding is the most complicated and precise machining process. For grinding machines, continuous generating gear grinding machines are widely used to machine gears which are essential machine elements. However, due to its complicated process, it is very difficult to design a reliable measurement method to identify the grinding wheel loading phenomena during the grinding process. Therefore, this paper proposes a measurement method to identify the grinding wheel loading phenomenon in the grinding process for continuous generating gear grinding machines. In the proposed approach, an acoustic emission (AE) sensor was embedded to monitor the grinding wheel conditions; an offline digital image processing technique was used to determine the loading areas over the surface of Al₂O₃ grinding wheels; and surface roughness of the ground workpiece was measured to quantify its machining quality. Then these three data were analyzed to find their correlation. The experimental results have shown that there are two stages of grinding in the grinding process and the proposed measurement method can provide a quantitative grinding wheel loading evaluation from the AE signals online. Full article

The tooth profile modification of cycloidal gears is important in the design and manufacture of precision reducers or rotary vector (RV) reducers for robots. The traditional modification design of cycloidal gears is mainly realized by setting various machining parameters, such as the size and center position of the grinding wheel. The traditional modification design has some disadvantages such as complex modification calculation, uncontrollable tooth profile curve shape and unstable meshing performance. Therefore, a new tooth profile modification method is proposed based on the consideration of the comprehensive influences of pressure angle distribution, meshing backlash, tooth tip and root clearance. Taking the pressure angle and modifications of tooth profile as the parameters of the modification function and the meshing backlash of gear teeth as constraints, the mathematical model for tooth profile modifications is built. The modifications are superimposed on the normal direction of the theoretical profile—the force transmission direction. The mathematical relationship between the modifications and the pressure angle distribution, which determines the force transmission performance, is established. Taking the straight line method, cycloid method and catenary method as examples, by means of the tooth contact analysis technology, the transmission error and minimum meshing backlash, which reflects the lost motion, of the newly modified profile are analyzed and verified. This proposed method can flexibly control the shape change of the modification profile and accurately pre-control the transmission accuracy of the cycloid-pin gear. It avoids the disadvantages of traditional modification methods, such as uncontrollable tooth profile shape and unstable meshing accuracy. The method allows good meshing characteristics, high force transmission performance and more precise tooth profile curve. The study provides a new design method of the modified profile of cycloidal gears. Full article

(1) The alloy material 20CrMnTiH is widely used in gear manufacturing, but difficult to process, and its quantity (efficiency) and quality (surface quality) are generally negative correlation indicators. As a difficult but realistic problem, it is of important practical significance to explore how to efficiently grind high-precision low-carbon alloy gear workpieces. (2) Firstly, the pixel method was applied to analyze the grinding principles and explore the grinding parameters—the grinding wheel speed and grinding wheel frame moving speed—as well as the feed rate, which impacts the grinding indicators. Secondly, based on the ceramic microcrystalline corundum grinding wheel and the 20CrMnTiH gear workpiece, controlled experiments with 28 groups of grinding parameters were conducted. Moreover, the impact curves of the grinding parameters on the grinding indicators—the grinding efficiency, grinding wheel life, and surface roughness—were obtained by the multiple linear regression method. Finally, the multi-objective optimization method was used to comprehensively optimize the grinding process. (3) Compared with the traditional grinding process, under optimized grinding parameters, the 20CrMnTiH gear workpieces have a lower surface roughness and a longer grinding wheel life, and require a shorter time to achieve grinding accuracy. (4) The grinding experiments showed that the grinding parameters are linearly related to the grinding indicators. The optimization results show that the precision, efficiency, and economy of the 20CrMnTiH gear grinding process have been improved via the comprehensive optimization of the grinding parameters. Full article