Alessio Artoni

Optimization of the Loaded Contact Pattern in Hypoid Gears by Automatic Topography Modification

Systematic optimization of the tooth contact pattern under load is an open problem in the design of spiral bevel and hypoid gears. In order to enhance its shape and position, gear engineers have been assisted by numerical tools based on trial-and-error approaches, and/or they have been relying on the expertise of skilled operators. The present paper proposes a fully automatic procedure to optimize the loaded tooth contact pattern, with the advantage of eventually reducing design time and cost. The main problem was split into two identification subproblems: first, to identify the ease-off topography capable of optimizing the contact pattern; second, to identify the machine-tool setting variations required to obtain such ease-off modifications. Both of them were formulated and solved as unconstrained nonlinear optimization problems. In addition, an original strategy to quickly approximate the tooth contact pattern under load was conceived. The results obtained were very satisfactory in terms of accuracy, robustness, and computational speed. They also suggest that the time required to optimize the contact pattern can be significantly reduced compared with typical time frames. A sound mathematical framework ensures results independent of the practitioner’s subjective decision-making process. By defining a proper objective function, the proposed method can also be applied to affect other contact properties, such as to improve the motion graph or to decrease the sensitivity of the transmission to assembly errors. Furthermore, it can be easily adapted to any gear drive by virtue of its systematic and versatile nature.

An Ease-Off Based Optimization of the Loaded Transmission Error of Hypoid Gears

Loaded transmission error (LTE) is one of the primary sources of gear noise and vibration. While ease-off topography has been shown to be powerful in improving the contact properties of a gear drive, its optimization to minimize LTEs has been an open problem in the gear literature. Through the formulation of an appropriate nonlinear optimization problem, this study proposes a novel methodology to systematically define optimal ease-off topography to simultaneously minimize LTEs and contact pressures, while concurrently confining the loaded contact pattern within a prescribed allowable region on the tooth surface to avoid any edge- or corner-contact condition. Effectiveness of this optimization is presented using a face-milled and a face-hobbed hypoid gear examples. These example analyses reveal particularly promising results that feature both a drastic reduction in LTE and an appreciable decrease in the maximum contact stress. Although the method is employed here for hypoid gears, its intrinsically systematic formulation enables straightforward applicability to any kind of gears. The methodology presented in this work can be a useful aid for gear engineers to determine optimal ease-off topographies without having to rely on time-consuming trial-and-error approaches or on a priori subjective judgments.

Nonlinear Identification of Machine Settings for Flank Form Modifications in Hypoid Gears

This paper presents a new systematic method for identifying the values of the machine-tool settings required to obtain flank form modifications in hypoid gears. The problem is given a nonlinear least-squares formulation, and it is solved by the Levenberg-Marquardt method with a trust-region strategy. To test the method, the same ease-off topography was obtained by means of very different sets of machine-tool settings, including a set of only kinematic parameters and a highly redundant set of 17 parameters. In all cases, the goal was achieved in a few iterations, with residual errors well below machining tolerances and, even more importantly, with realistic values of all parameters. Therefore, significant improvements in practical gear design can be achieved by employing the overall proposed procedure.

Multi-Objective Ease-Off Optimization of Hypoid Gears for Their Efficiency, Noise, and Durability Performances

Micro-geometry optimization has become an important phase of gear design that can remarkably enhance gear performance. For spiral bevel and hypoid gears, micro-geometry is typically represented by ease-off topography. The optimal ease-off shape can be defined as the outcome of a process where generally conflicting objective functions are simultaneously minimized (or maximized), in the presence of constraints. This matter naturally lends itself to be framed as a multi-objective optimization problem. This paper proposes a general algorithmic framework for ease-off multi-objective optimization, with special attention to computational efficiency. Its implementation is fully detailed. A simulation model for loaded tooth contact analysis is assumed to be available. The proposed method is tested on a face-hobbed hypoid gear set. Three objectives are defined: maximization of mechanical efficiency, minimization of loaded transmission error, minimization of maximum contact pressure. Bound constraints on the design variables are imposed, as well as a nonlinear constraint aimed at keeping the loaded contact pattern inside a predefined allowable contact region. The results show that the proposed method can obtain optimal ease-off topographies that significantly improve the basic design performances. It is also evident that the method is general enough to handle geometry optimization of any gear type.© 2011 ASME

Robust Optimization of Cylindrical Gear Tooth Surface Modifications Within Ranges of Torque and Misalignments

Tooth surface modifications are small, micron-level intentional deviations from perfect involute geometries of spur and helical gears. Such modifications are aimed at improving contact pressure distribution, while minimizing the motion transmission error to reduce noise excitations. In actual practice, optimal modification requirements vary with the operating torque level, misalignments, and manufacturing variance. However, most gear literature has been concerned with determining optimal flank form modifications at a single design point, represented by fixed, single load and misalignment values. A new approach to the design of tooth surface modifications is proposed to handle such conditions. The problem is formulated as a robust design optimization problem, and it is solved, in conjunction with an efficient gear contact solver (Load Distribution Program (LDP)), by a direct search, global optimization algorithm aimed at guaranteeing global optimality of the obtained microgeometry solutions. Several tooth surface modifications can be used as microgeometry design variables, including profile, lead, and bias modifications. Depending on the contact solver capabilities, multiple performance metrics can be considered. The proposed method includes the capability of simultaneously and robustly handling several conflicting design objectives. In the present paper, peak contact stress and loaded transmission error amplitude are used as objective functions (to be minimized). At the end, two example optimizations are presented to demonstrate the effectiveness of the proposed method.

On the Identification of Machine Settings for Gear Surface Topography Corrections

In this paper we set out to investigate the performances of some of the algorithms proposed in the gear literature for identifying the machine-settings required to obtain predesigned gear tooth surface topographies, or needed to compensate for flank form deviations of real teeth. For the ease of comparison, the problem is formulated as a nonlinear least-squares minimization, and the most widely employed algorithms are derived as particular cases. The algorithms included in the analysis are: (i) one-step methods; (ii) iterative methods; (iii) iterative methods with step control. The performance index is devised in their ability of returning practical solutions in the presence of: (i) strong model nonlinearities, (ii) ill-conditioning of the sensitivity matrix, (iii) demanding topographic shapes purposely selected. Instrumental here is an original classification of topographic modifications as either “simple” or “complex”, based on the SVD analysis of the sensitivity matrix. On the basis of the numerical tests documented, iterative techniques with step control seem the most convenient, due to reliability and robustness of the solutions produced. The generation process here considered is face-milling of hypoid gears, even though the methodology is general enough to cope with any gear cutting method requiring only some minor technical changes.Copyright

A Computational Framework for Environment-Aware Robotic Manipulation Planning

In this paper, we present a computational framework for direct trajectory optimization of general manipulation systems with unspecified contact sequences, exploiting environmental constraints as a key tool to accomplish a task. Two approaches are presented to describe the dynamics of systems with contacts, which are based on a penalty formulation and on a velocity-based time-stepping scheme, respectively. In both cases, object and environment contact forces are included among the free optimization variables, and they are rendered consistent via suitably devised sets of complementarity conditions. To maximize computational efficiency, we exploit sparsity patterns in the linear algebra expressions generated during the solution of the optimization problem and leverage Algorithmic Differentiation to calculate derivatives. The benefits of the proposed methods are evaluated in three simulated planar manipulation tasks, where essential interactions with environmental constraints are automatically synthesized and opportunistically exploited.

Synthesis of hypoid gear surface topography by a nonlinear least squares approach

This paper outlines a systematic methodology for finding the machine setting corrections required to obtain a predesigned ease-off surface in spiral bevel and hypoid gear teeth. The problem is given a nonlinear least squares formulation which, however, is highly prone to numerical instabilities. The Levenberg–Marquardt algorithm with a trust region strategy turned out to be quite effective and robust to obtain feasible solutions. The proposed method was tested on lengthwise crowning, profile crowning and spiral angle correction. In all cases, the goal was achieved with very high accuracy, in a few iterations and, remarkably, with different sets of machine parameters.Copyright

Grinding face-hobbed hypoid gears through full exploitation of 6-axis hypoid generators

Methods for accurate grinding of face-hobbed bevel gears have not been developed to date, the main obstacles being their epicycloidal lengthwise tooth curve and slot width taper. Grinding them while preserving their geometry would be desirable, as the epicycloidal tooth curve makes face-hobbed gears less sensitive to misalignments and deflections. To this end, we propose a method based on a flared-cup grinding wheel, whereby generated members are ground by a two-parameter enveloping process, while non-generated ones are finished by a one-parameter enveloping motion. Machine motions are synthesized exploiting the capabilities of 6-axis hypoid generators. Interference between parts is avoided.

A COMPUTATIONAL STRATEGY FOR TRAJECTORY OPTIMIZATION OF UNDERACTUATED MULTIBODY SYSTEMS WITH CONTACTS

In this paper we propose a strategy for improving the computational efficiency of direct methods for trajectory optimization of multibody systems. We particularly focus on those applications where the system necessarily has to interact with the surrounding environment through intermittent contacts. The problem is hereby formulated such that just the initial and final states of the system over a given time interval are prescribed, so as to let the solver automatically synthesize the best contact sequence to accomplish the considered task. The proposed computational strategy consists in: (i) solving a preliminary optimization problem that roughly approximates the original one, but differs from it by one or more conveniently chosen parameters and is faster to solve; (ii) using the obtained solution as an initial guess for the actual (fullfledged) optimal control problem. The performance of the method is evaluated in a simulated planar system, whose peculiarity is to be trivially underactuated. An extensive investigation is presented which shows how a proper choice of the parameters in the preliminary optimization can lead to a significant reduction in the computational effort required to solve the problem. The results we present assess both the validity and the robustness of the proposed method.