Bio: Shankar Krishnapillai is an academic researcher from Indian Institutes of Technology. The author has an hindex of 1, co-authored 1 publication(s) receiving 8 citation(s).
••10 Jul 2017
Abstract: When designing helical gears, the goal is to optimize gear weight, efficiency, and noise while simultaneously achieving the required strength. In this study, the macro geometry of a helical gear pair was optimized for low weight, high efficiency, and low noise; further, trends of optimal solutions for five combinations of the three objectives were analyzed. The gear mass and efficiency were directly used as the design objectives. However, since the calculation of the gear noise is generally very complicated and time-consuming, the gear noise has not been directly used as the design objective, and the peak-to-peak static transmission error (PPSTE), which is the main source of the gear vibration, was selected as the design objective for the gear noise in the optimization. The objectives exhibited a trade-off relation between each other in the optimal space. If one of them was omitted, the objective considerably deteriorated. To analyze the results, the objectives were normalized and scored. As a result, most of the top ranks were from the optimal solutions considering the mass, efficiency, and PPSTE. Therefore, all three objectives should be considered in the gear optimization for low weight, high efficiency, and low noise.
Vilmos Simon1•Institutions (1)
TL;DR: By the optimization considerable improvements in the operating characteristics of the gear pair are achieved, and the goals of the optimization are achieved by the optimal modification of meshing teeth surfaces.
Abstract: In this paper a multi-objective optimization method of hypoid gears correlating to the operating characteristics is presented. Optimal design of hypoid gears demands that multiple objectives be simultaneously achieved. Four objectives considered in this study are the minimization of the maximum tooth contact pressure, transmission error and the average temperature in the gear mesh, and the maximization of the mechanical efficiency of the gear pair. The goals of the optimization are achieved by the optimal modification of meshing teeth surfaces. In practice, these modifications are introduced by applying the appropriate machine tool setting for the manufacture of the pinion and the gear, and/or by using a tool with an optimized profile. The proposed optimization procedure relies heavily on the loaded tooth contact analysis for the prediction of tooth contact pressure distribution and transmission errors, and on the mixed elastohydrodynamic analysis of lubrication to determine temperature and efficiency. A fast elitist nondominated sorting genetic algorithm (NSGA-II) is applied to solve the model. The effectiveness of the method is demonstrated by using hypoid gear examples. The obtained results have shown that by the optimization considerable improvements in the operating characteristics of the gear pair are achieved.
TL;DR: An extended version of an optimal weight design problem available in literature is investigated using multi-objective teaching and learning-based optimization (MOTLBO) and reflects the trade-off effects of multiple objectives by increase in optimal weight value as compared to previous studies.
Abstract: The optimization of gears is crucial to the development of energy efficient mechanical systems. Weight, volume and power output are major objectives dependent on reduced inertia of rotary, mobile s...
••01 Oct 2019
TL;DR: A bevel gear pair is optimized using Nature inspired algorithms, namely, simulated annealing, fire fly, cuckoo search and fmincon solver employed in MATLAB environment to minimize the volume of the gear.
Abstract: Gears are used to transmit mechanical power in systems such as automotives, automation and machine tools. The demand for lighter and optimally designed gears is high in power transmission systems, as they save material, energy and also considerably influence performance. Hence, in this paper, a bevel gear pair is optimized. The problem consists of a non linear objective function, four design variables and eight inequality constraints. The objective is to minimize the volume of the gear. The design variables are: number of teeth, module, face width and diameter of the shaft, which is a new addition. Apart from considering regular mechanical constraints, six other additional critical constraints on contact ratio, load carrying capacity, power loss, root not cut, no involute interference and line of action are also included. Nature inspired algorithms, namely, simulated annealing, fire fly, cuckoo search and fmincon solver are employed in MATLAB environment. Results of simulation are analysed, compared and validated with literature.
Abstract: A novel multi-objective optimization of planetary gearbox is presented using a discrete version of Non-Dominated Sorting Genetic Algorithm (NSGA-II). Minimization of weight and total power loss of planetary gearbox are two objective functions. Number of teeth in the sun, planet and ring gears, module, face width, input shaft and planet pin diameter are design variables. Regular mechanical, bearing selection and scuffing are various design constraints considered. Investigations were done for three different gear profiles on an industrial planetary gearbox. The results were compared with an industrial gearbox provided in the AGMA standard, which showed not only significant reduction of weight and power loss, but were also found safer in scuffing. Pareto fronts of different ISO grade oils were compared for all gear profiles, and ISO VG 460 was found to be the best oil. Further analysis without a scuffing constraint showed moderate to high levels of scuffing risk for lower-grade ISO oils and lower level risk for higher-grade ISO oils. Ultimately, this study helps to reduce weight, enhance the efficiency and prevent early failures in planetary gearbox.
Author's H-index: 1