Multi-Objective Optimization of Two Stage Spur Gearbox Using NSGA-II
10 Jul 2017-
About: The article was published on 2017-07-10. It has received 11 citations till now.
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TL;DR: In this paper, 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.
43 citations
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.
30 citations
TL;DR: In this article, a multi-objective optimization of planetary gearbox using a discrete version of Non-Dominated Sorting Genetic Algorithm (NSGA-II) is presented.
15 citations
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...
14 citations
TL;DR: The combined optimization of volume, centre-distance and power output reveals key insights for the design of compact gearboxes.
Abstract: Gears are crucial elements in mechanical systems and contribute to the overall performance of machinery As such, optimization of gearbox transmission systems remains a challenging problem faced by researchers and designers for numerous years In the present work, three objectives viz volume, power output and centre-distance are investigated simultaneously A two-stage spur gearbox design problem is formulated with eight design variables viz face-width (stage 1), face-width (stage 2), shaft diameter (stage 1), shaft diameter (stage 2), module, pinion teeth number(stage 1) and pinion teeth number (stage 2) considered Two geometric and three design constraints are formulated Pareto frontiers are generated using NSGA-II evolutionary algorithm The Pareto frontier is investigated using decision tools viz FUZZY, LINMAP and TOPSIS and the best solutions selected using the deviation index Validation of results was done using previous reports in the literature and geometric modelling software Variation and sensitivity studies indicate that module, pinion tooth number and face-width variables had a higher influence on volume as compared to power output and centre-distance The combined optimization of volume, centre-distance and power output reveals key insights for the design of compact gearboxes
11 citations
References
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TL;DR: This paper extends NSGA-III to solve generic constrained many-objective optimization problems and suggests three types of constrained test problems that are scalable to any number of objectives and provide different types of challenges to a many- objective optimizer.
Abstract: In the precursor paper, a many-objective optimization method (NSGA-III), based on the NSGA-II framework, was suggested and applied to a number of unconstrained test and practical problems with box constraints alone. In this paper, we extend NSGA-III to solve generic constrained many-objective optimization problems. In the process, we also suggest three types of constrained test problems that are scalable to any number of objectives and provide different types of challenges to a many-objective optimizer. A previously suggested MOEA/D algorithm is also extended to solve constrained problems. Results using constrained NSGA-III and constrained MOEA/D show an edge of the former, particularly in solving problems with a large number of objectives. Furthermore, the NSGA-III algorithm is made adaptive in updating and including new reference points on the fly. The resulting adaptive NSGA-III is shown to provide a denser representation of the Pareto-optimal front, compared to the original NSGA-III with an identical computational effort. This, and the original NSGA-III paper, together suggest and amply test a viable evolutionary many-objective optimization algorithm for handling constrained and unconstrained problems. These studies should encourage researchers to use and pay further attention in evolutionary many-objective optimization.
1,247 citations
TL;DR: Two advanced optimization algorithms known as particle swarm optimization (PSO) and simulated annealing (SA) are presented to find the optimal combination of design parameters for minimum weight of a spur gear train.
152 citations
01 Dec 1998
TL;DR: In this paper, an optimal weight design problem of a gear for a constrained bending strength of gear, tortional strength of shafts and each gear dimension was formulated as a nonlinear integer programming (NIP) problem and solved directly by keeping the nonlinear constraint by using an improved GA.
Abstract: In this paper, we formulate an optimal weight designproblem of a gear for a constrained bending strength of gear, tortional strength of shafts and each gear dimension as a nonlinear integer programming (NIP) problem and solve it directly by keeping the nonlinear constraint by using an improved genetic algorithm (GA). We discuss the efficency of the proposed method.
94 citations
TL;DR: In this article, the authors presented an extensive campaign of experimental tests in an FZG test rig and an average coefficient of friction between meshing gears was devised from the experimental results.
78 citations
Book•
23 Aug 2012
TL;DR: In this paper, the authors discuss the integration of zupcanih prijenosa in the standard DIN 3996 and DIN 17485 standard, and show how po novim ISO i DIN standardima kontroliraju cvrstoce boka zuba na pitting and mikro-pitting, cvstoca korijena zuba, and nosivost zupcanika na zaribavanje.
Abstract: U prvom dijelu knjige predstavljena je podjela mehanickih prijenosa i zupcanih prijenosa snage te analizirana bilanca snage visestupanjskih prenosnika, dok je u drugom dijelu obrađena geometrija ozubljenja s težistem na teoriju evolventnog ozubljenja. Temeljito su obrađene smetnje pri izradi i u zahvatu evolventnih zupcanika te tolerancije cilindricnih zupcanika i cilindricnih zupcanih parova. U trecem dijelu udžbenika razmotrili su se uvjeti pod kojima integritet zupcanih prijenosa može biti narusen. Pokazano je kako se racunaju teoretske a kako stvarne vrijednosti opterecenja zuba, tj. zupcanika te kako se po novim ISO i DIN standardima kontroliraju cvrstoce boka zuba na pitting i mikro-pitting, cvrstoca korijena zuba te nosivost zupcanika na zaribavanje. U cetvrtom dijelu sažeta su dosadasnja iskustva u konstruiranju cilindricnih zupcanih prenosnika. Posebna pažnja posvecena je izboru materijala zupcanika, njihovoj obradi i proracunu temperature ulja, jednom od kljucnih parametara integriteta zupcanika. Konicni zupcanici obrađeni su u petom dijelu udžbenika. Narocito opsirno su obrađeni nacini izrade konicnih zupcanika, proracuni njihova integriteta i kontrola kvalitete prema novom standardu ISO 17485. U sestom dijelu udžbenika obrađeni su planetni prijenosi – najsloženiji prijenosi snage, kako po strukturi, tako i po međusobnom odnosu opterecenja, brzina i snage, tj. prijenosnih omjera i stupnjeva iskoristivosti. Posebna pažnja posvecena je specijalnim izvedbama jednostupanjskih planetnih prijenosa te sastavljenim planetnim prijenosima. Gradivo je popraceno s nizom 2-D i 3-D crteža i shema koji vode citatelja boljem razumijevanju napisanog. U sedmom dijelu obrađeni su pužni prijenosi. Narocita pažnja posvecena je problematici izrade puževa i pužnih kola i proracunima integriteta. Stupnjevi iskoristivosti i proracuni nosivosti obrađeni su prema novom standardu DIN 3996 a kontrole mjernih velicina i tolerancije puža, pužnog kola i pužnog para prema novom DIN 3974.
77 citations