Multiobjective Optimisation of Bevel Gear Pair design using NSGA-II

Chandrasekaran, Gokul; Sreebalaji, V.S.; Saravanan, R.; Maniraj, J.

doi:10.1016/j.matpr.2019.05.101

Cited by 6 publications

(4 citation statements)

References 7 publications

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“…The popularity of NSGA-II means that it has been coded in several computer-programming languages. Many researches cited in their work numerous studies using this algorithm, for example in building design ( [42], [43]) and especially in the field of gears ( [44], [13])…”

Section: Description Of the Retained Optimization Algorithmmentioning

confidence: 99%

“…Multi-objective processes are increasingly used in gear design optimization, mainly due to the contradictory requirements (one solution may be better than another for some objectives and worse for other objectives). They are interested in optimization of various kinds of gears; namely, bevel gears ( [11], [12], [13]), planetary gears ( [14], [15], [16], [17]), cylindrical gears e.g. [18].…”

Section: Introductionmentioning

confidence: 99%

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Multi-objective optimization of gear unit design to improve efficiency and transmission error

Younes

Changenet

Bruyère

et al. 2022

Mechanism and Machine Theory

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This study aims to implement multi-objective optimization of a gear unit in order to minimize the power loss and the vibrational excitation generated by the meshing, via a multi-scale approach that extends from gear contact to the complete transmission. All these indicators are closely linked to the macro and micro-geometry definition of the gear pair. The optimization is carried out using a genetic algorithm, namely the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The design variables chosen for the problem are the pressure angle and the helix angle, as macro-geometry characteristics of the gear, and/or the length and the amount of tooth profile modifications, as micro-geometry characteristics of the gear. Constraints are imposed in order to not exceed a maximum bending stress at the tooth root of the gear and to not fall below a minimum total contact ratio. From the results obtained, it is found that the multi-objective optimization with both micro and macro-geometry parameters simultaneously gives different results than those obtained with macro-geometry first and then micro-geometry parameters. In order to study the importance, or not, to take into account the complete gear unit, a comparison is made between the local power loss generated by gear tooth friction and the total power loss in the single stage gear unit in terms of design variables values.

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Section: Description Of the Retained Optimization Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of gear unit design to improve efficiency and transmission error

Younes

Changenet

Bruyère

et al. 2022

Mechanism and Machine Theory

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“…Two objective functions are formulated, the first minimizes the volume and the second minimizes the total power loss in the gearbox [28]- [30]. Weight reduction with a simultaneous increase in transmission efficiency, by optimization method, is very much essential for gear applications that transmit very high mechanical power, with a significant speed reduction [31]- [33]. In the process of actual transmission, due to the involved stresses, gears will experience an elastic deformation.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Topological Modification Parameters for Heavy-Duty Helical Gears

Wang

Liu

et al. 2022

IEEE Access

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To improve the meshing state of gear pairs, the abrasion of tooth surfaces must be reduced and on the other hand, the functional requirement of transmission stability for different conditions of heavyduty helical gears must be increased. To do this requires a topological modification of the tooth profile and tooth alignment. The topological modification parameter optimization model is established based on Hertz theory, which takes the functional requirement as a goal, and the tooth surface topological modification parameters as the design variables. The constraint condition equations in the tooth contact analysis process are derived, and the improved genetic algorithm is used to solve the numerical conditions of the tooth surface microgeometry parameter optimization model. Then, the modification parameters optimized by different modification schemes are obtained. The loaded transmission errors, the mesh misalignment movements, and the distribution characteristics of the tooth surface contact stress are studied. The parameter optimization model of the tooth surface topological modification for the functional requirements is established. With different modification parameters heavy-duty helical gear pairs under various loads, the research results provide a theoretical basis for tooth surface micro design of heavy-duty helical gears in practical application and in determining the reasonable modification parameters.INDEX TERMS Heavy-duty helical gears, topological modification, parameter optimization, loaded transmission error, mesh misalignment.

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“…Xu et al [16] used the Euler-Bernoulli beam bending theory to approve the elastic characteristic and particle swarm optimization method for the nonlinear model. Taguchi algorithm for optimization are also engaged to design compliant mechanism [17,18], nonlinear behavior should be investigated. Genetic algorithm (GA) has much utilization in engineering [19,20], especially non dominated sorting genetic algorithm II (NSGA-II) is widespread in design mechanism [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Optimal Design the Compliant Bistable Mechanism based on NSGA-II

Tran¹

2020

IJATCSE

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The bistable mechanism has a vital role in precision engineering and robotics with benefits in free friction, no backlash and saves energy. Multi-objective optimization techniques have many applications in design mechanism. NSGA-II is strengthening in quick sorting procedure and elitist methodology. This article introduces an optimization methodology for design compliant bistable mechanisms by employed non dominated sorting genetic algorithm II (NSGA-II). The method predicts the switching forces in forward and backward motion of the bistable mechanism. The program of NSGA-II was executed in Matlab combine with Abaqus to analyze the mechanism. A flowchart of processing is introduced. An example of a bistable mechanism is investigated and results are adopted by applying NSGA-II in order to verify the method.

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Multiobjective Optimisation of Bevel Gear Pair design using NSGA-II

Cited by 6 publications

References 7 publications

Multi-objective optimization of gear unit design to improve efficiency and transmission error

Multi-objective optimization of gear unit design to improve efficiency and transmission error

Optimization of Topological Modification Parameters for Heavy-Duty Helical Gears

Optimal Design the Compliant Bistable Mechanism based on NSGA-II

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