A Novel Multi-Objective Dynamic Reliability Optimization Approach for a Planetary Gear Transmission Mechanism

Planetary gear transmission mechanisms (PGTMs) are widely used in mechanical transmission systems due to their compact structure and high transmission efficiency. To implement the reliability design and optimization of a PGTM, a novel multi-objective dynamic reliability optimization approach is prop...

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Bibliographic Details
Published inAxioms Vol. 13; no. 8; p. 560
Main Authors Tong, Shuiguang, Yan, Xiaoyan, Yang, Lechang, Yang, Xianmiao
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.08.2024
Subjects
Accuracy
Adaptive algorithms
AMOEA/D
Damage accumulation
Design and construction
Design optimization
Efficiency
Evolutionary algorithms
Fatigue failure
Gear trains
Gearing, Planetary
Genetic algorithms
Load
Mathematical optimization
Mechanical transmissions
Monte Carlo simulation
Multiple objective analysis
Objectives
Optimization models
Particle swarm optimization
planetary gear
random forest
Random variables
Reliability analysis
reliability optimization
Structural reliability
System reliability
Transmission efficiency
China
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Summary:Planetary gear transmission mechanisms (PGTMs) are widely used in mechanical transmission systems due to their compact structure and high transmission efficiency. To implement the reliability design and optimization of a PGTM, a novel multi-objective dynamic reliability optimization approach is proposed. First, a multi-objective reliability optimization model is established. Furthermore, considering the strength degradation of gears during service, a dynamic reliability analysis is conducted based on the theory of nonlinear fatigue damage accumulation. In addition, to improve computing efficiency, a random forest surrogate model based on the particle swarm optimization algorithm is proposed. Finally, an adaptive multi-objective evolutionary algorithm based on decomposition (AMOEA/D) is designed to optimize the mechanism, along with an adaptive neighborhood updating strategy and a hybrid crossover operator. The feasibility and superiority of the proposed approach are verified through an NGW planetary gear reducer. The results show that the proposed surrogate model can reduce the calculation cost and has high accuracy. The AMOEA/D algorithm can improve transmission efficiency, reduce gear volume and ensure reliability at the same time. It can provide guidance for actual gear production.
ISSN:2075-1680
2075-1680
DOI:10.3390/axioms13080560