2011 IEEE 2nd International Conference on Computing, Control and Industrial Engineering 2011
DOI: 10.1109/ccieng.2011.6008077
|View full text |Cite
|
Sign up to set email alerts
|

Optimal design of two-stage Helical Gear Reducer based on MATLAB

Abstract: In the course of the optimal design of Two-stage function, Selecting the design variables, Setting constraint conditions, we could build the optimization model of Two-stage of Helical Gear Reducer Using the MATLAB Optimization Toolbox and its algorithm, what we want is to make the reducer smallest and save more materials. Through analysis of the outcomes compared with the design data, the optimized objective value has reduced by Ǥ ૡΨ, and the centre distance by Ǥ Ψ, It turns out that Based on this algorithm it… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
0
0

Year Published

2013
2013
2013
2013

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 1 publication
0
0
0
Order By: Relevance
“…[2]. Due to most of the mechanical optimization designs are the nonlinear constrained optimization problems, usually they are converted into the simpler sub-problems, the commonly solving method is that we construct the penalty function by converting the constrained optimization to an unconstrained optimization problem [3]. Today this method has been replaced by K-T (Kuhn-Tucker) equations which are more effective.…”
Section: Solving the Model With Matlabmentioning
confidence: 99%
“…[2]. Due to most of the mechanical optimization designs are the nonlinear constrained optimization problems, usually they are converted into the simpler sub-problems, the commonly solving method is that we construct the penalty function by converting the constrained optimization to an unconstrained optimization problem [3]. Today this method has been replaced by K-T (Kuhn-Tucker) equations which are more effective.…”
Section: Solving the Model With Matlabmentioning
confidence: 99%