Back to Search
Start Over
Research on Multistage Rotor Assembly Optimization Methods for Aeroengine Based on the Genetic Algorithm
- Source :
- Complexity, Vol 2021 (2021)
- Publication Year :
- 2021
- Publisher :
- Hindawi Limited, 2021.
-
Abstract
- The coaxiality and unbalance are the two important indexes to evaluate the assembly quality of an aeroengine. It often needs to be tested and disassembled repeatedly to meet the double-objective requirements at the same time. Therefore, an intelligent assembly method is urgently needed to directly predict the optimal assembly orientations of the rotors at each stage to meet the double-objective requirements simultaneously. In this study, an assembly optimization method for the multistage rotor of an aeroengine is proposed based on the genetic algorithm. Firstly, a spatial location propagation model is developed to accurately predict the spatial position of each rotor after assembly. The alignment process of the assembly screw holes of the adjacent rotors is considered for the first time. Secondly, a new assembly optimization strategy is proposed to select different assembly data for the specific values of the coaxiality and unbalance, respectively. Finally, a double-objective fitness function is constructed based on the coaxiality and unbalance. The simulation and experimental results show that the assembly optimization method proposed in this study can be utilized to achieve synchronous optimization of the coaxiality and unbalance of an aeroengine during preassembly.
- Subjects :
- 0209 industrial biotechnology
Multidisciplinary
Fitness function
Article Subject
General Computer Science
Rotor (electric)
Computer science
020209 energy
Process (computing)
QA75.5-76.95
02 engineering and technology
law.invention
020901 industrial engineering & automation
Control theory
law
Position (vector)
Electronic computers. Computer science
Genetic algorithm
0202 electrical engineering, electronic engineering, information engineering
Optimization methods
Subjects
Details
- ISSN :
- 10990526 and 10762787
- Volume :
- 2021
- Database :
- OpenAIRE
- Journal :
- Complexity
- Accession number :
- edsair.doi.dedup.....43002d218a98bb1cce58300f2714d4a3