Parameters Optimization of Laser Shot Peening Based on Multi-Island Genetic Algorithm

W. Wang; Jian Zhong Zhou; Shu Huang; Yu Jie Fan; C.D. Wang; J.R. Fan

doi:10.4028/www.scientific.net/AMM.43.387

Paper Titles

The Application of CAN Bus in Monitoring and Controlling System for Combine Harvester
p.366

Transistor Compensation Technology of Pressure Sensor Sensitivity Temperature Coefficient
p.371

The Analysis of Static and Dynamic Characteristics of Motorized High-Speed Spindle Based on Sensitivity Analysis of FEM Model
p.376

Simulation and Optimization of Job Shop Scheduling for Dry Transformers Based on eM-Plant
p.382

Parameters Optimization of Laser Shot Peening Based on Multi-Island Genetic Algorithm
p.387

Antifriction Effect of Micro-Deep Holes for Higher Pair Components
p.391

Study on the Inner Helical Gear Form Grinding Wheel Dressing Technology
p.397

Research on the Key Process Parameters in Direct Laser Deposition Using Coaxial Inside-Beam Wire Feeding
p.401

Research on the Equipment for Electrostatic Flocking of the Activated Carbon Fibers
p.405

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 43Parameters Optimization of Laser Shot Peening...

Parameters Optimization of Laser Shot Peening Based on Multi-Island Genetic Algorithm

Abstract:

Laser shot peening (LSP) has recently received more and more attention as a viable laser processing technology, since it can obtain the desirable residual compressive stress to improve fatigue life of the material by precisely controlling laser parameters. The purpose of this paper is mainly to explore the optimal residual compressive stress in the surface layer during LSP by statistical optimization algorithm. Based on the finite element analysis software ANSYS, Multi-island Genetic Algorithm (MIGA) is adopted to find the best solution of design requirements, the control parameters are laser pulse energy and spot diameter, while the aim parameters are residual compressive stress and deformation values, respectively. The results indicate that the optimal residual compressive stress obtained by integrated optimization technique can significantly improve the mechanical properties of the target after LSP. It provides a guiding importance for parameters optimization in future experimental research and practical application.