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Analysis and Prediction of Melt Pool Geometry in Rectangular Spot Laser Cladding Based on Ant Colony

Junhua Wang1, Jiameng Wang1, Xiaoqin Zha2

  • 1School of Mechanical and Electrical Engineering, Henan University of Science and Technology, Luoyang 471003, China.

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|March 6, 2025
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Summary
This summary is machine-generated.

This study developed a melt pool monitoring system for rectangular spot laser cladding to predict melt pool dimensions. An optimized Support Vector Regression model achieved high accuracy in predicting melt pool width and area, improving cladding quality.

Keywords:
ACO-SVRmelt pool areamelt pool widthwide beam laser cladding

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Area of Science:

  • Materials Science and Engineering
  • Manufacturing Technology
  • Additive Manufacturing

Background:

  • Rectangular spot laser cladding offers high efficiency but can compromise melt pool stability and cladding quality.
  • Accurate prediction of melt pool morphology is crucial for controlling quality in wide beam laser cladding.

Purpose of the Study:

  • To develop a melt pool monitoring system for real-time prediction of melt pool morphology and size during rectangular spot laser cladding.
  • To establish an accurate prediction model for melt pool width and area using Support Vector Regression (SVR) optimized with Ant Colony Optimization (ACO).

Main Methods:

  • Real-time monitoring of melt pool morphology using a developed system.
  • Image processing techniques to extract melt pool width and area.
  • Development and optimization of a Support Vector Regression (SVR) model using Ant Colony Optimization (ACO) with laser power, scanning speed, and powder feed rate as inputs.

Main Results:

  • The Ant Colony Optimization-Support Vector Regression (ACO-SVR) model accurately predicted melt pool width with a relative error below 2.2%.
  • The ACO-SVR model achieved a relative error of less than 9.13% in predicting melt pool area.
  • The developed system and model enable precise control over melt pool dimensions in laser cladding.

Conclusions:

  • The ACO-SVR model provides a reliable method for predicting melt pool dimensions in rectangular spot laser cladding.
  • The melt pool monitoring system and predictive model contribute to enhanced quality control in high-efficiency laser cladding processes.
  • Accurate prediction of melt pool width and area is achievable, addressing challenges associated with melt pool stability.