The purpose of this paper is to investigate the influence of different process parameters on the surface geometric quality characteristics of laser cladding layers and to develop a high accuracy prediction model for the geometric characteristics of single pass laser cladding layers. The surface geometric quality characteristics of the laser cladding layer mainly include the dilution rate and the aspect ratio. The paper designed and completed a full factorial laser cladding experiment of 15-5PH alloy powder coating on the surface of 20Cr13 stainless steel. Based on this experiment, data acquisition of geometric quality characteristics was completed by applying sample processing, tissue observation, and numerical processing. For the analysis of experimental results, this paper conducted single-factor process influence analysis and ternary quadratic regression analysis. Based on the regression model and prediction results, a prediction model and analysis method of geometric quality characteristics based on GWO-DELM intelligent algorithm were constructed. The results of the regression analysis showed that the prediction accuracy of both the dilution rate and the aspect ratio were extremely low and the prediction ability was poor. In order to construct a prediction model of geometric quality characteristics with high accuracy, this paper constructed an analytical model based on the GWO-DELM intelligent algorithm, and trains and tests the factorial experimental data. The evaluation index results were much better than the polynomial and DELM regression models, and the prediction accuracy was better.
Conclusion:
Based on the experiments of all-factor laser cladding process, the application of GWO-DELM intelligent algorithm can establish the prediction model of surface geometric quality characteristics of single-pass cladding layer with good accuracy. This model and analysis method can provide theoretical support for surface geometric quality control of composite laser cladding layers.