Method for predicting geometrical characteristics of laser melting deposition layer

Abstract

The invention discloses a geometric feature prediction method for a laser melting deposition layer. A coaxial powder feeding type laser deposition manufacturing numerical calculation model is established based on a VOF method and a powder feeding equation; integrating the development program with Fluent finite element software; carrying out multiple groups of single-channel single-layer melting deposition experiments, carrying out online real-time monitoring on the geometric characteristics and the temperature of the molten pool based on an online real-time monitoring system, preparing a deposition layer sample, extracting the geometric characteristics of the deposition layer, and verifying the accuracy of the numerical model through the geometric characteristics of the molten pool, the temperature of the molten pool and the geometric characteristics of the deposition layer sample; based on the process parameter and sedimentary layer geometric feature database, establishing a prediction model of the process parameters and the sedimentary layer geometric features by using a Gaussian process regression machine learning method; and performing feedback correction on the sedimentary layer geometric feature prediction model based on a small amount of experimental data. According to the method, the prediction model of the process parameters and the geometric features of the sedimentary layer can be quickly and accurately established, the process cost is low, the efficiency is high, and the prediction precision is controllable.

Description

technical field [0001] The invention belongs to the technical field of laser additive forming accuracy, and relates to a method for rapidly predicting the geometric characteristics of a laser melting deposition deposition layer. Background technique [0002] Laser metal deposition (LMD) uses a high-power laser as a heat source to melt the substrate, while raw materials are fed into the molten pool in the form of powder or wire. As the laser beam moves, the molten pool solidifies and completes layer-by-layer manufacturing. . As a result, the traditional multi-step manufacturing process of material forming is integrated into one-step manufacturing, which greatly improves the efficiency of workpiece manufacturing and material performance and saves costs. It is considered to be a major change in the manufacturing field and represents the latest advanced manufacturing technology and material preparation technology. Development direction, at present, it has shown broad applicatio...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the deficiencies of the prior art, the present invention provides a method for predicting the geometric characteristics of the laser melting deposition deposition layer, which can quickly and accurately establish the prediction model of the process parameters and the geometric characteristics of the deposition layer. The accuracy verification of the numerical model is realized by combining the length (L), width (b), temperature of the molten pool and the geometric characteristics of the sediment layer (height (H), width (w), penetration depth (h)) extracted from the prepared sample , establish a finite element and data-driven laser melting deposition deposition layer geometric feature prediction model based on a small amount of experimental data, and propose model feedback correction to achieve model accuracy control, while the prediction model has strong adaptability and is not affected by the substrate or feed material Size, attributes and other limitations, thus solving the problems of high process cost, low efficiency and uncontrollable prediction accuracy of the original laser melting deposition deposition layer geometric feature prediction method, and for the subsequent establishment of process planning and automation in the deposition manufacturing process. Lay the foundation for intelligent manufacturing

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