Method and system for predicting Young modulus of IN718 nickel-based alloy based on machine learning

The Young's modulus of IN718 nickel-based alloy is predicted through machine learning models, which solves the problems of long detection cycles and high costs in additive manufacturing, achieves fast and accurate material performance prediction, and improves production efficiency.

CN119181436APending Publication Date: 2024-12-24WUHAN INST OF TECH +1
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Patent Information

Application Number
CN202411090164.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-08-09
Publication Date
2024-12-24

AI Technical Summary

Technical Problem

During the additive manufacturing process, the Young's modulus detection cycle of IN718 nickel-based high-temperature alloy under different process parameters is long and costly, making it difficult to effectively monitor the differences in material performance.

Method used

Using a prediction method based on machine learning, a machine learning model is constructed by collecting processing parameters and material inherent attribute data, training to predict Young's modulus, and then predicting the Young's modulus of the alloy to be processed without the need to manufacture samples.

Benefits of technology

It significantly reduces manufacturing cycles and costs, improves production efficiency, provides effective insights for designing high-performance materials, and simplifies process parameter optimization process.

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Abstract

The invention relates to a method and a system for predicting Young modulus of an IN718 nickel-based alloy based on machine learning. The method comprises the following steps: acquiring processing parameter data of an IN718 nickel-based alloy sample, inherent attributes of a material and Young modulus data under the processing parameter data; constructing a machine learning model; training the machine learning model by using the processing parameter data, the raw material attribute data and the Young modulus data to obtain a Young modulus prediction model; determining preset raw material attribute data and preset processing parameters and data of the IN718 nickel-based alloy to be processed; inputting the preset raw material attribute data and the preset processing parameter data into the Young modulus prediction model so as to predict the Young modulus of the IN718 nickel-based alloy to be processed after being processed and formed under the preset processing parameter data; the manufacturing period is shortened, the manufacturing cost is reduced, and the production efficiency is improved.
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