基于神经网络的3D打印批次排样研究

针对3D打印批次排样是一个建立在多约束条件下的复杂优化问题,本文提出一种基于Hopfield人工神经网络的3D打印批次排样方法。通过对3D打印批次排样目标的设定,建立了Hopfield人工神经网络的能量函数。通过神经网络优化计算,实现了将3D打印工件在三维空间的排布问题转化为二维图形的输出。该算法实用性强,提高了工件的加工效率。

Research on Layout of 3D Printing Based on Neural Network

The optimal layout of 3D printing is a complicated problem under the control of multi-circumstances.Aiming at solving this problem,this article proposed a new kind of algorithm based on the artificial neural network.The paper established energy function of neural network by setting the target of 3D printing layout.This paper optimized calculation by using the neural network,and the output of the 3D printed workpiece in the three-dimensional space is converted into the output of the two-dimensional graphics.The algorithm is practical and improves the processing efficiency of the workpiece.