模糊神经网络算法对机械加工参数选择的优化分析

Optimization Analysis of Machining Parameters Selection Based on Fuzzy Neural Network Algorithm

机械加工过程中,参数的选择对加工质量的影响十分重要,但是存在参数频繁调整,加工参数设置不准确的问题,而且参数调整时间过长。由此,本文提出一种模糊神经网络算法,进行机械加工中的参数调整。首先,采用模糊理论对铣削量、每齿进给量、工序间余量、螺距、螺纹直径等参数进行判断,并按照调整标准进行划分,提高机械加工的准确性。然后,模糊神经算法对机械加工标准进行判断,并对判断结果进行验证。MATLAB仿真显示,在同一机械加工设备下,模糊神经网络算法对机械加工参数选择的准确性、选择时间均优于系统参数调节法。

In the process of machining,the selection of parameters has a very important impact on the processing quality,but there are problems such as frequent adjustment of parameters,inaccurate setting of processing parameters,and too long time for parameter adjustment.Therefore,this paper proposes a fuzzy neural network algorithm for parameter adjustment in machining.First of all,the fuzzy theory is used to judge the parameters such as milling amount,feed per tooth,inter-process allowance,thread pitch,thread diameter,and so on,and divide them according to the adjustment standard to improve the accuracy of machining.Then,the fuzzy neural algorithm judges the machining standard,and verifies the judgment results.MATLAB simulation shows that under the same machining equipment,the fuzzy neural network algorithm is superior to the system parameter adjustment method in the accuracy and time of machining parameter selection.