摘要
针对传统电火花加工仿真模型预测精度比较低的问题,结合电火花加工影响内在规律,提出一种基于神经网络算法的工艺参数优化模型。首先对BP神经网络算法的结构和原理进行了分析,然后结合电火花加工的研究文献,设计神经模型的输入和输出参数,并根据上述的参数对模型进行构建,最后以实际的材料加工为对象,通过MATLAB软件对上述的模型进行验证。结果表明:神经网络算法具有良好的预测效果,对提高电火花切割加工精度具有一定的价值。
Aiming at the low prediction accuracy of the traditional EDM simulation model, combined with the inherent law of EDM, an optimization model of process parameters based on neural network algorithm is proposed. Firstly, the structure and principle of BP neural network algorithm is analyzed, and then combined with the research of EDM, designed the input and output parameters of the neural network model,and according to the above parameters, established the model. Finally, processing the actual material as the object, verified the model through the MATLAB software. The results indicate that the neural network algorithm has good predictive value, has a certain value to improve the machining precision of WEDM.
出处
《小型内燃机与车辆技术》
2018年第1期37-40,共4页
Small Internal Combustion Engine and Vehicle Technique
