粒子群优化神经网络的电镀金刚石套钻使用寿命预测

电镀金刚石套钻广泛应用各种加工领域,而套钻使用寿命受到多种因素影响,具有一定的非线性变化特点,为了准确预测电镀金刚石套钻的使用寿命,提出了基于粒子群优化神经网络的电镀金刚石套钻使用寿命预测模型。对电镀金刚石套钻使用寿命预测现状进行分析,针对BP神经网络参数优化问题,采用粒子群优化算法确定最优参数,建立电镀金刚石套钻使用寿命的预测模型,通过仿真实验对其有效性和优越性进行分析。实验结果表明,模型可以准确刻画影响参数与电镀金刚石使用寿命之间的变化关系,获得比对比模型更高的预测精度,实际应用价值更高。

Service Life Prediction of Electroplated Diamond Drill Used in Particle Swarm Optimized Neural Network

Electroplated diamond drill is widely used in various kinds of machining fields,its service life is affected by various factors and has a certain nonlinear variation characteristic.In order to accurately predict the service life of the diamond drill,a novel prediction model of the diamond drill service life was presented based on particle swarm optimized neural network,and the prediction status quo of the service life of electroplated diamond drill was analyzed.For the issue of BP neural network parameters optimization,the optimal parameters were defined by using particle swarm optimization algorithm,the prediction model of electroplated diamond drill service life had been established and its effectiveness and superiorities were analyzed through simulation experiments.Results showed that the proposed model could accurately describe the changing relationship between the parameters and the service life of electroplating diamond drill,obtain higher prediction accuracy than that of contrast model,and possess higher practical application value.