摘要
提出和实现了一种基于切削力状态参量判别刀具故障的方法。利用LabVIEW软件平台采集和分析切削力信号。调用MatLAB中的小波包工具将信号分解,并计算各频段的能量谱,输入BP神经网络进行训练。将经过训练后的BP网络用于对刀具故障进行诊断,并给出了应用实例。
An approach to diagnosing the malfunction of cutting tool based on cutting force is presented. The cutting force signal is transformed by the wavelet packet tool of MatLAB and decomposed into the energy in several frequency bands. The BP neural network trained by the energy vectors is used to diagnosis cutting malfunction. The example of diagnosis is introduced.
出处
《工具技术》
北大核心
2006年第10期45-47,共3页
Tool Engineering
基金
江西省材料科学与工程研究中心科研基金资助项目
关键词
故障诊断
金属切削
小波包分析
BP神经网络
malfunction diagnosis, metal cutting, wavelet packet transformation, BP neural network
