现代制造工程Issue(3)：106-111,76,7.DOI:10.16731/j.cnki.1671-3133.2017.03.018
基于灰色神经网络建模的刀具可靠性评估
Tool reliability evaluation based on grey neural network modeling
摘要
Abstract
A reliability evaluation method based on grey neural network modeling is put forward to tool reliability evaluation of missing data in failure sample.The vibration signal and tool wear is obtained by online experiment.Wavelet packet decomposition,time domain statistics and correlation analysis are used to extract significant features.The obtained feature is wavelet energy entropy,seventh band and ninth band wavelet energy,seventh band mean,RMS amplitude,RMS value,standard deviation.Building grey neural network mode.Take 7 significant features as input,take tool wear as output to train network model.Enter the random sample data,to obtain the tool wear data.The pseudo failure life is determined by the preset failure threshold.At last,to establish and complete the Weibull distribution model of reliability assessment.Tool simulation experiment results show that grey neural network model has higher prediction accuracy compared with the grey forecasting model.关键词
可靠性评估/灰色神经网络/威布尔分布/特征量/磨损量/预测Key words
reliability evaluation/grey neural network/the Weibull distribution/features/tool wear/prediction分类
机械制造引用本文复制引用
陈保家,朱晨希,严文超,吴志平,陶立涛..基于灰色神经网络建模的刀具可靠性评估[J].现代制造工程,2017,(3):106-111,76,7.基金项目
国家自然科学基金项目(51205230,51405264) （51205230,51405264）
湖北省自然科学基金项目(2015CFB445) （2015CFB445）
湖北省重点实验室开放基金项目(2016KSD15) （2016KSD15）
三峡大学研究生科研创新基金项目(2015CX042) （2015CX042）
