摘要
使用普瑞美RING EXPERT装置采集环锭纺纱机钢丝圈振动信息,结合联合时域频域方法提取钢丝圈振动信息特征向量,在运用交叉验证法和网格搜索法进行参数优化的基础上,利用支持向量机智能算法对钢丝圈出现的不平衡、碰磨、裂纹等故障进行诊断分析.仿真结果表明,诊断耗时短,正确率达到88.0%,基本解决了中小型纺织企业环锭纺纱机钢丝圈故障诊断问题.
This paper firstly adopts the Bremen RING EXPERT device to collect the vibration information, and combines with the time-frequency domain method to extract the characteristic vector of the vibration information of steel wire ring. Then, it use the support vector machine（SVM） intelligent algorithm for the fault diagnosis and analysis based on the parameters optimization by the cross validation method and the grid search method, when the steel wire ring appears the unbalance, rubbing and cracking state. The simulation results show that the diagnosis time is short and the correct rate is 88. 0%, basic solves the small and medium-sized textile enterprises ring spinning frame steel wire circle fault diagnosis problem.
出处
《杭州电子科技大学学报（自然科学版）》
2017年第4期47-52,共6页
Journal of Hangzhou Dianzi University：Natural Sciences
基金
浙江省公益技术研究资助项目(2015C31084)
关键词
环锭纺纱机钢丝圈
信息采集
特征提取
支持向量机算法
故障诊断
ring spindle spinning machine
information acquisition
feature extraction
support vector machine algorithm
fault diagnosis
