独立成分分析及其在纺纱锭子噪音测试中的应用  

Independent component analysis and its application in noise test of spinning spindle

作　　者：吕志军[1,2] 刘晓芝[1,2] 杨建国[2] 李蓓智[2] 王敏鹏[2] 

机构地区：[1]东华大学纺织面料技术教育部重点实验室,上海201620 [2]东华大学机械工程学院,上海201620

出　　处：《机械设计与制造》2012年第1期82-84,共3页Machinery Design & Manufacture

基　　金：上海市重点学科项目建设资助(B602);教育部纺织装备工程技术研究中心基金资助

摘　　要：纺纱锭子性能的优劣对生产效率和纱线质量具有决定性的影响。以纺纱锭子运转中的噪音信号为考察对象,对纺纱锭子运转过程进行分析。利用快速独立成分分析FastICA算法对工作状态中的锭子声压信号进行噪音源数据分离分析,得到工作状态下源信号的主频率。将工作状态下源信号的主频率与锭子不运转下的噪音主频率进行对比,38.88%分离主频率与锭子不运转下的噪音主频率一致,44.44%分离主频率与锭子不运转下的噪音主频率相近,最小误差为0.05%。实验与分析结果表明,FastICA算法用于噪音源信号主频率分离的有效性和正确性。The performance of spinning spindles decisively influences the production efficiency and yarn quality.It analyzes the noise during the running process of spinning spindles.Sound pressure signals which is collected during the experiment is analyzed and separated by rapid independent component analysis method and FastICA algorithm.Thus the source of the noise component during the running process of spinning spindles is separated and contrasted with the main frequency of the motor noise,in which 38.88% of the main frequency is identical,44.44% of the main frequency is close with the minimum error 0.05%.Experimental and analytical results show the effectiveness and correctness of FastICA algorithm used in sound pressure signals separation.

关 键 词：纺纱锭子 FastlCA算法 噪音 信号分离 

分 类 号：TH16[机械工程—机械制造及自动化]