华侨大学学报（自然科学版）2018，Vol.39Issue(3)：337-342,6.DOI:10.11830/ISSN.1000-5013.201708005
采用PARAFAC的欠定盲分离中机械振源数估计方法
Mechanical Vibration Source Number Estimation of Underdetermined Blind Source Separation Using PARAFAC
摘要
Abstract
Considering the existing problem of underdetermined blind separation(UBSS)in the complex me-chanical system with unknown number of vibration sources,a new estimation algorithm of source number in the UBSS method based on parallel factor analysis(PARAFAC)and the core consistency diagnostic(COR-CONDIA)is proposed to improve the performance of UBSS method.The main idea of this algorithm is that the centralized sensor data are firstly divided into some non-overlapping data blocks.Then single time-delay co-variance matrices of each data block are calculated and stacked into a third-order tensor,which is constructed into the PARAFAC model.CORCONDIA is used to estimate the optimal number of components in PARAFAC model.Thus the obtained number of components is the number of vibration sources.The simulation results show that the proposed algorithm can accurately estimates the number of vibration sources from the underde-termined mixtures of non-stationary signal.It has been successfully applied to the test of multi-source mechan-ical vibration,and the experiment results further verify the effectiveness of the proposed algorithm.关键词
振源估计/平行因子分析/核一致诊断/欠定混合/盲源分离Key words
source number estimation/parallel factor analysis/core consistency diagnostic/underdetermined mixture/blind source separation分类
信息技术与安全科学引用本文复制引用
杨诚,李志农..采用PARAFAC的欠定盲分离中机械振源数估计方法[J].华侨大学学报（自然科学版）,2018,39(3):337-342,6.基金项目
国家自然科学基金资助项目(51675258,51261024,51075372) （51675258,51261024,51075372）
机械传动国家重点实验室开放基金资助项目(SKLMT-KFKT-201514) （SKLMT-KFKT-201514）
南昌航空大学研究生创新专项基金资助项目(YC2016050) （YC2016050）
