An efficient equivariant adaptive separation via independence algorithm for acoustical source separation and identification

作     者：CHENG Wei LU Jian Tao GAO Lin ZHANG Jie 

作者机构：State Key Laboratory for Manufacturing Systems EngmeermgXi'an Jiaotong UniversityXi'an 710049China Institute of Biomedical EngineeringKey Laboratory of Biomedical Information Engineering of Education MinistryXi'an Jiaotong UniversityXi'an 710049China 

出 版 物：《Science China(Technological Sciences)》 (中国科学（技术科学英文版）)

年 卷 期：2016年第59卷第12期

页      面：1825-1836页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 

基　　金：supported by the National Natural Science Foundation of China(Grant No.51305329) the China Postdoctoral Science Foundation(Grant No.2014T70911) the Doctoral Foundation of Education Ministry of China(Grant No.20130201120040) Basic Research Project of Natural Science in Shaanxi Province(Grant No.2015JQ5183) 

主　　题：equivariant adaptive separation via independence adaptive step size separation indicator forgetting factor acoustical source separation and identification 

摘      要：To balance the convergence rate and steadystate error of blind source separation(BSS) algorithms, an efficient equivariant adaptive separation via independence(Efficient EASI) algorithm is proposed based on separating indicator, which was derived from the convergence condition of EASI, and can be used to evaluate the separation degree of separated signals. Furthermore, a nonlinear monotone increasing function between suitable step sizes and separating indicator is constructed to adaptively adjust step sizes, and forgetting factor is employed to weaken effects of data at the initial stage. Numerical case studies and experimental studies on a test bed with shell structures are provided to validate the efficiency improvement of the proposed method. This study can benefit for vibration & acoustic monitoring and control, and machinery condition monitoring and fault diagnosis.