Source Quantitative Identification by Reference-Based Cubic Blind Deconvolution Algorithm

作     者：Xin Luo Zhousuo Zhang Teng Gong Yongjie Li Xin Luo;Zhousuo Zhang;Teng Gong;Yongjie Li

作者机构：State Key Laboratory for Manufacturing Systems EngineeringXi’an Jiaotong UniversityXi’an 710049China 

出 版 物：《Chinese Journal of Mechanical Engineering》 (中国机械工程学报（英文版）)

年 卷 期：2023年第36卷第4期

页      面：180-195页

核心收录：

学科分类：08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 080502[工学-材料学] 

基　　金：Supported by National Natural Science Foundation of China(Grant No.51775410) Science Challenge Project of China(Grant No.TZ2018007) 

主　　题：Quantitative identification Reference-based cubic contrast function Semi-blind deconvolution Satellite micro-vibration Adaptive step size 

摘      要：The semi-blind deconvolution algorithm improves the separation accuracy by introducing reference ***,the separation performance depends largely on the construction of reference *** improve the robustness of the semi-blind deconvolution algorithm to the reference signals and the convergence speed,the reference-based cubic blind deconvolution algorithm is proposed in this *** proposed algorithm can be combined with the contribution evaluation to provide trustworthy guidance for suppressing satellite *** normalized reference-based cubic contrast function is proposed and the validity of the new contrast function is theoretically *** deriving the optimal step size of gradient iteration under the new contrast function,we propose an efficient adaptive step optimization ***,the contribution evaluation method based on vector projection is presented to implement the source contribution *** simulation analysis is carried out to validate the availability and superiority of this *** tests given by the simulated satellite experiment and satellite ground experiment also confirm the *** signals of control moment gyroscope and flywheel were extracted,respectively,and the contribution evaluation of vibration sources to the sensitive load area was *** research proposes a more accurate and robust algorithm for the source separation and provides an effective tool for the quantitative identification of the mechanical vibration sources.