带参考信号的频域盲解卷积算法及其在卫星微振动同频相关源定量辨识中的应用

doi:10.3901/JME.2025.10.215

机械工程学报 ›› 2025, Vol. 61 ›› Issue (10): 215-229.doi: 10.3901/JME.2025.10.215

• 仪器科学与技术 • 上一篇

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带参考信号的频域盲解卷积算法及其在卫星微振动同频相关源定量辨识中的应用

李永杰, 张周锁, 罗欣

西安交通大学机械制造系统工程国家重点实验室西安 710049

收稿日期:2024-05-23 修回日期:2025-01-22 发布日期:2025-07-12
作者简介:李永杰，男，1996年出生。主要研究方向为盲源分离算法。E-mail：lyj19961120@stu.xjtu.edu.cn;张周锁(通信作者)，男，1964年出生，博士，教授，博士研究生导师。主要研究方向为机电设备状态监测和智能诊断。E-mail：zzs@mail.xjtu.edu.cn
基金资助:
国家自然科学基金(51775410)和国防基础科研核科学挑战专题(TZ2018007)资助项目。

Frequency-domain Blind Deconvolution Algorithm with Reference Signals and Its Application in Quantitative Identification of Satellite Micro-vibration Dependent Sources with the Same Frequency

LI Yongjie, ZHANG Zhousuo, LUO Xin

State Key Laboratory for Manufacturing and System Engineering, Xi'an Jiaotong University, Xi'an 710049

Received:2024-05-23 Revised:2025-01-22 Published:2025-07-12

摘要/Abstract

摘要： 卫星微振动源定量辨识能够为微振动的抑制提供指导和依据，而由于振源信号中含有同频强相关性信号成分且信号传递路径复杂，给信号的分离和源贡献量的定量估计带来困难和挑战。为此，提出带参考信号的频域盲解卷积(Frequency-domain blind deconvolution with reference signals,FBDR)算法。首先，提出一种基于同频去除的相关源盲分离算法，利用去除同频成分后混合信号计算分离矩阵，并将其作用于原始混合信号得到估计信号，为含同频成分相关源信号的分离提供了解决思路。在此基础上，提出复值参考FastICA算法，将参考信号的相似度信息引入到优化迭代目标函数中，从而引入先验信息提高算法的分离性能。最后，通过仿真分析和卫星舱段结构激励试验验证了FBDR算法的有效性，结果表明，提出算法振源贡献量估计误差相较于对比算法明显降低。将FBDR算法应用于卫星微振动地面试验信号中，试验结果表明，贡献量估计误差小于3%，满足工程需求，可为卫星减振降噪和振源在轨控制提供参考依据。

Abstract: The quantitative identification of satellite micro-vibration sources can provide the guidance and basis for the suppression of micro-vibration. However, due to the strong dependence of the same frequency in vibration source signals and the complex signal transmission path, it is difficult and challenging to separate the signals and estimate the source contribution quantitatively. To this end, frequency-domain blind deconvolution algorithm with reference signals(FBDR) is proposed. Firstly, a dependent source blind separation algorithm based on the same frequency removal is proposed. The separation matrix is calculated by mixed signals which the same frequency components are removed, and it is applied to original mixed signals to obtain the estimated signals. It provides an idea for the separation of dependent source signals with same frequency components. On this basis, a complex-valued FastICA algorithm with reference is proposed. The similarity information of reference signals is introduced into the optimization iterative objective function, so as to introduce the priori information to improve the separation performance of the algorithm. Finally, the effectiveness of the FBDR algorithm is verified by simulation analysis and the satellite cabin structure excitation test. The results show that the estimation error of vibration source contribution of the proposed algorithm is significantly lower than that of the comparison algorithm. The FBDR algorithm is applied to signals obtained from the satellite micro-vibration ground test. Test results show that the error of contribution estimation is less than 3%, which meets the engineering needs. It can provide a reference basis for satellite vibration attenuation and noise reduction and on orbit vibration source control.

Key words: frequency-domain blind deconvolution, dependent source with the same frequency, reference signal, quantitative identification, satellite micro-vibration

中图分类号:

TH17

李永杰, 张周锁, 罗欣. 带参考信号的频域盲解卷积算法及其在卫星微振动同频相关源定量辨识中的应用[J]. 机械工程学报, 2025, 61(10): 215-229.

LI Yongjie, ZHANG Zhousuo, LUO Xin. Frequency-domain Blind Deconvolution Algorithm with Reference Signals and Its Application in Quantitative Identification of Satellite Micro-vibration Dependent Sources with the Same Frequency[J]. Journal of Mechanical Engineering, 2025, 61(10): 215-229.

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带参考信号的频域盲解卷积算法及其在卫星微振动同频相关源定量辨识中的应用

Frequency-domain Blind Deconvolution Algorithm with Reference Signals and Its Application in Quantitative Identification of Satellite Micro-vibration Dependent Sources with the Same Frequency

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