|Table of Contents|

Application of conjugate gradient algorithm in vibration signal processing(PDF)

《火箭推进》[ISSN:1672-9374/CN:CN 61-1436/V]

Issue:
2021年01期
Page:
97-100
Research Field:
测控与试验
Publishing date:

Info

Title:
Application of conjugate gradient algorithm in vibration signal processing
Author(s):
LI Qiqi ZHUANG Jian WANG Zhichao ZHANG Guoqing
(Beijing Institute of Aerospace Testing Technology, Beijing 100074,China)
Keywords:
liquid rocket engine test conjugate gradient algorithm vibration signal simulation analysis
PACS:
TP301.6
DOI:
-
Abstract:
In order to improve the accuracy of frequency-domain data processing of vibration signal in liquid rocket engine test, a spectral estimation algorithm based on conjugate gradient and AR model is proposed.The algorithm has low computational complexity and high estimated spectral resolution, which can overcome the problem that the traditional Fourier transform power spectrum estimation algorithm cannot effectively distinguish the spectral lines of similar frequency points when the signal-to-noise ratio is reduced.In addition, it also solves the inherent shortcoming of the traditional algorithm with serious side leakage.Based on the simulation analysis and test data verification of the algorithm under different signal-to-noise ratio conditions, the estimated spectrum of this algorithm still has the characteristics of high resolution under low signal-to-noise ratio conditions.

References:

[1] 郭霄峰.液体火箭发动机试验[M].北京: 中国宇航出版社,2005.
[2] 刘英元,陈海峰,耿直,等.液体火箭发动机振动故障特征信号提取方法[J].火箭推进,2019,45(1):77-82.
LIU Y Y,CHEN H F,GENG Z,et al.Extraction method of characteristic signal for vibration fault of liquid rocket engine[J].Journal of Rocket Propulsion,2019,45(1):77-82.
[3] 孙百红,田川.基于特征频段RMS值的发动机故障实时监测方法[J].火箭推进,2019,45(4):74-78.
SUN B H,TIAN C.The fault real—time monitoring method for engine based on RMS value of characteristic frequency band[J].Journal of Rocket Propulsion,2019,45(4):74-78.
[4] 张贤达.现代信号处理[M].3版.北京: 清华大学出版社,2015.
[5] 张鹏,廖飞.共轭梯度法研究与展望[J].牡丹江师范学院学报(自然科学版),2012(4):10-12.
[6] 胡广书.数字信号处理理论、算法与实现[M].北京: 清华大学出版社,2007.
[7] 刘松强.数字信号处理系统及其应用[M].北京: 清华大学出版社,1996.
[8] 沈福民.自适应信号处理[M].西安: 西安电子科技大学出版社,2001.
[9] LARSSON E G,STOICA P,LI J.Spectral estimation via adaptive filterbank methods: a unified analysis and a new algorithm[J].Signal Processing,2002,82(12):1991-2001.
[10] KAY S M.Modern spectral estimation: theory and application[Z].1988.
[11] HAYKIN S.自适应滤波器原理[M].郑宝玉,译.北京: 电子工业出版社,2003.
[12] STOICA P,LI H B,LI J.Amplitude estimation of sinusoidal signals: survey,new results,and an application[J].IEEE Transactions on Signal Processing,2000,48(2):338-352.
[13] KAY S M.Modern spectral estimation theory and application[Z].1988.
[14] KITSIOS K,SPANIAS A,WELFERT B.Adaptive modified covariance algorithms for spectral analysis[J].Signal Processing,2002,82(5):715-720.
[15] 胡昌华.基于MATLAB 7.x的系统分析与设计——小波分析[M].西安: 西安电子科技大学出版社,1999.
[16] 张志涌.精通MATLAB 6.5版[M].北京: 北京航空航天大学出版社,2003.
[17] 天工在线.MATLAB 2018从入门到精通:实战案例版[M].北京: 中国水利水电出版社,2018.
[18] 宋知用.MATLAB数字信号处理85个实用案例精讲:入门到进阶[M].北京: 北京航空航天大学出版社,2016.
[19] 李德葆,陆秋海.工程振动试验分析[M].北京: 清华大学出版社,2004.
[20] 王凤瑛,张丽丽.功率谱估计及其MATLAB仿真[J].微计算机信息,2006,22(31):287-289.

Memo

Memo:
-
Last Update: 2021-02-20