Resonance enhanced singular value decomposition and its application to the vibration monitoring of turboprop engine

PDF(2496 KB)

Journal of Vibration and Shock ›› 2018, Vol. 37 ›› Issue (22) : 206-213.

CHENG Li1,2,LIANG Tao1,GUO Li3,CHENG Ming1,4,ZENG Lin1

Author information +

History +

Abstract

Singular value decomposition (SVD) can linearly decompose a signal into a series of components.In this paper, the basic principles and problems of singular value decomposition (SVD) based on Hankel matrix were analyzed, and three basic properties of SVD were revealed, which are linear decomposition, frequency domain disorder of reconstructed components and band-pass filtering.Based on this, a resonance enhanced singular value decomposition (SVD) method was proposed.The numerical simulation results show that the proposed method not only solves the frequency-domain disorder problem of the traditional singular value decomposition (SVD) well, but also can realize the linear bandpass filtering with a given bandwidth near any given frequency.The amplitude, frequency and phase features of the original signal are extracted completely.This is the advantage the existing signal processing methods do not have.The proposed method was successfully applied to the characteristic frequency extraction of a turboprop engine vibration monitoring.The results show that the proposed method has excellent feature extraction effect.

Key words

Singular value decomposition / Band-pass filtering / Bandwidth / Vibration detection / Feature extraction

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

CHENG Li1,2,LIANG Tao1,GUO Li3,CHENG Ming1,4,ZENG Lin1. Resonance enhanced singular value decomposition and its application to the vibration monitoring of turboprop engine[J]. Journal of Vibration and Shock, 2018, 37(22): 206-213

References

[1]. 吕志民，张武军，徐金梧等. 基于奇异谱的降噪方法及其在故障诊断技术中的应用[J].机械工程学报，1999，35(3)：85-88.
LV Zhimin, ZHANG Wujun, XU Jinwu, et al. A noise reduction method based singular spectrum and its application in machine fault diagnosis [J]. Chinese Journal of Mechanical Engineering, 1999, 35(3)：85-88.
[2]. WALTON J, FAIRLEY N. Noise reduction in X-ray photoelectron spectromicroscopy by a singular value decomposition sorting procedure[J] Journal of Electron Spectroscopy and Related Phenomena, 2005, 148(1), 29-40.
[3]. 张波，李健军. 基于Hankel矩阵与奇异值分解(SVD)的滤波方法以及在飞机颤振试验数据预处理中的应用[J].振动与冲击，2009，28(2)：162-166.
ZHANG Bo, LI Jianjun. Denoising method based on hankel matrix and SVD and its application in flight flutter testing data preprocessing[J]. Journal of Vibration and Shock, 28(2):162-166.
[4]. 冯广斌，朱云博，孙华刚等. 一种有效奇异值选择方法在微弱信号特征提取中的应用 [J].机械科学与技术，2012，31（9）：1449-1453.
FENG Guangbin, ZHU Yunbo, SUN Huaguang, et al. Application of an effective singular value selection method in faint signal feature extraction[J]. Mechanical Science and Technology for Aerospace Engineering, 2012，31（9）：1449-1453.
[5]. 申永军，杨绍普，孔德顺. 基于奇异值分解的欠定盲信号分离新方法及应用[J].机械工程学报，2009，45(8)：64-70.
SHEN Yongjun, YANG Shaopu, KONG Deshun. New method of blind source separation in under-determined mixtures based on singular value decomposition and application[J]. Journal of Mechanical Engineering，2009,45(8)：64-70.
[6]. HASAN D，GHOLAMREZA A ,CAGRI O. Satellite image contrast enhancement using discrete wavelet transform and singular value decomposition[J]. IEEE Geoscience and Remote Sensing Letters，2010，7(2)：333-337.
[7]. 赵学智，叶邦彦，陈统坚. 基于小波-奇异值分解差分谱的弱故障特征提取方法[J].机械工程学报，2012，48(7)：37-47
ZHAO Xuezhi, YE Bangyan, CHEN Tongjian. Extraction method of faint fault feature based on wavelet-SVD difference spectrum[J]. Journal of Mechanical Engineering，2012，48(7)：37-47.
[8]. YANG Yang, WEI Kexiang, DONG Xingjian. Time-varying frequency modulated component extraction based on parameterized demodulated and singular value decomposition[J]. IEEE Transactions on Instrumentation and Measurement,2015,65(2),276-285.
[9]. 丁建明,王晗,林建辉. 基于EMD-Hankel-SVD的高速列车万向轴动不平衡检测[J]. 振动与冲击,2015,34(9):166-167.
DING Jianming, WANG Han, LIN Jianhui. Detection of dynamic imbalance due to cardan shaft in high-speed train based on EMD-Hankel-SVD method[J]. Journal of Vibration and Shock, 2015, 34(9): 166-167.
[10]. 丁建明, 林建辉，王晗等. 万向轴动不平衡检测的二代小波变化奇异值方法[J].机械工程学报，2014，50(12)：110-116.
DING Jianming, LIN Jianhui, WANG Han, et al. Detection of the dynamic unbalance with cardan shaft applying the second wavelet transform and singular value decomposition[J]. Journal of Mechanical Engineering，2014，50(12)：110-116.
[11]. 赵学智，叶邦彦，陈统坚. 奇异值差分谱理论及其在车床主轴箱故障诊断中的应用 [J].机械工程学报，2010，46（1）：100-108.
ZHAO Xuezhi, YE Bangyan, CHEN Tongjian. Difference spectrum theory of singular value and its application to the fault diagnosis of headstock of lathe[J] Journal of Mechanical Engineering，2010,46(1):100-108.
[12]. Xuezhi Zhao and Bangyan Ye. Similarity of signal processing effect between Hankel matrix-based SVD and wavelet transform and its mechanism analysis[J]. Mechanical Systems and Signal Processing. 2009,23:1062-1075.
[13]. Alonso FJ, Salgado DR. Analysis of the structure of vibration signals for tool wear detection[J]. Mechanical Systems and Signal Processing. 2008,22(3):735-748.
[14]. 赵学智，聂振国，叶邦彦等. 信号有效奇异值的数量规律及其在特征提取中的应用[J]. 振动工程学报，2016，29（3）：532-541.
ZHAO Xuezhi, NIE Zhenguo, CHEN Tongjian. Number law of effective singular values of signal and its application to feature extraction[J] Journal of Vibration Engineering，2016，29（3）：532-541.
[15]. 程礼，屈轲，陈卫等. 某型涡桨发动机减速器整机振动监控阀值研究[J].振动与冲击，2015，34(18)：136-141.
CHENG Li，QU Ke，CHEN Wei, et al. Vibration monitoring threshold of turboprop engine reducer[J]. Journal of Vibration and Shock, 2015,34(18):136-141.