Features of Singular Value Decomposition and Its Application to the Vibration Monitoring of Turboprop Engine

  • Cheng Li
  • Chen Lishun
  • Liang Tao
  • Guo Li
  • Cheng Ming
  • Zeng Lin
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 463)


The singular value decomposition (SVD) can decompose an original signal into a series of component signals linearly. By means of analyzing deeply the fundamental principle and existing problems of Hankel matrix-based SVD, This paper reveals the three basic features of SVD, including linear decomposition, reconstruction component frequency domain disorder and band-pass filtering. Based on those features a new SVD method is put forward. Numerical simulation results show that the proposed method not only solve the frequency domain disorder problem of traditional SVD, and can achieve a given linear band-pass filter bandwidth, complete recovery of original signal amplitude, frequency and phase characteristics in any given frequency nearby. Other signal processing methods have no such advantages. The proposed method has been successfully applied to the vibration signal extraction of a certain type of turbofan engine, and the results show that the method has excellent in the feature extraction.


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


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Cheng Li
    • 1
    • 2
  • Chen Lishun
    • 1
  • Liang Tao
    • 1
  • Guo Li
    • 3
  • Cheng Ming
    • 1
    • 4
  • Zeng Lin
    • 1
  1. 1.Aeronautics and Astronautics Engineering CollegeAir Force Engineering UniversityXi’anChina
  2. 2.Advanced Aero Engine Collaborative Innovation CenterBeijingChina
  3. 3.The Chinese People’s Liberation Army 95606 TroopsGuiyangChina
  4. 4.The Chinese People’s Liberation Army 93066 TroopsShenyangChina

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