Research on a Signal Separation Method Based on Vold-Kalman Filter of Improved Adaptive Instantaneous Frequency Estimation

The fault vibration signal of rotating machinery system under strong background noise has the characteristics of non-stationary, non-Gaussian and complex components. In view of these characteristics, an improved method of signal separation based on Vold-Kalman filter (VKF) of adaptive instantaneous...

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Main Authors: Yanfeng Li, Zhennan Han, Zhijian Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9119429/
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author Yanfeng Li
Zhennan Han
Zhijian Wang
author_facet Yanfeng Li
Zhennan Han
Zhijian Wang
author_sort Yanfeng Li
collection DOAJ
description The fault vibration signal of rotating machinery system under strong background noise has the characteristics of non-stationary, non-Gaussian and complex components. In view of these characteristics, an improved method of signal separation based on Vold-Kalman filter (VKF) of adaptive instantaneous frequency estimation is proposed. First, a method for adaptive multiridge extraction of peaks detection based on synchro-squeezing wavelet transform (SWT) is proposed as the high-precision adaptive instantaneous frequency (IF) estimation method. The high precision IF estimation is used as the instantaneous frequency parameter of VKF, so that the complex multi-component non-stationary signal can be separated directly in the time domain and transformed into a signal combination composed of multiple stationary single-component signals and signal residues. Secondly, an improved method is proposed combining the adaptive IF estimation method with order tracking analysis and diagonal slice of bispectrum. In the improved method, the corresponding IF estimation of each component signal is taken as the reference frequency of its order tracking and the order spectrum analysis of each component signal is carried out respectively. Meanwhile, the signal residual is analyzed by diagonal slice of bispectrum, so as to suppress Gaussian noise and effectively separate and extract fault features in the vibration signal. Finally, the method is verified on simulation data and experimental data under different conditions. The results show that the improved method has higher extraction accuracy than other traditional methods. It has the superiority and the great potential for practical applications.
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spelling doaj.art-e7048218d68e4bd4aeebe15048e9420e2022-12-21T18:13:47ZengIEEEIEEE Access2169-35362020-01-01811217011218910.1109/ACCESS.2020.30029999119429Research on a Signal Separation Method Based on Vold-Kalman Filter of Improved Adaptive Instantaneous Frequency EstimationYanfeng Li0https://orcid.org/0000-0002-5884-5060Zhennan Han1Zhijian Wang2https://orcid.org/0000-0002-6794-2065College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan, ChinaCollege of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan, ChinaSchool of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, ChinaThe fault vibration signal of rotating machinery system under strong background noise has the characteristics of non-stationary, non-Gaussian and complex components. In view of these characteristics, an improved method of signal separation based on Vold-Kalman filter (VKF) of adaptive instantaneous frequency estimation is proposed. First, a method for adaptive multiridge extraction of peaks detection based on synchro-squeezing wavelet transform (SWT) is proposed as the high-precision adaptive instantaneous frequency (IF) estimation method. The high precision IF estimation is used as the instantaneous frequency parameter of VKF, so that the complex multi-component non-stationary signal can be separated directly in the time domain and transformed into a signal combination composed of multiple stationary single-component signals and signal residues. Secondly, an improved method is proposed combining the adaptive IF estimation method with order tracking analysis and diagonal slice of bispectrum. In the improved method, the corresponding IF estimation of each component signal is taken as the reference frequency of its order tracking and the order spectrum analysis of each component signal is carried out respectively. Meanwhile, the signal residual is analyzed by diagonal slice of bispectrum, so as to suppress Gaussian noise and effectively separate and extract fault features in the vibration signal. Finally, the method is verified on simulation data and experimental data under different conditions. The results show that the improved method has higher extraction accuracy than other traditional methods. It has the superiority and the great potential for practical applications.https://ieeexplore.ieee.org/document/9119429/Adaptive instantaneous frequency estimationdiagonal slice of bispectrumorder trackingsignal separationVold-Kalman filtering
spellingShingle Yanfeng Li
Zhennan Han
Zhijian Wang
Research on a Signal Separation Method Based on Vold-Kalman Filter of Improved Adaptive Instantaneous Frequency Estimation
IEEE Access
Adaptive instantaneous frequency estimation
diagonal slice of bispectrum
order tracking
signal separation
Vold-Kalman filtering
title Research on a Signal Separation Method Based on Vold-Kalman Filter of Improved Adaptive Instantaneous Frequency Estimation
title_full Research on a Signal Separation Method Based on Vold-Kalman Filter of Improved Adaptive Instantaneous Frequency Estimation
title_fullStr Research on a Signal Separation Method Based on Vold-Kalman Filter of Improved Adaptive Instantaneous Frequency Estimation
title_full_unstemmed Research on a Signal Separation Method Based on Vold-Kalman Filter of Improved Adaptive Instantaneous Frequency Estimation
title_short Research on a Signal Separation Method Based on Vold-Kalman Filter of Improved Adaptive Instantaneous Frequency Estimation
title_sort research on a signal separation method based on vold kalman filter of improved adaptive instantaneous frequency estimation
topic Adaptive instantaneous frequency estimation
diagonal slice of bispectrum
order tracking
signal separation
Vold-Kalman filtering
url https://ieeexplore.ieee.org/document/9119429/
work_keys_str_mv AT yanfengli researchonasignalseparationmethodbasedonvoldkalmanfilterofimprovedadaptiveinstantaneousfrequencyestimation
AT zhennanhan researchonasignalseparationmethodbasedonvoldkalmanfilterofimprovedadaptiveinstantaneousfrequencyestimation
AT zhijianwang researchonasignalseparationmethodbasedonvoldkalmanfilterofimprovedadaptiveinstantaneousfrequencyestimation