Research on compound faults identification of aeroengine inter-shaft bearing based on CCF–Complexity–VMD

Abstract

Inter-shaft bearing is an important component of dual-rotor aeroengine and it is difficult to extract fault characteristics and identify a fault type. Therefore, the paper has proposed a method (CCF–Complexity–VMD–SVD) combining information fusion, Complexity parameter of Hjorth parameters, variational mode decomposition (VMD), and singular value decomposition (SVD). Firstly, to fully embody fault characteristic information, the method has established the cross-correlation function (CCF) of homologous acceleration information from the casing of one of the aeroengines (acceleration signals collected from the same section at the same moment in orthogonal directions) to blend homologous information, reinforce fault characteristic components, and lessen the influence of noise. Secondly, considering the great influence of signal complexity on the extraction of fault characteristics and the Complexity parameter of Hjorth parameters can express the complexity of signals better, the Complexity parameter of Hjorth parameters is placed into the fault characteristic extraction of inter-shaft bearing. The Complexity parameter is applied to optimize the number of layers and central frequency of VMD. Thirdly, signals are denoised through SVD to further lessen the influence of noise on characteristic extraction. Finally, frequency spectrum (FS) of signal denoised is used to make characteristic extraction and fault identification of compound faults of inter-shaft bearing. The result of comparative analysis with other methods has further illustrated the proposed method CCF–Complexity–VMD–SVD that can actualize the effective characteristic extraction of compound faults and precise identification in the early stage of fault based on vibration signals from casing of aeroengine. The performance of engineering appliance of the proposed method has been further verified through fault analysis of disassembly for the aeroengine.

Keywords

Information fusion Complexity parameter variational mode decomposition Hjorth parameters inter-shaft bearing compound faults

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References

Gao

Hou

Cheng

Study on nonlinear thermal behavior of intermediate bearing under dynamic load. Theor Appl Mech 2021; 53(1): 248–259.

Zhi

Youru

Jing

, et al. Fault diagnosis technology of intermediate bearing based on EMD fuzzy entropy and consultation decision fusion model. Aeroengine 2019; 45(5): 76–81.

Van Heacke

Yoon

. Low speed bearing fault diagnosis using acoustic emission sensors. Appl Acoist 2016; 105: 35–44.

Meng

Liao

. Fault diagnosis of rolling bearing using time delay correlation demodulation method. J Aeronaut 2004; 25(1): 41–44.

Laha

. Enhancement of fault diagnosis of rolling element bearing using maximum Kurtosis fast nonlocal means denoising. Measurement 2017; 100: 157–163.

Had

Sabri

. A two-stage blind deconvolution strategy for bearing fault vibration signals. Mech Syst Signal Process 2019; 106307.

McDonald

Zhao

Zuo

. Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection. Mech Syst Signal Process 2012; 33: 237–255.

Singh

Darpe

Singh

. Rolling element bearing fault diagnosis based on over-complete rational dilation wavelet transform and auto-correlation of analytic energy operator. Mech Syst Signal Process 2018; 100: 662–693.

Mishra

Samantaray

Chakraborty

. Rolling element bearing fault diagnosis under slow speed operation using wavelet de-noising. Measurement 2017; 103: 77–86.

10.

Kumar

Gandhi

Zhou

, et al. Fault diagnosis of rolling element bearing based on symmetric cross entropy of neutrosophic sets. Measurement 2020; 152: 107318.

11.

Bakdi

Kouadri

Bensmail

. Fault detection and diagnosis in a cement rotary kiln using PCA with EWMA-based adaptive threshold monitoring scheme. Control Eng Pract 2017; 66: 64–75.

12.

Basir

Yuan

. Engine fault diagnosis based on multi-sensor information fusion using Dempster–Shafer evidence theory. Inf Fusion 2007; 8: 379–386.

13.

Benkhedda

Patton

. Information fusion in fault diagnosis based on B-spline networks. IFAC Proc Volumes 1997; 30: 669–674.

14.

López

Zhong

. Stochastic resonance in an underdamped system with Fitzhug-Nagumo potential for weak signal detection. J Sound Vibration 2017; 411: 34–46.

15.

Dibaj

Hassannejad

Ettefagh

, et al. Incipient fault diagnosis of bearings based on parameter-optimized VMD and envelope spectrum weighted Kurtosis index with a new sensitivity assessment threshold. ISA Trans 2021; 114: 413–433.

16.

, et al. Rolling bearing fault diagnosis based on composite multiscale permutation entropy and reverse cognitive fruit fly optimization algorithm – extreme learning machine. Measurement 2021; 173: 108636.

17.

Mingfu

Zhenguo

Wei

. Vibration analysis of an aeroengine intermediate bearing outer ring fault. J Aerospace Power 2011; 26(11): 2422–2426.

18.

Guo

Zhiyuan

, et al. Vibration analysis of outer ring spalling fault of intermediate bearing based on whole machine. J Aerospace Power 2020; 35(3): 658–672.

19.

Jing

Jie

Shuguang

, et al. Fault diagnosis method of intermediate bearing based on adaptive bistable stochastic resonance. J Aerospace Power 2019; 34(10): 2237–2245.

20.

Chuanjin

Xiangwei

Wensi

, et al. Full vector envelope technique based on LMD and its application in TRT vibration fault diagnosis. Electr Power Autom Equip 2015; 35(2): 168–174.

21.

Heng

Guangxian

Jinhai

, et al. Research on rolling bearing state health monitoring and life prediction based on PCA and internet of things with multi-sensor. Measurement 2020; 157: 107657.

22.

Yuling

Zhaodi

. Formation drilling diagnosis based on wavelet cross correlation algorithm. Comput Eng Appl 2014; 50(4): 258–261.

23.

Dragomiretskiy

Zosso

. Variational mode decomposition. IEEE Trans Signal Process 2014; 62(3): 531–544.

24.

Kumar

Yuqing

Jiawei

. Optimization of VMD using kernel-based mutual information for the extraction of weak features to detect bearing defects. Measurement 2021; 168: 108402.

25.

Nassef

MGA

Hussein

Mokhiamar

. An adaptive variational mode decomposition based on sailfish optimization algorithm and Gini index for fault identification in rolling bearings. Measurement 2021; 173: 108514.

26.

Hongxian

Yan

Jingtao

, et al. Fault diagnosis of rolling bearing based on ICA envelope enhanced MEMD. J Aerospace Power 2021; 36(2): 405–412.

27.

Yong

Hong

Hui

. A new bearing fault diagnosis method based on genetic algorithm with VMD parameter optimization. J Vibration Shock 2021; 40(6): 184–189.

28.

Hjorth

. EEG analysis based on time domain properties. Electroencephalogra Clin Neurophysiol 1970; 29(3): 306–310.

29.

Cecchin

Ranta

Koessler

, et al. Seizure lateralization in scalp EEG using Hjorth parameters. Clin Neurophysiol 2010; 121(3): 290–300.

30.

Mouzé-Amady

Horwat

. Evaluation of Hjorth parameters in forearm surface EMG analysis during an occupational repetitive task. Electroencephalogr Clin Neurophysiol 1996; 101(2): 181–183.

31.

Grover

Turk

. Rolling element bearing fault diagnosis using empirical mode decomposition and Hjorth parameters. Procedia Comput Sci 2020; 167(11): 1484–1494.

32.

Sadat Safi

Mehdi Safi

. Early detection of Alzheimer’s disease from EEG signals using Hjorth parameters. Biomed Signal Process Control 2021; 65: 102338.

33.

Golafshan

Sanliturk

. SVD and Hankel matrix based de-noising approach for ball bearing fault detection and its assessment using artificial faults. Mech Syst Signal Process 2016; 71: 36–50.

34.

Hernandez-Vargas

Cabal-Yepez

Garcia-Perez

. Real-time SVD-based detection of multiple combined faults in induction motors. Comput Electr Eng 2014; 40: 2193–2203.

35.

Zhao

Guo

Gao

. Bearing fault feature extraction based on singular value decomposition and variational mode decomposition. J Vibration Shock 2016; 35(22): 183–188.

36.

Jing

Yuwei

Fengling

, et al. A study on inter-shaft bearing fault diagnosis method based on multi-scale quantum entropy. Acta Aeronautica et Astronautica Sinica 2022; 43(8): 75–86.

37.

Qiao

Zhong

. Analysis on vibration of intershaft bearing with inner and outer ring rotating in same and opposite direction. Bearing 2018; 1: 52–55.

Research on compound faults identification of aeroengine inter-shaft bearing based on CCF–Complexity–VMD–SVD

Abstract

Keywords

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