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Research Papers

Doppler Shift Removal Based on Instantaneous Frequency Estimation for Wayside Fault Diagnosis of Train Bearings

[+] Author and Article Information
Ao Zhang, Fei Hu, Changqing Shen, Fang Liu

Department of Precision Machinery
and Precision Instrumentation,
University of Science and Technology of China, Hefei, Anhui 230026, China

Qingbo He

Department of Precision Machinery
and Precision Instrumentation,
University of Science and Technology of China, Hefei, Anhui 230026, China
e-mail: qbhe@ustc.edu.cn

Fanrang Kong

Department of Precision Machinery
and Precision Instrumentation,
University of Science and Technology of China, Hefei, Anhui 230026, China
e-mail: kongfr@ustc.edu.cn

1Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received September 30, 2012; final manuscript received December 10, 2013; published online February 5, 2014. Assoc. Editor: Patrick S. Keogh.

J. Vib. Acoust 136(2), 021019 (Feb 05, 2014) (10 pages) Paper No: VIB-12-1272; doi: 10.1115/1.4026431 History: Received September 30, 2012; Revised December 10, 2013

The phenomenon of Doppler shift in the acoustic signal acquired by a microphone amounted beside the railway leads to the difficulty for fault diagnosis of train bearings with a high moving speed. To enhance the condition monitoring performance of the bearings on a passing train using stationary microphones, the elimination of the Doppler shift should be implemented firstly to correct the severe frequency-domain distortion of the acoustic signal recorded in these conditions. In this paper, a Doppler shift removal method is proposed based on instantaneous frequency (IF) estimation (IFE) for analyzing acoustic signals from train bearings with a high speed. Specifically, the IFE based on short-time Fourier transform is firstly applied to attain the IF vector. According to the acoustic theory of Morse, the data fitting is then carried out to achieve the fitting IFs with which the resampling sequence can be established as the resampling vector in time domain. The resampled signal can be finally reconstructed to realize fault diagnosis of train bearings. To demonstrate the effectiveness of this method, two simulations and an experiment with practical acoustic signals of train bearings with a crack on the outer raceway and the inner raceway have been carried out, and the comparison results have been presented in this paper.

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Figures

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Fig. 1

Schematic diagram of the sound source with subsonic velocity

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Fig. 2

Flow chart of Doppler shift removal

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Fig. 3

Simulated signal and spectrum

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Fig. 4

Restored results of Doppler-shifted signal with a single characteristic frequency based on IFE-HT

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Fig. 5

Restored results of Doppler-shifted signal with a single characteristic frequency based on the proposed method

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Fig. 6

Simulated signal and spectrum

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Fig. 7

Restored results of Doppler-shifted signal with three characteristic frequencies based on IFE-HT

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Fig. 8

Restored results of Doppler-shifted signal with three characteristic frequencies based on the proposed method

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Fig. 9

Artificial cracks on the component of the bearing: (a) the outer race and (b) the inner race

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Fig. 10

Experimental setup for signal acquisition with Doppler shift: (a) test bench of the train bearing and (b) experiment scene

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Fig. 11

Train bearing signal with a defect on the outer race

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Fig. 16

Envelope spectral analysis result of the inner-race defective bearing signal

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Fig. 15

Estimation of the IF of the inner-race defective bearing signal: (a) STFT result and (b) IF

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Fig. 14

Train bearing signal with a defect on the inner race

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Fig. 13

Envelope spectral analysis results of the outer-race defective bearing signal

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Fig. 12

Estimation of the IF of the outer-race defective bearing signal: (a) STFT result and (b) IF

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