JOURNAL ARTICLE

Gear Fault Detection Based on Teager-Huang Transform

Hui LiHaiqi ZhengLiwei Tang

Year: 2010 Journal:   International Journal of Rotating Machinery Vol: 2010 Pages: 1-9   Publisher: Hindawi Publishing Corporation

Abstract

Gear fault detection based on Empirical Mode Decomposition (EMD) and Teager Kaiser Energy Operator (TKEO) technique is presented. This novel method is named as Teager-Huang transform (THT). EMD can adaptively decompose the vibration signal into a series of zero mean Intrinsic Mode Functions (IMFs). TKEO can track the instantaneous amplitude and instantaneous frequency of the Intrinsic Mode Functions at any instant. The experimental results provide effective evidence that Teager-Huang transform has better resolution than that of Hilbert-Huang transform. The Teager-Huang transform can effectively diagnose the fault of the gear, thus providing a viable processing tool for gearbox defect detection and diagnosis.

Keywords:
Hilbert–Huang transform Instantaneous phase Energy operator Hilbert transform Computer science S transform Fault (geology) Signal processing Artificial intelligence Pattern recognition (psychology) SIGNAL (programming language) Mode (computer interface) Fault detection and isolation Time–frequency analysis Vibration Energy (signal processing) Speech recognition Algorithm Mathematics Spectral density Wavelet transform Acoustics Computer vision Digital signal processing Statistics Physics Telecommunications Discrete wavelet transform

Metrics

28
Cited By
5.67
FWCI (Field Weighted Citation Impact)
34
Refs
0.95
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Machine Fault Diagnosis Techniques
Physical Sciences →  Engineering →  Control and Systems Engineering
Gear and Bearing Dynamics Analysis
Physical Sciences →  Engineering →  Mechanical Engineering
Structural Health Monitoring Techniques
Physical Sciences →  Engineering →  Civil and Structural Engineering

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