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Title: A novel vibration-based fault diagnostic algorithm for gearboxes under speed fluctuations without rotational speed measurement

The localized failures of gears introduce cyclic-transient impulses in the measured gearbox vibration signals. These impulses are usually identified from the sidebands around gear-mesh harmonics through the spectral analysis of cyclo-stationary signals. However, in practice, several high-powered applications of gearboxes like wind turbines are intrinsically characterized by nonstationary processes that blur the measured vibration spectra of a gearbox and deteriorate the efficacy of spectral diagnostic methods. Although order-tracking techniques have been proposed to improve the performance of spectral diagnosis for nonstationary signals measured in such applications, the required hardware for the measurement of rotational speed of these machines is often unavailable in industrial settings. Moreover, existing tacho-less order-tracking approaches are usually limited by the high time-frequency resolution requirement, which is a prerequisite for the precise estimation of the instantaneous frequency. To address such issues, a novel fault-signature enhancement algorithm is proposed that can alleviate the spectral smearing without the need of rotational speed measurement. This proposed tacho-less diagnostic technique resamples the measured acceleration signal of the gearbox based on the optimal warping path evaluated from the fast dynamic time-warping algorithm, which aligns a filtered shaft rotational harmonic signal with respect to a reference signal assuming a constant shaft rotational speedmore » estimated from the approximation of operational speed. The effectiveness of this method is validated using both simulated signals from a fixed-axis gear pair under nonstationary conditions and experimental measurements from a 750-kW planetary wind turbine gearbox on a dynamometer test rig. Lastly, the results demonstrate that the proposed algorithm can identify fault information from typical gearbox vibration measurements carried out in a resource-constrained industrial environment.« less
Authors:
 [1] ;  [1] ;  [2] ;  [3] ;  [1] ;  [1]
  1. Wuhan Univ. of Technology (China)
  2. Univ. of Auckland (New Zealand)
  3. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Report Number(s):
NREL/JA-5000-67137
Journal ID: ISSN 0888-3270
Grant/Contract Number:
AC36-08GO28308
Type:
Accepted Manuscript
Journal Name:
Mechanical Systems and Signal Processing
Additional Journal Information:
Journal Volume: 94; Journal Issue: C; Journal ID: ISSN 0888-3270
Publisher:
Elsevier
Research Org:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; gear fault diagnosis; tacho-less algorithm; speed fluctuations; vibration; gearbox
OSTI Identifier:
1349216
Alternate Identifier(s):
OSTI ID: 1414635

Hong, Liu, Qu, Yongzhi, Dhupia, Jaspreet Singh, Sheng, Shuangwen, Tan, Yuegang, and Zhou, Zude. A novel vibration-based fault diagnostic algorithm for gearboxes under speed fluctuations without rotational speed measurement. United States: N. p., Web. doi:10.1016/j.ymssp.2017.02.024.
Hong, Liu, Qu, Yongzhi, Dhupia, Jaspreet Singh, Sheng, Shuangwen, Tan, Yuegang, & Zhou, Zude. A novel vibration-based fault diagnostic algorithm for gearboxes under speed fluctuations without rotational speed measurement. United States. doi:10.1016/j.ymssp.2017.02.024.
Hong, Liu, Qu, Yongzhi, Dhupia, Jaspreet Singh, Sheng, Shuangwen, Tan, Yuegang, and Zhou, Zude. 2017. "A novel vibration-based fault diagnostic algorithm for gearboxes under speed fluctuations without rotational speed measurement". United States. doi:10.1016/j.ymssp.2017.02.024. https://www.osti.gov/servlets/purl/1349216.
@article{osti_1349216,
title = {A novel vibration-based fault diagnostic algorithm for gearboxes under speed fluctuations without rotational speed measurement},
author = {Hong, Liu and Qu, Yongzhi and Dhupia, Jaspreet Singh and Sheng, Shuangwen and Tan, Yuegang and Zhou, Zude},
abstractNote = {The localized failures of gears introduce cyclic-transient impulses in the measured gearbox vibration signals. These impulses are usually identified from the sidebands around gear-mesh harmonics through the spectral analysis of cyclo-stationary signals. However, in practice, several high-powered applications of gearboxes like wind turbines are intrinsically characterized by nonstationary processes that blur the measured vibration spectra of a gearbox and deteriorate the efficacy of spectral diagnostic methods. Although order-tracking techniques have been proposed to improve the performance of spectral diagnosis for nonstationary signals measured in such applications, the required hardware for the measurement of rotational speed of these machines is often unavailable in industrial settings. Moreover, existing tacho-less order-tracking approaches are usually limited by the high time-frequency resolution requirement, which is a prerequisite for the precise estimation of the instantaneous frequency. To address such issues, a novel fault-signature enhancement algorithm is proposed that can alleviate the spectral smearing without the need of rotational speed measurement. This proposed tacho-less diagnostic technique resamples the measured acceleration signal of the gearbox based on the optimal warping path evaluated from the fast dynamic time-warping algorithm, which aligns a filtered shaft rotational harmonic signal with respect to a reference signal assuming a constant shaft rotational speed estimated from the approximation of operational speed. The effectiveness of this method is validated using both simulated signals from a fixed-axis gear pair under nonstationary conditions and experimental measurements from a 750-kW planetary wind turbine gearbox on a dynamometer test rig. Lastly, the results demonstrate that the proposed algorithm can identify fault information from typical gearbox vibration measurements carried out in a resource-constrained industrial environment.},
doi = {10.1016/j.ymssp.2017.02.024},
journal = {Mechanical Systems and Signal Processing},
number = C,
volume = 94,
place = {United States},
year = {2017},
month = {2}
}