Gear condition indicators are one of the most important gear transmission fault detection and diagnosis techniques. Various kinds of condition indicators for different kinds of gear fault types (e.g. tooth crack, wear, eccentricity, etc.) have been proposed in the past several decades. However, their relative effectiveness, especially in light of some newly proposed indicators, on gear fault detection or diagnosis has not been fully evaluated. Performance assessment of gear fault condition indicators is not only helpful in designing new advanced indicators but also important for the development of a reliable Condition Based Maintenance (CBM) system. The objective of this paper is to verify and compare the relative performances of twenty-one selected gear condition indicators as applied to a progressive gear tooth crack under constant load and speed working conditions. The main goals are to identify which indicators are sensitive to the fault or have the capability to detect the initial tooth crack and therefore to recommend the most effective gear condition indicators. Dynamic simulations were used to generate the vibration signals which reflect the real underlying vibration behavior of the transmission system. Based on the simulated results, the performances of the selected indicators under noise-free as well as various signal to noise ratio conditions were evaluated and compared. Results indicate that many of the selected indicators are effective for the detection of the progressive tooth crack only under noise-free conditions, and the indicators that only consider time or frequency domain features, such as RMS, Kurtosis, energy ratio, sideband index, are generally less able to detect a tooth crack at an early stage compared to the methods based on reconstructed signals, such as the NA4, FM4, M6A, M8A.
Skip Nav Destination
ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
August 6–9, 2017
Cleveland, Ohio, USA
Conference Sponsors:
- Design Engineering Division
- Computers and Information in Engineering Division
ISBN:
978-0-7918-5822-6
PROCEEDINGS PAPER
Performance Assessment of Gear Condition Indicators in Detecting Progressive Gear Tooth Crack Available to Purchase
Yang Luo,
Yang Luo
University of Ottawa, Ottawa, ON, Canada
Search for other works by this author on:
Natalie Baddour,
Natalie Baddour
University of Ottawa, Ottawa, ON, Canada
Search for other works by this author on:
Ming Liang
Ming Liang
University of Ottawa, Ottawa, ON, Canada
Search for other works by this author on:
Yang Luo
University of Ottawa, Ottawa, ON, Canada
Natalie Baddour
University of Ottawa, Ottawa, ON, Canada
Ming Liang
University of Ottawa, Ottawa, ON, Canada
Paper No:
DETC2017-67460, V008T12A010; 11 pages
Published Online:
November 3, 2017
Citation
Luo, Y, Baddour, N, & Liang, M. "Performance Assessment of Gear Condition Indicators in Detecting Progressive Gear Tooth Crack." Proceedings of the ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 8: 29th Conference on Mechanical Vibration and Noise. Cleveland, Ohio, USA. August 6–9, 2017. V008T12A010. ASME. https://doi.org/10.1115/DETC2017-67460
Download citation file:
43
Views
Related Proceedings Papers
Related Articles
The Influence of Gear Design Parameters on Gear Tooth Damage Detection Sensitivity
J. Mech. Des (December,2002)
A Step Toward Fault Type and Severity Characterization in Spur Gears
J. Mech. Des (August,2019)
Related Chapters
Data Analysis of Optimal Square of Pixel Pair Modification Based Brute Force
International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)
Constrained Spectrum Denoising Based on Sparse Representation
International Conference on Computer and Computer Intelligence (ICCCI 2011)
Backlash
Design and Application of the Worm Gear