Early detection of gear-tooth bending-fatigue damage by the Average-Log-Ratio ALR algorithm

William D. Mark; Matthew E. Wagner; Aaron C. Isaacson

doi:10.1016/j.ymssp.2022.108922

Early detection of gear-tooth bending-fatigue damage by the Average-Log-Ratio ALR algorithm

William D. Mark, Matthew E. Wagner, Aaron C. Isaacson

Applied Research Laboratory (ARL)

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

This work illustrates and explains an application of the Average-Log-Ratio, ALR, gear-damage detection algorithm for a case of gear-tooth bending fatigue. Gear-vibration rotational-harmonic spans between adjacent tooth-meshing harmonics are combined in ALR, thereby greatly reducing the masking effects resulting from the meshing action of the mating gear with the damaged gear. The first observation of unambiguous tooth fracture is identified. Moreover, 100,000 revolutions of the failing gear before this first observation of fracture, gear damage initiation, likely plastic deformation, is identified by ALR, thereby illustrating the potential for early warning of impending gear failure. Computation of kurtosis, FM4, using the same data, is provided for comparison of the detections provided by ALR and FM4, indicating earlier detection of damage initiation provided by ALR in comparison to that provided by FM4.

Original language	English (US)
Article number	108922
Journal	Mechanical Systems and Signal Processing
Volume	171
DOIs	https://doi.org/10.1016/j.ymssp.2022.108922
State	Published - May 15 2022

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Signal Processing
Civil and Structural Engineering
Aerospace Engineering
Mechanical Engineering
Computer Science Applications

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10.1016/j.ymssp.2022.108922

Cite this

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title = "Early detection of gear-tooth bending-fatigue damage by the Average-Log-Ratio ALR algorithm",

abstract = "This work illustrates and explains an application of the Average-Log-Ratio, ALR, gear-damage detection algorithm for a case of gear-tooth bending fatigue. Gear-vibration rotational-harmonic spans between adjacent tooth-meshing harmonics are combined in ALR, thereby greatly reducing the masking effects resulting from the meshing action of the mating gear with the damaged gear. The first observation of unambiguous tooth fracture is identified. Moreover, 100,000 revolutions of the failing gear before this first observation of fracture, gear damage initiation, likely plastic deformation, is identified by ALR, thereby illustrating the potential for early warning of impending gear failure. Computation of kurtosis, FM4, using the same data, is provided for comparison of the detections provided by ALR and FM4, indicating earlier detection of damage initiation provided by ALR in comparison to that provided by FM4.",

author = "Mark, {William D.} and Wagner, {Matthew E.} and Isaacson, {Aaron C.}",

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AU - Mark, William D.

AU - Wagner, Matthew E.

AU - Isaacson, Aaron C.

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N2 - This work illustrates and explains an application of the Average-Log-Ratio, ALR, gear-damage detection algorithm for a case of gear-tooth bending fatigue. Gear-vibration rotational-harmonic spans between adjacent tooth-meshing harmonics are combined in ALR, thereby greatly reducing the masking effects resulting from the meshing action of the mating gear with the damaged gear. The first observation of unambiguous tooth fracture is identified. Moreover, 100,000 revolutions of the failing gear before this first observation of fracture, gear damage initiation, likely plastic deformation, is identified by ALR, thereby illustrating the potential for early warning of impending gear failure. Computation of kurtosis, FM4, using the same data, is provided for comparison of the detections provided by ALR and FM4, indicating earlier detection of damage initiation provided by ALR in comparison to that provided by FM4.

AB - This work illustrates and explains an application of the Average-Log-Ratio, ALR, gear-damage detection algorithm for a case of gear-tooth bending fatigue. Gear-vibration rotational-harmonic spans between adjacent tooth-meshing harmonics are combined in ALR, thereby greatly reducing the masking effects resulting from the meshing action of the mating gear with the damaged gear. The first observation of unambiguous tooth fracture is identified. Moreover, 100,000 revolutions of the failing gear before this first observation of fracture, gear damage initiation, likely plastic deformation, is identified by ALR, thereby illustrating the potential for early warning of impending gear failure. Computation of kurtosis, FM4, using the same data, is provided for comparison of the detections provided by ALR and FM4, indicating earlier detection of damage initiation provided by ALR in comparison to that provided by FM4.

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Early detection of gear-tooth bending-fatigue damage by the Average-Log-Ratio ALR algorithm

Abstract

All Science Journal Classification (ASJC) codes

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