Detecting material type using low-energy sensing
US-11885661-B2 · Jan 30, 2024 · US
US9482647B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9482647-B2 |
| Application number | US-201314035227-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 24, 2013 |
| Priority date | Sep 24, 2013 |
| Publication date | Nov 1, 2016 |
| Grant date | Nov 1, 2016 |
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Embodiments are directed to obtaining an impact energy signal associated with each of a plurality of teeth of a gear over a revolution of a shaft associated with the gear, generating, by a computing device comprising a processor, a profile of the impact energy signal, and declaring a fault associated with an identified tooth included in the plurality of teeth based on an analysis of the profile.
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What is claimed is: 1. A method comprising: generating an estimated impact energy signal corresponding to each of a plurality of teeth of a gear over a revolution of a shaft associated with the gear tooth; obtaining an impact energy signal associated with each of the plurality of teeth; comparing the estimated impact energy signal with the obtained impact energy signal; generating, by a computing device comprising a processor, a profile of the impact energy signal; and declaring a fault associated with at least one tooth of the plurality of teeth, the fault being based on said comparing indicating a deviation between the estimated impact energy signal and the obtained impact energy signal in an amount greater than a threshold. 2. The method of claim 1 , further comprising: segmenting the impact energy signal into a number of segments equal to a number of teeth included in the plurality of teeth; and integrating each segment included in the number of segments to calculate the total energy released by each gear tooth impact. 3. The method of claim 1 , further comprising: separating the signal into a time synchronous average signal and a random signal; and processing the random signal to obtain an energy history associated with a meshing of the teeth. 4. The method of claim 1 , further comprising: computing slices of a spectral correlation density associated with the shaft at a fundamental frequency and multiples of the fundamental frequency to obtain a cyclic frequency domain representation; and converting the cyclic frequency domain representation to a rotation domain to produce a time-frequency representation for the shaft. 5. The method of claim 4 , further comprising: integrating a spectral frequency out of the time-frequency representation to obtain a time synchronous variance; and using the time synchronous variance to detect and isolate a fault associated with the shaft. 6. The method of claim 4 , further comprising: integrating an angular rotation out of the time-frequency representation to obtain a time synchronous spectrum; and using the time synchronous spectrum to monitor vibration of a gearbox. 7. The method of claim 4 , further comprising: integrating a spectral frequency out of the time-frequency representation in bands coinciding with identified spectral peaks equal to a number of substantially similar gear meshes; and using the integrated spectral frequency to obtain a unique time synchronous variance for each of the gear meshes. 8. An apparatus comprising: at least one processor; and memory having instructions stored thereon that, when executed by the at least one processor, cause the apparatus to: generate an estimated impact energy signal corresponding to each tooth of the plurality of teeth; obtain an impact energy signal associated with each of a plurality of teeth of a gear over a revolution of a shaft associated with the gear; compare the estimated impact energy signal with the obtained impact energy signal; generate a profile of the impact energy signal; and declare a fault associated with at least one of the plurality of teeth, the fault being based on the comparison indicating a deviation between the estimated impact energy signal and the obtained impact energy signal in an amount greater than a threshold. 9. The apparatus of claim 8 , wherein the instructions, when executed by the at least one processor, cause the apparatus to: segment the impact energy signal into a number of segments equal to a number of teeth included in the plurality of teeth, and integrate each segment included in the number of segments to calculate the total energy released by each gear tooth impact. 10. The apparatus of claim 8 , wherein the instructions, when executed by the at least one processor, cause the apparatus to: separate the impact energy signal into a time synchronous average signal and a random signal, and process the random signal to obtain an energy history associated with a meshing of the teeth. 11. The apparatus of claim 8 , wherein the instructions, when executed by the at least one processor, cause the apparatus to: compute slices of a spectral correlation density associated with the shaft at a fundamental frequency and multiples of the fundamental frequency to obtain a cyclic frequency domain representation, and convert the cyclic frequency domain representation to a rotation domain using an inverse Fourier transform to produce a time-frequency representation for the shaft. 12. The apparatus of claim 11 , wherein the instructions, when executed by the at least one processor, cause the apparatus to: integrate a spectral frequency out of the time-frequency representation to obtain a time synchronous variance, and use the time synchronous variance to detect and isolate a fault associated with the shaft. 13. The apparatus of claim 11 , wherein the instructions, when executed by the at least one processor, cause the apparatus to: integrate an angular rotation out of the time-frequency representation to obtain a time synchronous spectrum, and use the time synchronous spectrum to monitor vibration of a gearbox associated with the gear and the shaft. 14. The apparatus of claim 11 , wherein the instructions, when executed by the at least one processor, cause the apparatus to: integrate a spectral frequency out of the time-frequency representation in bands coinciding with identified spectral peaks equal to a number of gear meshes, and use the integrated spectral frequency to obtain a unique time synchronous variance for each of the gear meshes.
Wheels, Gears, Bearings · CPC title
by spectral analysis, e.g. Fourier analysis {or wavelet analysis (spectral signal processing per se G06F17/14)} · CPC title
using acoustic emission techniques {(echo of particles G01N29/046; measuring mechanical vibrations or acoustic waves in solids in general G01H1/00)} · CPC title
Acoustic or vibration analysis · CPC title
Gearings · CPC title
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