Drill bit repair type prediction using machine learning
US-2020149354-A1 · May 14, 2020 · US
US11566988B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11566988-B2 |
| Application number | US-202117187700-A |
| Country | US |
| Kind code | B2 |
| Filing date | Feb 26, 2021 |
| Priority date | Feb 26, 2021 |
| Publication date | Jan 31, 2023 |
| Grant date | Jan 31, 2023 |
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A testing device that includes a wear testing device, a sensor array, and a controller. The wear testing device includes a sample rotation element configured to hold and to rotate a sample; and a cutting element holder configured to hold a cutting element and to engage the cutting element with the sample as the sample rotates. The sensor array includes an acoustic emissions (AE) sensor configured to measure an acoustic signal generated during engagement between the cutting element and the sample; and a load sensor. The controller is communicably connected to the sensor array and configured to determine a toughness and a wear resistance of the cutting element using the acoustic signal, the applied load, and a wear state of the cutting element.
Opening claim text (preview).
What is claimed: 1. A testing device, comprising: a wear testing device comprising: a sample rotation element configured to hold and to rotate a sample; and a cutting element holder configured to hold a cutting element and to engage the cutting element with the sample as the sample rotates; a sensor array comprising: an acoustic emissions (AE) sensor configured to measure an acoustic signal generated during engagement between the cutting element and the sample; and a load sensor configured to measure an applied load by the cutting element on the sample during the engagement; and a controller communicably connected to the sensor array and configured to determine a toughness and a wear resistance of the cutting element using the acoustic signal, the applied load, and a wear state of the cutting element. 2. The testing device of claim 1 , wherein the sensor array further comprises a wear sensor communicably connected to the controller and configured to measure the wear state of the cutting element during the engagement. 3. The testing device of claim 2 , wherein the wear sensor is an image capture device. 4. The testing device of claim 1 , wherein the sensor array further comprises a vibration sensor communicably connected to the controller and configured to measure vibrations of the cutting element during the engagement. 5. The testing device of claim 1 , wherein the sensor array is located proximate to the cutting element. 6. The testing device of claim 1 , wherein the acoustic signal includes AE generated by macroscale and microscale changes of the cutting element. 7. The testing device of claim 1 , wherein the wear testing device is configured to perform a vertical turret lathe test or a horizontal mill wear test. 8. The testing device of claim 1 , wherein the sensor array further comprises a temperature sensor communicably connected to the controller and configured to measure a temperature of the cutting element during the engagement. 9. A method for characterizing a cutting element, the method comprising: engaging the cutting element with a sample while a sample rotation element rotates the sample, generating a wear state of the cutting element; measuring, during the engaging, an acoustic signal using an AE sensor and an applied load by the cutting element on the sample using a load sensor; and determining a toughness and a wear resistance of the cutting element using the acoustic signal, the applied load, and the wear state of the cutting element. 10. The method of claim 9 , further comprising: mounting the cutting element to a cutting element holder of a wear testing device; and mounting a sample to a sample rotation element of the wear testing device. 11. The method of claim 9 , wherein the engaging proceeds for a predetermined length. 12. The method of claim 9 , wherein the toughness and the wear resistance of the cutting element are determined in real-time during the engaging. 13. The method of claim 9 , further comprising: measuring, during the engaging, the wear state of the cutting element using a wear sensor. 14. The method of claim 9 , further comprising: measuring, after the engaging, the wear state of the cutting element by assessing the cutting element. 15. The method of claim 9 , further comprising: processing the acoustic signal to remove acoustic features originating outside of the cutting element. 16. The method of claim 15 , wherein the acoustic features originating outside of the cutting element comprise background noise and acoustic features originating in the sample. 17. The method of claim 15 , further comprising: measuring, during the engaging, vibrations of the cutting element using a vibration sensor, wherein the processing the acoustic signal further uses the vibrations. 18. The method of claim 9 , wherein determining the toughness further comprises: determining an area under a curve in a plot of the acoustic signal vs. time. 19. The method of claim 9 , further comprising: measuring, during the engaging, a temperature of the cutting element by a temperature sensor, wherein determining the toughness and the wear resistance further comprises monitoring for a phase transformation of the cutting element using the temperature.
Investigating machinability by cutting tools; Investigating the cutting ability of tools · CPC title
Investigating resistance to wear or abrasion · CPC title
by measuring noise · CPC title
one or more transducer arrays · CPC title
Structural degradation, e.g. fatigue of composites, ageing of oils · CPC title
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