IP Library › Granted Patent US 11,407,079
Granted Patent B2
US 11,407,079 · App. 16/816,533 · Granted Aug 9, 2022

Monitoring condition of deburring media in vibration deburring machine

Inventors: Kristen Stone (Townsend, MA); Robert R. S. Di Carlo (Boxford, MA)
Assignee: Raytheon Company
B24B31/02G06K9/6253G06N20/00G06T7/0004G06T7/60G06T2207/20081
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Quick Facts
Patent No.
US 11,407,079
App. No.
16/816,533
Granted
Aug 9, 2022
Kind
B2
Abstract

An apparatus includes at least one memory configured to store at least one image of multiple pieces of deburring media used in a vibration deburring machine. The apparatus also includes at least one processor configured to analyze the at least one image to determine a condition of each of the multiple pieces of deburring media and determine an overall condition of the deburring media. The at least one processor is also configured to generate a graphical user interface containing a notification based on at least one of: the conditions of the multiple pieces of deburring media and the overall condition of the deburring media.

Claims (65)

1. An apparatus comprising:

at least one memory configured to store at least one image of multiple pieces of deburring media used in a vibration deburring machine; and

at least one processor configured to:

analyze the at least one image to determine a condition of each of the multiple pieces of deburring media;

determine an overall condition of the deburring media; and

generate a graphical user interface containing a notification based on at least one of: the conditions of the multiple pieces of deburring media and the overall condition of the deburring media.

2. The apparatus of claim 1 , wherein, to analyze the at least one image to determine the condition of each of the multiple pieces of deburring media, the at least one processor is configured to:

perform pattern recognition to compare shapes and sizes of the multiple pieces of deburring media to shapes and sizes of deburring media having known conditions; and

determine which of the deburring media having a specific known condition is most similar to each of the multiple pieces of deburring media.

3. The apparatus of claim 1 , wherein, to analyze the at least one image to determine the condition of each of the multiple pieces of deburring media, the at least one processor is configured to use a trained machine learning model to classify each of the multiple pieces of deburring media as having a specific condition.

4. The apparatus of claim 1 , wherein, to determine the overall condition of the deburring media, the at least one processor is configured to determine one or more ratios based on at least one of: a number of pieces of deburring media having a first condition, a number of pieces of deburring media having a second condition different than the first condition, and a total number of pieces of deburring media.

5. The apparatus of claim 1 , wherein the graphical user interface comprises:

the at least one image of the multiple pieces of deburring media;

multiple controls configured to receive user input in order to identify the at least one image to be analyzed; and

results of analyzing the at least one image, the results including the conditions of the multiple pieces of deburring media, the overall condition of the deburring media, and the notification.

6. The apparatus of claim 1 , wherein the at least one processor is further configured to predict at least one of:

a future overall condition of the deburring media in the vibration deburring machine;

a time at which additional deburring media should be added to the vibration deburring machine; and

a time when preventative maintenance should occur for the vibration deburring machine.

7. The apparatus of claim 1 , further comprising:

an interface configured to receive the at least one image from a fixed or portable imaging system.

8. A method comprising:

obtaining at least one image of multiple pieces of deburring media used in a vibration deburring machine;

analyzing the at least one image to determine a condition of each of the multiple pieces of deburring media;

determining an overall condition of the deburring media; and

generating a graphical user interface containing a notification based on at least one of: the conditions of the multiple pieces of deburring media and the overall condition of the deburring media.

9. The method of claim 8 , wherein analyzing the at least one image to determine the condition of each of the multiple pieces of deburring media comprises:

performing pattern recognition to compare shapes and sizes of the multiple pieces of deburring media to shapes and sizes of deburring media having known conditions; and

determining which of the deburring media having a specific known condition is most similar to each of the multiple pieces of deburring media.

10. The method of claim 8 , wherein analyzing the at least one image to determine the condition of each of the multiple pieces of deburring media comprises:

using a trained machine learning model to classify each of the multiple pieces of deburring media as having a specific condition.

11. The method of claim 8 , wherein determining the overall condition of the deburring media comprises:

determining one or more ratios based on at least one of: a number of pieces of deburring media having a first condition, a number of pieces of deburring media having a second condition different than the first condition, and a total number of pieces of deburring media.

12. The method of claim 8 , wherein the graphical user interface comprises:

the at least one image of the multiple pieces of deburring media;

multiple controls configured to receive user input in order to identify the at least one image to be analyzed; and

results of analyzing the at least one image, the results including the conditions of the multiple pieces of deburring media, the overall condition of the deburring media, and the notification.

13. The method of claim 8 , further comprising:

predicting at least one of:

a future overall condition of the deburring media in the vibration deburring machine;

a time at which additional deburring media should be added to the vibration deburring machine; and

a time when preventative maintenance should occur for the vibration deburring machine.

14. The method of claim 8 , further comprising:

receiving the at least one image from a fixed or portable imaging system.

15. A non-transitory computer readable medium containing instructions that when executed cause at least one processor to:

obtain at least one image of multiple pieces of deburring media used in a vibration deburring machine;

analyze the at least one image to determine a condition of each of the multiple pieces of deburring media;

determine an overall condition of the deburring media; and

generate a graphical user interface containing a notification based on at least one of: the conditions of the multiple pieces of deburring media and the overall condition of the deburring media.

16. The non-transitory computer readable medium of claim 15 , wherein the instructions that cause the at least one processor to analyze the at least one image to determine the condition of each of the multiple pieces of deburring media comprise:

instructions that when executed cause the at least one processor to:

perform pattern recognition to compare shapes and sizes of the multiple pieces of deburring media to shapes and sizes of deburring media having known conditions; and

determine which of the deburring media having a specific known condition is most similar to each of the multiple pieces of deburring media.

17. The non-transitory computer readable medium of claim 15 , wherein the instructions that cause the at least one processor to analyze the at least one image to determine the condition of each of the multiple pieces of deburring media comprise:

instructions that when executed cause the at least one processor to use a trained machine learning model to classify each of the multiple pieces of deburring media as having a specific condition.

18. The non-transitory computer readable medium of claim 15 , wherein the instructions that cause the at least one processor to determine the overall condition of the deburring media comprise:

instructions that when executed cause the at least one processor to determine one or more ratios based on at least one of: a number of pieces of deburring media having a first condition, a number of pieces of deburring media having a second condition different than the first condition, and a total number of pieces of deburring media.

19. The non-transitory computer readable medium of claim 15 , wherein the graphical user interface comprises:

the at least one image of the multiple pieces of deburring media;

multiple controls configured to receive user input in order to identify the at least one image to be analyzed; and

results of analyzing the at least one image, the results including the conditions of the multiple pieces of deburring media, the overall condition of the deburring media, and the notification.

20. The non-transitory computer readable medium of claim 15 , further containing instructions that when executed cause the at least one processor to predict at least one of:

a future overall condition of the deburring media in the vibration deburring machine;

a time at which additional deburring media should be added to the vibration deburring machine; and

a time when preventative maintenance should occur for the vibration deburring machine.

Assignments (2)
CORRECTIVE ASSIGNMENT TO CORRECT THE SECOND ASSIGNOR'S NAME PREVIOUSLY RECORDED AT REEL: 052095 FRAME: 0858. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Apr 1, 2020
From: STONE, KRISTEN; DI CARLO, ROBERT R. S.
To: RAYTHEON COMPANY
Reel/Frame 052282/0433 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 12, 2020
From: STONE, KRISTEN; DI CARLO, STONE R. S.
To: RAYTHEON COMPANY
Reel/Frame 052095/0858 →
Continuity (1)
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