IP Library Granted Patent US 10,054,552
Granted Patent B1
US 10,054,552 · App. 15/716,911 · Granted Aug 21, 2018

System and method for automated fluorescent penetrant inspection

Inventors: Sergio S. Frutuoso (Avon, CT); Alan Matthew Finn (Hebron, CT); Gene B. Donskoy (Farmington, CT)
Assignee: UNITED TECHNOLOGIES CORPORATION
G01N21/91G01N21/8806G01N21/8851G01N35/00584G01N2021/8887
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Quick Facts
Patent No.
US 10,054,552
App. No.
15/716,911
Granted
Aug 21, 2018
Kind
B1
Abstract

An example method of inspecting a part includes applying a penetrant dye to the part, the penetrant dye exhibiting a fluorescent color when subjected to light from a lighting device. A portion of the part is illuminated with light from the lighting device. An image of the portion of the part is automatically recorded with a camera while the portion is illuminated. An uncertainty metric for the image is automatically determined that is indicative of a likelihood that pixels in the image having the fluorescent color represent damage to the part. At least one of the part, lighting device, and camera are automatically adjusted based on the uncertainty metric being within a predefined range. The automatic recording, determining, and adjusting steps are iteratively repeated until the uncertainty metric is greater than the predefined range, or a predefined number of iterations have been performed for the portion of the part.

Claims (63)

1. A method of inspecting a part, comprising:

applying a penetrant dye to a part, the penetrant dye exhibiting a fluorescent color when subjected to light from a lighting device;

illuminating a portion of the part with light from the lighting device;

automatically recording an image of the portion of the part with a camera while the portion is illuminated;

automatically determining an uncertainty metric for the image indicative of a likelihood that pixels in the image having the fluorescent color represent damage to the part;

automatically adjusting at least one of the part, the lighting device, and the camera based on the uncertainty metric being within a predefined range; and

iteratively repeating the automatic recording, determining, and adjusting steps until the uncertainty metric is greater than the predefined range, or a predefined number of iterations have been performed for the portion of the part.

2. The method of claim 1 , wherein the light is ultraviolet (UV) light.

3. The method of claim 1 , wherein said automatically adjusting at least one of the part, the lighting device, and the camera comprises automatically adjusting at least one of the following:

a relative position of the part with respect to one or both of the lighting device and the camera; and

an orientation of one or more of the part, the lighting device, and the camera.

4. The method of claim 1 , wherein said automatically adjusting at least one of the part, the lighting device, and the camera based comprises at least one of:

automatically adjusting one or more of a light intensity, light illumination area, and polarization of the lighting device; and

automatically adjusting an exposure setting of the camera to accommodate the adjustment to the lighting device.

5. The method of claim 1 , comprising:

determining that the portion of the part is damaged based on the uncertainty metric being greater than the predefined range; and

determining that the portion of the part is not damaged based on the uncertainty metric not exceeding the predefined range for any of the iterations.

6. The method of claim 5 , comprising:

based on a determination that the portion of the part is damaged, automatically depositing a damage marker on the part in proximity to the damage.

7. The method of claim 1 , wherein said determining an uncertainty metric for the image comprises:

converting the image, which uses a first color representation, to a second image that uses a different, second color representation;

performing a color detection to determine areas in the second image having the fluorescent color;

performing a pattern detection based on the color detection; and

determining a likelihood that a detected pattern depicts damage to the part based on pattern matching with a defect model.

8. The method of claim 7 , comprising:

situating a fiducial marker that exhibits the fluorescent color in close enough proximity to the portion of the part that it is recorded as part of the image;

wherein said performing a color detection is performed based on the fiducial marker in the image.

9. The method of claim 7 , wherein said performing a pattern detection comprises:

creating a skeleton image based on the color detection; and

performing a Hough transform of the skeletal image.

10. The method of claim 1 , comprising

situating a light filter between the part and a portion of either the camera or the lighting device when recording images, the light filter preventing one or more of certain non-UV light and light polarizations from passing through the filter.

11. The method of claim 1 , comprising

situating the camera, which is part of a borescope, inside the part when recording images of the portion of the part.

12. A part inspection system comprising:

a part onto which a penetrant dye is applied, the penetrant dye exhibiting a fluorescent color when subjected to light within a given frequency band;

a lighting device operable to project light within the given frequency band onto the part;

a camera; and

a controller configured to:

automatically record an image of a portion of the part with the camera while the portion is illuminated by the light within the given frequency band;

automatically determine an uncertainty metric for the image indicative of a likelihood that pixels in the image having the fluorescent color represent damage to the part;

automatically adjust at least one of the part, the lighting device, and the camera based on the uncertainty metric being within a predefined range; and

iteratively repeat the automatic recording, determining, and adjusting until the uncertainty metric is greater than the predefined range, or a predefined number of iterations have been performed for the portion of the part.

13. The part inspection system of claim 12 , comprising at least one robotic arm operable to move with six degrees of freedom, wherein said automatically adjusting at least one of the part, the light, and the camera based comprises manipulating the at least one robotic arm to adjust at least one of the following:

a relative position of the part with respect to one or both of the lighting device and the camera; and

an orientation of one or more of the part, the lighting device, and the camera.

14. The part inspection system of claim 12 , wherein to automatically adjust at least one of the part, the lighting device, and the camera, the controller is configured to perform at least one of:

automatically adjust one or more of a light intensity, light illumination area, and polarization of the lighting device; and

automatically adjust an exposure setting of the camera to accommodate the adjustment to the lighting device.

15. The part inspection system of claim 12 , wherein the controller is configured to:

determine that the portion of the part is damaged based on the uncertainty metric being greater than the predefined range; and

determine that the portion of the part is not damaged based on the uncertainty metric not exceeding the predefined range for any of the iterations.

16. The part inspection system of claim 15 , comprising a marking device, wherein the controller is configured to automatically deposit a damage marker on the part in proximity to the damage based on a determination that the portion of the part is damaged.

17. The part inspection system of claim 12 , wherein to determine an uncertainty metric for the image, the controller is configured to:

convert the image, which uses a first color representation, to a second image that uses a different, second color representation;

perform a color detection to determine areas in the second image having the fluorescent color;

perform a pattern detection based on the color detection; and

determine a likelihood that a detected pattern depicts damage to the part based on pattern matching with a defect model.

18. The part inspection system of claim 17 , wherein to perform a pattern detection, the controller is configured to:

create a skeleton image based on the color detection; and

perform a Hough transform of the skeletal image.

19. The part inspection system of claim 12 , wherein the given frequency band includes ultraviolet light, and the part inspection system comprises a light filter situated between the part and a portion of either the camera or the lighting device when the camera records an image of the part, the light filter operable to prevent one or more of certain non-UV light and light polarizations from passing through the filter.

20. The part inspection system of claim 12 , wherein the camera is part of a borescope, and is situated within the part when recording images of the part.

Assignments (4)
CHANGE OF NAME Recorded Jul 27, 2023
From: RAYTHEON TECHNOLOGIES CORPORATION
To: RTX CORPORATION
Reel/Frame 064714/0001 →
CORRECTIVE ASSIGNMENT TO CORRECT THE AND REMOVE PATENT APPLICATION NUMBER 11886281 AND ADD PATENT APPLICATION NUMBER 14846874. TO CORRECT THE RECEIVING PARTY ADDRESS PREVIOUSLY RECORDED AT REEL: 054062 FRAME: 0001. ASSIGNOR(S) HEREBY CONFIRMS THE CHANGE OF ADDRESS. Recorded Mar 4, 2021
From: UNITED TECHNOLOGIES CORPORATION
To: RAYTHEON TECHNOLOGIES CORPORATION
Reel/Frame 055659/0001 →
CHANGE OF NAME Recorded Sep 4, 2020
From: UNITED TECHNOLOGIES CORPORATION
To: RAYTHEON TECHNOLOGIES CORPORATION
Reel/Frame 054062/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 27, 2017
From: FRUTUOSO, SERGIO S.; FINN, ALAN MATTHEW; DONSKOY, GENE B.
To: UNITED TECHNOLOGIES CORPORATION
Reel/Frame 043713/0905 →
Cited By (2)
US 12,412,263 US 12,614,273