Turbine inspection system, computer program product and method of inspecting
View Patent ↗The disclosure includes a system, a computer program product, and a method for inspecting a turbine system. In one embodiment, the system includes at least one computing device configured to inspect a turbine system by performing actions including: obtaining a set of pre-maintenance digital images of the turbine system, obtaining a set of post-maintenance digital images of the turbine system, comparing the set of pre-maintenance digital images with the set of post-maintenance digital images to identify an anomaly in the set of post-maintenance digital images, and comparing the set of post-maintenance digital image with a set of computer modeled image of the turbine system to determine a type of the anomaly in response to identifying the anomaly. The post-maintenance digital images depict the turbine system after a maintenance process has been performed on the turbine system.
1. A system comprising:
at least one computing device configured to inspect a turbine system by performing actions including:
obtaining a set of pre-maintenance digital images of the turbine system;
obtaining a set of post-maintenance digital images of the turbine system, the post-maintenance digital images depicting the turbine system after a maintenance process has been performed on the turbine system;
comparing the set of pre-maintenance digital images with the set of post-maintenance digital images to identify an anomaly in the set of post-maintenance digital images; and
comparing the set of post-maintenance digital images with a set of computer modeled images of the turbine system to determine a type of the anomaly in response to identifying the anomaly.
2. The system of claim 1 , wherein the obtaining of the set of pre-maintenance digital images is performed by capturing the set of pre-maintenance digital images using an industrial camera, and
wherein the obtaining of the set of post-maintenance digital images is performed by capturing the set of post-maintenance digital images using the industrial camera.
3. The system of claim 1 , wherein the at least one computing device further performs actions including:
retrieving the set of computer modeled images of the turbine system from a library of a plurality of computer modeled images for a plurality of distinct turbine systems.
4. The system of claim 1 , wherein the set of computer modeled images of the turbine system includes a computer modeled image for all components in the turbine system.
5. The system of claim 1 , wherein the determining of the type of the anomaly includes at least one of:
identifying an unknown component not included in the set of computer modeled images of the turbine system and included in the set of post-maintenance digital images,
identifying a displaced component included in the set of computer modeled images of the turbine system and missing from the set of post-maintenance digital images, or
identifying a misaligned component included in the set of computer modeled images of the turbine system in a first alignment and included in the set of post-maintenance digital images in a second alignment, distinct from the first alignment.
6. The system of claim 1 , wherein the type of the anomaly is associated with a pre-determined severity level.
7. The system of claim 6 , wherein the at least one computing device further performs actions including:
providing an indicator based on the pre-determined severity level in response to the determining of the type of the anomaly.
8. A program product stored on a non-transitory computer readable medium for inspecting a turbine system, the non-transitory computer readable medium comprising program code for causing the computer system to:
obtain a set of pre-maintenance digital images of the turbine system;
obtain a set of post-maintenance digital images of the turbine system, the post-maintenance digital images depicting the turbine system after a maintenance process has been performed on the turbine system;
compare the set of pre-maintenance digital images with the set of post-maintenance digital images to identify an anomaly in the set of post-maintenance digital images; and
compare the set of post-maintenance digital image with a set of computer modeled images of the turbine system to determine a type of the anomaly in response to identifying the anomaly.
9. The program product of claim 8 , further comprising program code for causing the computer system to:
retrieve the set of computer modeled images of the turbine system from a library of a plurality of computer modeled images for a plurality of distinct turbine systems.
10. The program product of claim 8 , wherein the set of computer modeled images of the turbine system includes a computer modeled image for all components in the turbine system.
11. The program product of claim 8 , wherein the determining of the type of the anomaly includes at least one of:
identifying an unknown component not included in the set of computer modeled images of the turbine system and included in the set of post-maintenance digital images,
identifying a displaced component included in the set of computer modeled images of the turbine system and missing from the set of post-maintenance digital images, or
identifying a misaligned component included in the set of computer modeled images of the turbine system in a first alignment and included in the set of post-maintenance digital images in a second alignment, distinct from the first alignment.
12. The program product of claim 8 , wherein the type of the anomaly is associated with a pre-determined severity level.
13. The program product of claim 12 , further comprising program code for causing the computer system to:
provide an indicator based on the pre-determined severity level in response to the determining of the type of the anomaly.
14. A method of inspecting a turbine system, the method comprising:
obtaining a set of pre-maintenance digital images of the turbine system;
obtaining a set of post-maintenance digital images of the turbine system, the post-maintenance digital images depicting the turbine system after a maintenance process has been performed on the turbine system;
comparing the set of pre-maintenance digital images with the set of post-maintenance digital images to identify an anomaly in the set of post-maintenance digital images; and
comparing the set of post-maintenance digital image with a set of computer modeled images of the turbine system to determine a type of the anomaly in response to identifying the anomaly.
15. The method of claim 14 , wherein the obtaining of the set of pre-maintenance digital images is performed by capturing the set of pre-maintenance digital images using an industrial camera, and
wherein the obtaining of the set of post-maintenance digital images is performed by capturing the set of post-maintenance digital images using the industrial camera.
16. The method of claim 14 , further comprising:
retrieving the set of computer modeled images of the turbine system from a library of a plurality of computer modeled images for a plurality of distinct turbine systems.
17. The method of claim 14 , wherein the set of computer modeled images of the turbine system includes a computer modeled image for all components in the turbine system.
18. The method of claim 14 , wherein the determining of the type of the anomaly includes at least one of:
identifying an unknown component not included in the set of computer modeled images of the turbine system and included in the set of post-maintenance digital images,
identifying a displaced component included in the set of computer modeled images of the turbine system and missing from the set of post-maintenance digital images, or
identifying a misaligned component included in the set of computer modeled images of the turbine system in a first alignment and included in the set of post-maintenance digital images in a second alignment, distinct from the first alignment.
19. The method of claim 14 , wherein the type of the anomaly is associated with a pre-determined severity level.
20. The method of claim 19 , further comprising:
providing an indicator based on the pre-determined severity level in response to the determining of the type of the anomaly.