Equipment damage prediction system using neural networks
First Claim
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1. A repair system comprising:
- a generative adversarial network (GAN) system comprising;
a generator sub-network configured to examine one or more images of actual damage to equipment, the generator sub-network also configured to create one or more images of potential damage based on the one or more images of actual damage that were examined; and
a discriminator sub-network configured to examine the one or more images of potential damage to determine whether the one or more images of potential damage represent progression of the actual damage to the equipment,the repair system further comprising an automated system for automatically repairing at least one damaged portion of at least one component of the equipment based on the one or more images of potential damage, the automated system comprising a robotic system,wherein the at least one component comprises at least one turbine blade, andwherein the robotic system sprays an additive onto a thermal barrier coating of the at least one turbine blade.
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Abstract
A generative adversarial network (GAN) system includes a generator sub-network configured to examine one or more images of actual damage to equipment. The generator sub-network also is configured to create one or more images of potential damage based on the one or more images of actual damage that were examined. The GAN system also includes a discriminator sub-network configured to examine the one or more images of potential damage to determine whether the one or more images of potential damage represent progression of the actual damage to the equipment.
13 Citations
20 Claims
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1. A repair system comprising:
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a generative adversarial network (GAN) system comprising; a generator sub-network configured to examine one or more images of actual damage to equipment, the generator sub-network also configured to create one or more images of potential damage based on the one or more images of actual damage that were examined; and a discriminator sub-network configured to examine the one or more images of potential damage to determine whether the one or more images of potential damage represent progression of the actual damage to the equipment, the repair system further comprising an automated system for automatically repairing at least one damaged portion of at least one component of the equipment based on the one or more images of potential damage, the automated system comprising a robotic system, wherein the at least one component comprises at least one turbine blade, and wherein the robotic system sprays an additive onto a thermal barrier coating of the at least one turbine blade. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method comprising:
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examining one or more images of actual damage to equipment using a generator sub-network of a generative adversarial network (GAN); creating one or more images of potential damage using the generator sub-network based on the one or more images of actual damage that were examined; determining whether the one or more images of potential damage represent progression of the actual damage to the equipment by examining the one or more images of potential damage using a discriminator sub-network of the GAN, and automatically repairing, using a robotic system, at least one damaged portion of the equipment based on the one or more images of potential damage, wherein the equipment comprises at least one of a surface of a road and a surface of a sidewalk. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A repair system comprising:
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a generative adversarial network (GAN) system comprising; a generator sub-network configured to be trained using one or more images of actual damage to equipment, the one or more images comprising one or more pixels, the generator sub-network also configured to create one or more images of potential damage based on the one or more images of actual damage that were examined; and a discriminator sub-network configured to examine the one or more images of potential damage to determine whether the one or more images of potential damage represent progression of the actual damage to the equipment, the repair system further comprising an automated system for automatically repairing at least one damaged portion of the equipment based on the one or more images of potential damage, the automated system comprising a robotic system, wherein the discriminator sub-network classifies the one or more pixels into different categories of objects, and wherein the different categories of objects include at least one of a tree, a car, a person, a bird, spalling of a thermal barrier coating, a sign, and a crack in a surface. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification