ROBOTIC REPAIR OR MAINTENANCE OF AN ASSET

• US 20170329297A1
• Filed: 03/29/2017
• Published: 11/16/2017
• Est. Priority Date: 05/13/2016
• Status: Active Grant

• Current Assignee: GE Infrastructure Technology, LLC (General Electric Company)
• Original Assignee: General Electric Company
• Inventors: Gilman, Charles Robert, Castillo-Effen, Mauricio, Theurer, Charles Burton
• Granted Patent: US 10,518,411 B2
• Time in Patent Office: Days
• CPC Class Codes: B25J 9/1602 characterised by the control system, structure, architecture
• CPC Class Codes: B25J 9/163 learning, adaptive, model based, rule based expert control
• CPC Class Codes: B25J 9/1661 characterised by task planning, object-oriented languages
• CPC Class Codes: B25J 9/1664 characterised by motion, path, trajectory planning
• CPC Class Codes: B25J 9/1671 characterised by simulation, either to verify existing program or to create and verify new program, CAD/CAM oriented, graphic oriented programming systems
• CPC Class Codes: B25J 9/1697 Vision controlled systems
• CPC Class Codes: F01D 5/005 Repairing methods or devices
• CPC Class Codes: F22B 37/00 Component parts or details of steam boilers venting devices F16K24/00; steam traps or like apparatus F16T
• CPC Class Codes: G05B 19/042 using digital processors G05B19/05 takes precedence
• CPC Class Codes: G05B 19/048 Monitoring; Safety
• CPC Class Codes: G05B 19/4065 Monitoring tool breakage, life or condition
• CPC Class Codes: G05B 19/4097 characterised by using design data to control NC machines, e.g. CAD/CAM G05B19/4093 takes precedence
• CPC Class Codes: G05B 2219/35134 3-D cad-cam
• CPC Class Codes: G05B 2219/40323 Modeling robot environment for sensor based robot system
• CPC Class Codes: G05B 2219/42329 Defective measurement, sensor failure
• CPC Class Codes: G05B 2219/49007 Making, forming 3-D object, model, surface
• CPC Class Codes: G05D 1/0094 involving pointing a payload, e.g. camera, weapon, sensor, towards a fixed or moving target
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
• CPC Class Codes: Y10S 901/01 Mobile robot
• CPC Class Codes: Y10S 901/44 : inspection

Abstract

A method includes receiving, via at least one sensor of a robot, sensor data indicating one or more characteristics of an asset. The method includes detecting, based on the sensor data, an existing or imminent defect of the asset. The method includes fabricating a part suitable for use in correcting the defect. The structure of the part is derived using one or both of a digital representation of the asset generated using the sensor data or stored reference data related to the asset.

Claims

1. A method, comprising:

receiving, via at least one sensor of a robot, sensor data indicating one or more characteristics of an asset;

detecting, based on the sensor data, an existing or imminent defect of the asset; and

perform a corrective action that corrects the defect, wherein the structure of the part is derived using one or both of a digital representation of the asset generated using the sensor data or stored reference data related to the asset.

2. The method of claim 1, comprising creating or updating a three dimensional (3D) model of the part based on the sensor data, wherein the 3D model comprises a location of the defect with respect to geometry of the 3D model.

3. The method of claim 2, wherein the 3D model is created or updated based on one or both of the digital representation of the asset or the stored reference data related to the asset.

4. The method of claim 2, comprising sending, the 3D model to a fabrication device configured to fabricate the part based on the 3D model using additive manufacturing.

5. The method of claim 4, comprising instructing the robot or another robot to autonomously repair the defect using the part.

6. The method of claim 5, wherein the instruction to autonomously repair the defect includes a location of the defect determined using the sensor data.

7. The method of claim 1, comprising dividing a three dimensional model (3D) model into a plurality of 3D printable parts based on print times of each of the 3D printable parts, source materials used to print each of the 3D printable parts, or any combination thereof.

8. A robotic system configured to monitor an asset, comprising:

at least one robot comprising at least one sensor capable of detecting one or more characteristics of an asset and at least one effector capable of performing a repair or maintenance operation on the asset; and

a processing system comprising at least one processor operatively coupled to at least one memory, wherein the at least one processor is configured to;

receive, via at least one sensor of a robot, sensor data indicating one or more characteristics of an asset;

detect, based on the sensor data, an existing or imminent defect of the asset; and

perform a corrective action that corrects the defect using one or both of a digital representation of the asset or stored reference data related to the asset.

9. The robotic system of claim 8, wherein the corrective action comprises fabricating a part suitable for correcting the defect.

10. The robotic system of claim 8, wherein the 3D model is displayed on a display and is colored based on the sensor data.

11. The robotic system of claim 8, wherein the processing system is configured to determine whether the 3D model is solid.

12. The robotic system of claim 11, wherein the processing system is configured to:

send a first signal indicative of instructions to display the 3D model on a display of the robotic system;

receive a second signal indicative of modifications to the 3D model to enable the 3D model to become solid; and

send a third signal indicative of instructions to print a part from the modified 3D model on a fabrication device.

13. The robotic system of claim 8, comprising a fabrication device proximate to a location of the asset or on the asset.

14. A non-transitory, computer readable medium comprising instructions configured to be executed by a processor of a robotic system comprising at least one robot, wherein the instructions comprise instructions configured to cause the processor to:

receive, via at least one sensor of the at least one robot, sensor data indicating one or more characteristics of an asset;

detect, based on the sensor data, an existing or imminent defect of the asset; and

fabricate a part suitable for correcting the defect using one or both of a digital representation of the asset or stored reference data related to the asset.

15. The non-transitory computer readable medium of claim 15, comprising instructions configured to cause the processor to build, update, or maintain a digital representation of the asset based on the one or more characteristics, wherein the digital representation of the asset comprises a mathematical model of parts of the asset.

16. The non-transitory computer readable medium of claim 15, wherein the digital representation comprises a physical geometry of the asset.

17. The non-transitory computer readable medium of claim 15, comprising instructions configured to cause the processor to divide a model of the repair into a plurality of parts based on an amount of time to fabricate each of the parts, source materials used to fabricate each of the parts, or any combination thereof.

18. The non-transitory computer readable medium of claim 15, comprising instructions configured to cause the processor to create, update, or maintain a three dimensional (3D) model of the part suitable to be used in the repair of the defect.

19. The non-transitory computer readable medium of claim 18, wherein the 3D model is displayed on a display and is colored based on the sensor data.

20. The non-transitory computer readable medium of claim 19, comprising instructions configured to cause the processor to:

send a first signal indicative of instructions to display the 3D model on a display of the robotic system;

receive a second signal indicative of modifications to the 3D model to enable the 3D model to become solid; and

send a third signal indicative of instructions to print a part from the modified 3D model on a fabrication device.