Wind turbine blade and wind turbine power generating apparatus

Patent metadata

Field	Value
Publication number	US-11679452-B2
Application number	US-201916526530-A
Country	US
Kind code	B2
Filing date	Jul 30, 2019
Priority date	Jun 24, 2015
Publication date	Jun 20, 2023
Grant date	Jun 20, 2023

Abstract

A machine-vision-assisted welding system comprises welding equipment, a time of Flight (ToF) camera operable to generate a three-dimensional depth map of a welding scene, digital image processing circuitry operable to extract welding information from the 3D depth map, and circuitry operable to control a function of the welding equipment based on the extracted welding information. The welding equipment may comprise, for example, arc welding equipment that forms an arc during a welding operation, and a light source of the ToF camera may emit light whose spectrum comprises a peak that is centered at a first wavelength, wherein the first wavelength is selected such that a power of the peak is at least a threshold amount above a power of light from the arc at the first wavelength.

First claim

What is claimed is:

1. A machine-vision-assisted welding system comprising:
a first Time of Flight (ToF) camera configured to generate a three-dimensional (3D) depth map of a first field of view;
a second camera configured to capture images of a second field of view that at least partially overlaps the first field of view;
digital image processing circuitry configured to:
identify at least one aspect of a welding scene of the second field of view from 3D depth map; and
generate an augmented reality user interface based on the at least one aspect; and

a display configured to display an augmented reality view representative of the second field of view and the augmented reality user interface.

2. The machine-vision-assisted welding system of claim 1 , further comprising circuitry configured to control an automation device based on the at least one aspect.

3. The machine-vision-assisted welding system of claim 1 , further comprising circuitry configured to control welding equipment based on the at least one aspect.

4. The machine-vision-assisted welding system of claim 1 , comprising:
an image sensor comprising a plurality of pixels, each of which is operable to convert light energy incident on it to an electrical signal; and
circuitry operable to, for each one of said pixels, measure time required for light to travel from a light source of said ToF camera to said welding scene and back to said one of said pixels.

5. The machine-vision-assisted welding system of claim 1 , further comprising:
a light source of said first ToF camera is configured to emit light whose spectrum comprises a peak that is centered at a first wavelength, wherein said first wavelength is selected such that a power of said peak, as measured at a particular pixel of an imager of said first ToF camera after reflection off of said welding scene, is at least a threshold amount above a power of light from a welding arc at said first wavelength, as measured at said particular pixel of said imager of said first ToF camera.

6. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect comprises activity of one or both of a human and a machine in said welding scene; and
further comprising circuitry configured to perform activity tracking, cycle time improvement, and workflow streamlining based on the at least one aspect.

7. The machine-vision-assisted welding system of claim 6 , wherein said activity comprises one or more of: welding operations, pre-welding operations and post-welding operations.

8. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect comprises activity of one or both of a human and a machine in said welding scene; and
further comprising circuitry configured to perform real-time assessment of risk of personal injury based on the at least one aspect.

9. The machine-vision-assisted welding system of claim 1 , wherein said digital image processing circuitry uses data from sources other than said first ToF camera to interpret said 3D depth map.

10. The machine-vision-assisted welding system of claim 1 , wherein the second camera is a second ToF camera, wherein said first ToF camera and said second ToF camera differ in one or more of: field of focus, mounting location, wavelength of light used, and targets viewed.

11. The machine-vision-assisted welding system of claim 1 , wherein the second camera is a non-ToF camera configured to capture visible-spectrum images, wherein said information from said depth map and visible-spectrum images are combined to provide an augmented reality user interface.

12. The machine-vision-assisted welding system of claim 1 , wherein the second camera is a non-ToF camera configured to capture infrared images, and being configured to use said infrared images to provide a temperature overlay on said 3D depth map.

13. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect comprises identification of one or more of: welding equipment, welding consumables, and welding operator; and
further comprising circuitry configured to perform one or more of: verification of compliance with a welding procedure specification (WPS), welder performance qualification (WPQ), procedure qualification record (PQR), or generation of alerts for error prevention, based on the at least one aspect.

14. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect identifies a sequence of welds being made on a workpiece in said welding scene; and
further comprising circuitry configured to perform one or both of:
indicating, via a user interface of welding equipment, a location of a next weld in said sequence; or
one or both of generating an alert and triggering of a lock out for prevention of wrong weld sequence.

15. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect comprises at least one of frequency or amplitude of surface oscillations of a weld puddle; and
further comprising circuitry configured to control welding equipment based on said at least one of frequency or amplitude of said surface oscillations based on the at least one aspect.

16. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect comprises joint fit-up condition of a workpiece in said welding scene; and
further comprising circuitry configured to adapt welding parameters used by welding equipment based on said fit-up condition based on the at least one aspect.

17. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect comprises actual joint seam location; and
further comprising circuitry configured to guide a robot based on the at least one aspect to ensure a welding tool center point follows said joint seam.

18. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect indicates maintenance condition of welding equipment; and
further comprising circuitry configured to perform one or both of:
preventative maintenance service based on the at least one aspect; or
condition-based maintenance service tracking and alert generation based on the at least one aspect.

19. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect indicates remaining stock of welding consumables; and
further comprising circuitry configured to generate an alert to replenish a supply of said welding consumables based on the at least one aspect.

20. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect indicates an identity and position of a welding workpiece in said welding scene; and
further comprising circuitry configured to automatically select a weld program to be used for welding said workpiece, based on said identity and position of said welding workpiece and based on the at least one aspect.

21. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect indicates a position and orientation of a welding torch in said welding scene; and
further comprising circuitry configured to automatically generate a weld program to be used by an automated robot for welding said workpiece based on the at least one aspect.

22. The machine-vision-assisted welding system of claim 1 , wherein:
said at least one aspect indicates an identity and position of a welding workpiece in said welding scene; and
further comprising circuitry configured to automatica

Assignees

• Illinois Tool Works

Inventors

• Hsu Christopher

Classifications

• B23K9/127

  Means for tracking lines during arc welding or cutting · CPC title

• B23K9/095 Primary

  Monitoring or automatic control of welding parameters · CPC title

• B23K26/044

  Seam tracking · CPC title

• B23K37/00

  Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass · CPC title

• B23K31/02 Primary

  relating to soldering or welding · CPC title