IN-PROCESS WELD GEOMETRY METHODS & SYSTEMS

• US 20120091185A1
• Filed: 10/18/2010
• Published: 04/19/2012
• Est. Priority Date: 10/18/2010
• Status: Abandoned Application

• Current Assignee: Georgia Tech Research Corporation (University System of Georgia)
• Original Assignee: Georgia Tech Research Corporation (University System of Georgia)
• Inventors: Ume, I. Charles, Rogge, Matthew Douglas
• Application Number:
  US12/906,859
• Publication Number:
  US 20120091185A1
• Time in Patent Office: Days
• US Class Current: 228/1.1
• CPC Class Codes: B23K 31/125 Weld quality monitoring
• CPC Class Codes: B23K 9/0956 using sensing means, e.g. optical
• CPC Class Codes: B23K 9/173 and of a consumable electrode

Abstract

Some embodiments include in-process welding devices to compensate for error associated with detected weld penetration depth. Exemplary devices can generally include an ultrasonic energy source, an ultrasonic receiving sensor, and a controller. The ultrasonic energy source can be disposed to generate ultrasonic energy through a first specimen being welded to a second specimen. A weld seam can be used to join the first specimen to the second specimen. The ultrasonic sensor can be disposed on an opposite side of the weld seam from the ultrasonic energy source, and configured to detect ultrasonic energy propagated from the first specimen side of the weld seam to the second specimen side of the weld seam. The controller can be disposed to receive data from the ultrasonic sensor, configured to determine time of flight signal data corresponding to arrival of the ultrasonic energy detected by the ultrasonic sensor, and configured to compare the determined time of flight signal data to a model to compute error associated with the determined time of flight signal data due to a dynamic welding environment. Other aspects, embodiments, and features are claimed and described.

Claims

1. An in-process welding device to compensate for error associated with detected weld penetration depth, the device comprising:

an ultrasonic energy source disposed to generate ultrasonic energy through a first specimen being welded to a second specimen, wherein a weld seam is used to join the first specimen to the second specimen;

an ultrasonic sensor disposed on an opposite side of the weld seam from the ultrasonic energy source, the ultrasonic sensor configured to detect ultrasonic energy propagated from the first specimen side of the weld seam to the second specimen side of the weld seam; and

a controller disposed to receive data from the ultrasonic sensor and configured to determine time of flight signal data corresponding to arrival of the ultrasonic energy detected by the ultrasonic sensor and further configured to compare the determined time of flight signal data to a model to compute error associated with the determined time of flight signal data due to a dynamic welding environment.

2. The in-process welding device of claim 1, wherein the controller is configured to utilize the computed error to adjust welding parameters in the dynamic welding environment based on the computed error.

3. The in-process welding device of claim 1, wherein the controller is configured to utilize the computed error to determine an estimated time of flight value for use in estimating weld penetration depth.

4. The in-process welding device of claim 1, wherein the model is based on a neuro-fuzzy based dynamic data model based at least partially on wire feed rate history.

5. The in-process welding device of claim 1, wherein the controller is configured to vary at least one of location of the first and second specimens, laser parameters, and weld parameters in the dynamic welding environment based on the computed error.

6. The in-process welding device of claim 1, wherein the ultrasonic energy source comprises at least one of a pulsed laser, laser, laser phase array, and an EMAT.

7. The in-process welding device of claim 1, wherein the ultrasonic sensor comprises at least one of an electro-magnetic acoustic transducer, a piezo-electric transducer, laser inferometer, and vibrometer.

8. The in-process welding device of claim 1, wherein the controller receives ultrasonic energy from the ultrasonic energy source for use in instructing the ultrasonic sensor to detect ultrasonic energy propagated through the first specimen.

9. The in-process welding device of claim 1, wherein the model is trained at least partially based on test samples that have been characterized via destructive testing.

10. An in-process welding method to compensate for error occurring during welding processes, the method comprising:

preparing an error compensation model to account for error introduced during a dynamic welding environment;

sensing on-line time of flight data proximate one or more welding specimens during a dynamic welding environment with one or more data sensors; and

providing estimated time of flight data based on the error compensation model and the sensed on-line time of flight data.

11. The method of claim 10, further comprising subtracting estimated time of flight error based on the error compensation model from the sensed on-line time of flight data to provide the estimated time of flight data.

12. The method of claim 10, wherein the error compensation model is a neuro-fuzzy compensation model.

13. The method of claim 10, further comprising altering welding system parameters in response to the estimated time of flight data.

14. The method of claim 10, further comprising providing an ultrasonic energy source to direct ultrasonic energy toward a welding specimen to generate ultrasonic energy to be sensed by one or more sensors, said one or more sensors being located on an opposing side of a weld seam from the ultrasonic energy source.

15. The method of claim 10, wherein the error compensation model is at least partially dependent upon wire feed rate of a welder.

16. The method of claim 10, further comprising analyzing a previously welded specimen to determine actual, off-line time of flight data and using said off-line time of flight data to generate the error compensation model.

17. An in-process welding device to compensate for error associated with detected weld penetration depth, the device comprising:

a welding station comprising a welding specimen, a welding torch, an ultrasonic energy source, and an ultrasonic energy transducer, the welding specimen having a welding seam for joining a first specimen and a second specimen;

the ultrasonic energy source being disposed to emit ultrasonic energy toward the first specimen for creating a wave energy that travels through the welding seam toward the second specimen;

the ultrasonic energy transducer being disposed to sense the wave energy traveling through the second specimen; and

a controller, operatively coupled to the ultrasonic energy transducer, configured to compare sensed wave energy to error compensation data and in response to said comparison adjust welding parameters in the dynamic welding environment.

18. The device of claim 17, wherein the error compensation data is based on a nuero-fuzzy error compensation model.

19. The device of claim 17, wherein the controller is further configured to compare the sensed wave energy to error compensation data to determine estimated time of flight data for use in estimating weld penetration depth.

20. The device of claim 17, wherein the controller is further configured to determine an estimated weld penetration depth of the weld seam based on the error compensation model.