Electric heating – Metal heating – By arc
Reexamination Certificate
1999-11-03
2001-02-06
Shaw, Clifford C. (Department: 1725)
Electric heating
Metal heating
By arc
Reexamination Certificate
active
06184491
ABSTRACT:
TECHNICAL FIELD
This invention relates generally to a method and apparatus for determining quality of an arc welding process in real time and, more particularly, to a method and apparatus for utilizing welding parameter signals such as, but not limited to, current, voltage, and wire feed speed and determining if defects are being formed in a weld bead.
BACKGROUND ART
In general, gas metal arc welding is defined as an arc welding process in which an electrical arc is established between a consumable electrode, such as a wire, and a base metal to be welded. Droplets are formed on the tip of the molten electrode, e.g., wire, and are transferred across the arc. There is an inert or slightly reactive shielding gas that is provided in the arc region to reduce the reaction of the base metal, molten electrode, and the arc that is due to contamination with the atmosphere. A constant voltage/potential power source is utilized to maintain welding voltage invariable at a particular electrode feed speed. The disturbances in the arc region such as shielding gas contamination that can form porosity, weld pool interference, and excessive melt-through can be detected in the current and voltage signals as the power source compensates for these events. Similar types of welding can also include flux core welding and submerged arc welding.
Prior welding strategies measure variations in welding current signals and welding voltage signals in order to track a weld seam, adjust fill volume, or detect shielding gas contamination. In addition, short circuits can be detected as well as pulse frequency in the sampled electrical signals. Another method for detecting weld quality problems is disclosed in U.S. Pat. No. 5,750,957, which issued on May 12, 1998. The method includes determinations based on the standard deviation of the electrical signal, the summed power spectrum of the electrical signal, and/or the average absolute value of the time derivative of the electrical signal and requires a minimum threshold limit.
The present invention is directed to overcoming one or more of the problems set forth above.
DISCLOSURE OF THE INVENTION
In one aspect of this invention, a method for monitoring quality of a weld bead during a welding process utilizing an electronic controller is disclosed. The method includes the steps of determining an average power spectral density value for a first welding parameter signal between a first predetermined frequency and a second predetermined frequency, determining an average power spectral density value for a second welding parameter signal between a first predetermined frequency and a second predetermined frequency and comparing said average power spectral density value for said second welding parameter signal with said average power spectral density value for said first welding parameter signal and terminating said welding process if said average power spectral density value for said first welding parameter signal exceeds said average power spectral density value for said second welding parameter signal.
In another aspect of this invention, an apparatus for monitoring quality of a weld bead during a welding process is disclosed. The apparatus includes an electronic controller for receiving a first welding parameter signal and a second welding parameter signal and then determining an average power spectral density value for said first welding parameter signal between a first predetermined frequency and a second predetermined frequency and determining an average power spectral density value for said second welding parameter signal area between a first predetermined frequency and a second predetermined frequency and then comparing said average power spectral density value for said second welding parameter signal with said average power spectral density value for said first welding parameter signal and terminating said welding process if said average power spectral density value for said first welding parameter signal exceeds said average power spectral density value for said second welding parameter signal.
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Crane Bryan L.
Jones Brett A.
Kilty Alan L.
Ludewig Howard W.
Caterpillar Inc.
Kercher Kevin M.
Shaw Clifford C.
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