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Thursday, August 20, 2015 10:40:59 AM
"SUMMARY OF THE INVENTION
None of the present processes use thermal sensors in conjunction with a thermal inverse model and augmented by weld pool frequency sensing for the specific purpose of controlling the size and shape of the weld pool. Some embodiments of the present invention provide a welding process based on sensing and direct control of the weld pool volume. Some embodiments of the present invention provide a method that combines a thermal sensor or sensors with a thermal inverse model that then allows direct inference and calculation of the weld pool volume, thereby allowing a control system to be implemented that directly controls the weld pool volume. An additional and augmenting method of sensing comprises sensing of the natural frequency of the weld pool, which in turn allows an independent estimate of the weld pool volume and, when combined with a thermal prediction, allows more accurate volume estimation and thus better process control of weld pool volume.
Some embodiments of the present invention provide a method of process control for any fusion welding process comprising constant weld pool volume control. Some embodiments of the present invention provide for monitoring and control of welding processes using a thermal inverse modelling approach coupled with multi-channel thermal sensing with the objective of maintaining a constant weld pool size or volume. Some embodiments of the present invention use thermal sensors combined with a real time or near real-time thermal model to determine the weld pool volume, a reduced-order thermal model coupled with an optimization method to solve a thermal inverse problem in near-real time, and the ability to implement models-based control using the thermal model and real-time sensing.
Some embodiments of the present invention provide algorithms and computational approaches that accomplish the following in near-real time: 1) monitor the thermal condition of the weld process (in real time) using any of a variety of sensors, such as a high speed non-contact pyrometer; 2) take the limited thermal data from a single point in a thermal field or several points in the thermal field and process it with a reduced order thermal model; and 3) solve an inverse problem in near-real time using the thermal model to infer the effective welding heat source energy distribution characteristics, including predicting the thermal field at multiple subregions of the weld region as well as the heat affected zone, predicting the cooling rate of the weld at the various weld liquid/solid interfaces, predicting the size and volume of the weld pool, and predicting what change in heat source distribution characteristics will be required to maintain a constant weld pool volume. The predictions can be compared to the thermal measurement and the welding machine tool settings can be changed accordingly to control the weld pool volume.
Embodiments of the present invention can be used with all arc welding processes (e.g., GMAW—gas metal arc welding; GTAW—gas tungsten arc welding; FCAW—flux cored arc welding; SAW—submerged arc welding; HWGTAW—hot wire gas tungsten arc welding; P-GMAW —pulsed gas metal arc welding; P-GTAW pulsed gas tungsten arc welding; Orbital tube welding—a specific type of GTAW; SMAW—submerged arc welding; VP-PAW—Variable polarity plasma arc welding; VP-GTAW—variable polarity tungsten arc welding; VP-GMAW—variable polarity gas metal arc welding.), beam welding processes (e.g., LBW, EBW), and material deposition and build-up processes involving any type of arc welding and any type of beam welding as the heat source."
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