Monitoring material processing using imaging signal density determined from inline coherent imaging (ICI)
Inventors
Galbraith, Christopher M. • Kanko, Jordan • WEBSTER, Paul J. L. • Van Vlack, Cole • Hayes, Genevieve Elizabeth
Assignees
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Publication Number
US-11458566-B2
Publication Date
2022-10-04
Expiration Date
Abstract
Systems, methods and apparatuses are used for monitoring material processing using imaging signal density calculated for an imaging beam directed to a workpiece or processing region, for example, during inline coherent imaging (ICI). The imaging signal density may be used, for example, to monitor laser and e-beam welding processes such as full or partial penetration welding. In some examples, the imaging signal density is indicative of weld penetration as a result of reflections from a keyhole floor and/or from a subsurface structure beneath the keyhole. The monitoring may include, for example, automated pass/fail or quality assessment of the welding or material processing or parts produced thereby. The imaging signal density may also be used to control the welding or material processing, for example, using imaging signal density data as feedback. The imaging signal density may be used alone or together with other measurements or metrics, such as distance or depth measurements.
Core Innovation
The disclosure monitors material processing by directing a process beam to a workpiece while generating an imaging beam directed to the workpiece. An interferometry output is produced from at least a component of the imaging beam reflected from the workpiece, and the interferometry output is detected to produce interferometry data including a plurality of A-scans of the workpiece.
A monitoring system determines an imaging signal density from the interferometry data by determining whether each A-scan contains a measurement point above a signal intensity threshold. The imaging signal density is calculated as a percentage of A-scans satisfying this condition within a bin of A-scans, with A-scans spaced by distance or time and bin construction described as user-defined, end-to-end starting with a first A-line, or overlapping bins.
The imaging signal density supports automated monitoring for process feedback/control, pass/fail quality assessment, and system health monitoring. The disclosure further uses signal-density-defined aspects of the phase change region and workpiece sub-region, including surface versus keyhole depth, vapor channel, vapor channel bottom, vapor channel sidewall, melt pool, and workpiece surface, along with material composition, material phase, and material density.
Claims Coverage
The independent claims identified are clm-00001, clm-00016, and clm-00022. Across these claims, the inventive subject matter centers on producing ICI A-scans and determining an ICI imaging signal density by thresholding each A-scan’s measurement point and calculating a percentage within a bin, with system-level and method-level configurations and optional spacing/binning refinements.
Process beam with inline coherent imaging interferometry data
Generating a process beam and directing the process beam to a workpiece; generating an imaging beam and directing the imaging beam to the workpiece; producing an interferometry output from at least a component of the imaging beam reflected from the workpiece; detecting the interferometry output to produce interferometry data including a plurality of A-scans of the workpiece.
Imaging signal density from thresholded a-scans within a-scan bins
Determining, using a monitoring system, an imaging signal density from the interferometry data by determining whether each A-scan contains a measurement point above a signal intensity threshold and calculating a percentage of A-scans satisfying this condition within a bin of A-scans.
Ici a-scans spaced by distance or time with bin-based imaging signal density
Producing a plurality of A-scans of a workpiece using inline coherent imaging (ICI), wherein the A-scans are spaced by distance or time; and determining, using a monitoring system, an ICI signal density by determining whether each A-scan contains a measurement point above a signal intensity threshold and calculating a percentage of A-scans satisfying this condition within a bin of A-scans.
System with material processing, ici interferometry, and monitoring for bin-based signal density
A material processing system configured to generate a process beam and to direct the process beam toward a workpiece; an inline coherent imaging (ICI) system configured to generate an imaging beam, to direct the imaging beam toward the workpiece together with the process beam, to produce an interferometer output from a reflection of the imaging beam, and to detect the interferometer output to produce ICI data; and a monitoring system programmed to receive the ICI data and to determine at least an ICI imaging signal density by determining whether each of the A-scans contains a measurement point above a threshold and calculating a percentage of A-scans satisfying this condition within a bin of A-scans.
All independent claims cover producing ICI-based interferometry data including a plurality of A-scans and computing an ICI imaging signal density by checking whether each A-scan contains a measurement point above a signal intensity threshold and calculating the percentage of qualifying A-scans within a bin. The method claim variants further specify spacing by distance or time, while the system claim integrates a material processing system, an ICI system, and a monitoring system programmed to compute the bin-based signal density from the received A-scan data.
Stated Advantages
Automated pass/fail quality assessment.
Process feedback/control.
System health monitoring.
Classification of A-scans into phase change region/workpiece sub-region aspects using imaging signal density.
Documented Applications
Monitoring material processing including laser/e-beam welding with full/partial penetration and wobble welding.
Monitoring keyhole during full penetration welding using the signal density.
Monitoring material surfaces ahead of and behind a material modification process using the signal density.
Classifying aspects of a phase change region or workpiece sub-region, including using wobble welding-based monitoring and classification.
Monitoring system health.
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