Additive Manufacturing Sensor Mapping for Melt Pool Defect Detection
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Solution Overview
Problem
Current additive manufacturing technologies face challenges in accurately spatially mapping sensor data during the process, particularly in representing the influence of the melt pool or energy beam spot, which can lead to inadequate detection of defects such as porosity and under-dosing of powder, due to insufficient resolution and representation of sensor values.
Innovation Solution
The method generates cell values for a cell-based spatial mapping of sensor data by merging sensor values over an area or volume comparable to the melt pool or energy beam spot, using techniques like summation, weighted summation, and blurring to create a more representative mapping that accounts for the physical processes, allowing for improved defect identification and process control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor values are mapped directly to individual pixels without merging, then spatial resolution is maximized, but the representation of melt pool influence and defect detection accuracy deteriorates
Solution Approach 1:
The patent merges multiple sensor values that fall within a defined region of interest (ROI) corresponding to the melt pool or energy beam spot into a single cell value. This merging process, which can use summation, weighted summation, or averaging, creates a spatial mapping where each cell represents the integrated sensor signal over the physical extent of the melt pool, thereby accurately representing the thermal influence zone while maintaining defect detection capability through the aggregated signal.
2Reliability
If sensor values are merged over large areas to represent melt pool influence, then reliability of process monitoring is improved, but spatial resolution and ability to detect localized defects deteriorates
Solution Approach 1:
The patent applies local quality by making the merging region adaptive - the size and shape of the ROI for merging sensor values corresponds to the actual melt pool dimensions, which vary spatially and temporally. By dynamically adjusting the merging area to match the physical extent of the melt pool at each location and time point, the system maintains high spatial resolution where needed while ensuring reliable process monitoring through appropriate signal aggregation in each local region.
3Measurement precision
If sensor data is collected at high sampling rates to capture melt pool dynamics, then measurement precision is improved, but data processing complexity and time consumption increases
Solution Approach 1:
The patent applies preliminary action by performing the merging of sensor values into cell values representing the melt pool region during or immediately after data acquisition, rather than processing all raw sensor data separately afterward. This preliminary aggregation reduces the volume of data requiring further processing and analysis, while the cell values maintain the essential temporal dynamics of the melt pool through the integrated signal, thereby reducing computational complexity without sacrificing measurement precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables higher resolution spatial mapping, facilitating the detection of defects and process anomalies, leading to enhanced in-process control and improved quality of the additive manufacturing output by correlating cell values with object density and allowing for closed-loop control adjustments.
Implementation Method 1
a laser beam is scanned across portions of the powder layer that correspond to a cross-section (slice) of the object being constructed. The laser beam melts the powder to form a solidified layer.
Implementation Method 2
a spatially resolved detector (e.g. a CCD or CMOS camera) or an integrated detector (e.g. a photodiode with a large active area) for capturing radiation emitted by a melt zone
Data Source
AI summary
A method of generating a spatial map of sensor data collected during additive manufacturing, in which a plurality of layers of powder are selectively melted with an energy beam to form an object. The method includes receiving sensor data collected during additive manufacturing of an object, the sensor data including sensor values, the sensor values captured for different coordinate locations of the energy beam during the additive manufacturing of the object, and generating cell values for a corresponding cell-based spatial mapping of the sensor data. Each of the cell values is determined from a respective plurality of the sensor values extending over an area/volume comparable to an extent of the melt pool or the energy beam spot.