Normalized Thermal Defect Detection for Additive Manufacturing Layers
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Solution Overview
Problem
Current additive manufacturing quality assurance methods are limited, particularly in non-destructive testing, as data from wide area thermal sensors can be biased by varying distances and scan lengths, making it difficult to accurately characterize the quality of parts produced.
Innovation Solution
The method involves monitoring a heat source with an optical temperature sensor across a powder bed, recording scan intensity and duration, generating characteristic curves, and comparing them to baseline curves to identify defects, while accounting for distance and scan length variations using additional sensors and data normalization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a wide area thermal sensor is used to monitor the additive manufacturing process, then the coverage area is increased, but the measurement precision deteriorates due to varying distances between the sensor and different portions of the build plane
Solution Approach 1:
The build plane is divided into multiple discrete regions, each with its own baseline characteristic curve. The wide area sensor collects data for each region separately, and measurements are compared against region-specific baselines rather than a single global baseline. This segmentation approach maintains measurement precision across the entire wide coverage area by accounting for distance variations on a regional basis.
Solution Approach 2:
The patent transforms raw thermal sensor data into normalized characteristic curves that account for varying distances. By changing the parameter representation from absolute temperature values to normalized characteristic curves that incorporate distance compensation, the system maintains measurement precision across the wide sensor coverage area.
2Measurement precision
If destructive testing is used to verify part quality, then the measurement precision is improved, but the productivity deteriorates due to part destruction and inability to apply to production parts
Solution Approach 1:
Baseline characteristic curves are established during the design and validation phase before production begins. These pre-established baselines represent known good parts and are stored for comparison during production. This preliminary action enables rapid non-destructive quality verification during manufacturing without sacrificing measurement precision.
Solution Approach 2:
The patent creates a digital copy of the expected thermal signature through baseline characteristic curves. Instead of physically testing each part, the system compares sensor data against these digital baselines, enabling non-destructive quality verification that maintains productivity while achieving sufficient measurement precision for production environments.
3Adaptability or versatility
If the heat source scans across the powder bed with varying scan lengths, then the manufacturing flexibility is improved, but the measurement precision deteriorates due to artificial bias in thermal data
Solution Approach 1:
The patent replaces mechanical measurement approaches with a computational normalization system. Instead of physically adjusting the sensor to maintain constant distance, the system uses software-based normalization to compensate for varying scan lengths and distances, maintaining measurement precision while preserving scan pattern flexibility.
Solution Approach 2:
The patent introduces asymmetric normalization factors that are applied differently to different regions based on their specific characteristics. Each region's data is normalized using factors tailored to that region's geometry and distance from the sensor, allowing varying scan lengths while maintaining measurement precision through region-specific compensation.
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 allows for non-destructive identification and characterization of defects in additive manufacturing, ensuring the quality of produced parts by correcting for systematic errors and providing a reliable method for quality control.
Implementation Method 1
monitoring a heat source scanning across a powder bed using an optical temperature sensor
Implementation Method 2
the heat source melts the incrementally added powder by welding regions of the powder layer creating a moving molten region
Data Source
AI summary
The disclosed embodiments relate to the monitoring and control of additive manufacturing. In particular, a method is shown for removing errors inherent in thermal measurement equipment so that the presence of errors in a product build operation can be identified and acted upon with greater precision. Instead of monitoring a grid of discrete locations on the build plane with a temperature sensor, the intensity, duration and in some cases position of each scan is recorded in order to characterize one or more build operations.