Internal Temperature Estimation in Powder Bed Fusion via Kalman Filter
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Solution Overview
Problem
Powder bed fusion (PBF) processes face challenges in monitoring and controlling internal temperature distributions within components due to limitations in temperature sensing, leading to defects such as residual stresses, porosity, and anisotropy, as commercial systems rely on remote and incomplete thermal measurements.
Innovation Solution
The implementation of a closed-loop state estimation system using a simplified linear time-invariant (LTI) model and Ensemble Kalman Filter to estimate internal temperature distributions by discretizing part geometry into finite units, converting thermal transport models into ordinary differential equations, and applying Kalman filters for accurate temperature estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If remote temperature sensing is used (thermocouple on build plate or pyrometer on surface), then the sensing system is simple and accessible, but the temperature measurement is incomplete and inaccurate for internal temperature distribution
Solution Approach 1:
The patent uses an optical path as an intermediary to transmit infrared radiation from internal locations through the transparent build plate to the pyrometer sensor. This allows remote sensing without direct contact with the melt pool, maintaining sensing system accessibility while enabling internal temperature measurement
Solution Approach 2:
The patent replaces mechanical thermocouple contact sensing with optical/infrared remote sensing. Instead of physically placing a thermocouple in the melt pool (mechanical system), the system uses infrared radiation detection through optics (optical system) to measure temperature non-contactingly
2Loss of information
If no internal temperature sensing is implemented, then the system operates simply without advanced sensors, but temperature history cannot be determined for process control
Solution Approach 1:
The patent performs preliminary action by establishing an optical path through the transparent build plate before manufacturing begins. The optical components are positioned and aligned in advance, enabling subsequent temperature measurements without adding complexity during the manufacturing process
Solution Approach 2:
The patent implements feedback by using pyrometer temperature measurements to monitor and control the manufacturing process in real-time. The temperature history data feeds back to the control system to adjust processing parameters and prevent defects
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 predictive and accurate monitoring and control of temperature fields during the PBF process, reducing defects and improving the quality of manufactured components by providing real-time temperature data and feedback for process optimization.
Implementation Method 1
selectively melting a pattern of desired geometry into the powder by application of a high-powered laser
Implementation Method 2
application of a high-powered laser
Implementation Method 3
monitor the melt pool using a digital camera based pyrometer
Implementation Method 4
heat transport between elements
Data Source
AI summary
Estimation algorithms, methods, and systems are provided that estimate the internal temperatures inside of a part being built using powder bed fusion (PBF). Closed-loop state estimation is applied to the problem of monitoring temperature fields within parts during the PBF build process. A simplified linear time-invariant (LTI) model of PBF thermal physics with the properties of stability, controllability and observability is presented. In some aspects, an Ensemble Kalman Filter is applied to the model. Linear time-varying (LTV) systems are also contemplated.