Liquid Metal Nozzle Meniscus Reconstruction From Reflective Images

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Solution Overview

Problem

Current 3D printing technologies face challenges in characterizing the liquid reflective surface of liquid metal drops within the nozzle of magnetohydrodynamic (MHD) printers due to the highly specular nature of the surfaces, which complicates shape estimation and motion analysis, especially when the drops are partially or fully within the nozzle.

Innovation Solution

A method involving video frame synthesis, dataset generation, and inverse mapping using artificial neural networks to reconstruct the shape and motion of the meniscus, allowing for the extraction of metrics like carrier oscillation frequency and waveform decay rate, enabling real-time adjustments to improve printing quality.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If stereo imaging is used to estimate depth and shape of liquid metal drops, then depth estimation can be obtained, but the highly specular surface causes dramatic light pattern changes with viewing angle making patch matching difficult

Engineering Contradiction:
Improvedepth estimationVSAvoidpatch matching difficulty
Core Design Contradiction:
Measurement precisionVSDifficulty of detecting and measuring

Solution Approach 1:

The patent creates a digital twin (synthetic video frame) that copies the visual appearance of the liquid metal meniscus under controlled virtual lighting conditions. This synthetic copy can be compared with real video frames to infer meniscus shape and motion without requiring direct patch matching on the challenging specular surface.

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The patent introduces an intermediate synthetic video frame generated by a graphics simulator as a mediator between the real video frame and the meniscus shape parameters. This intermediary allows indirect measurement by comparing the real scene with a controlled virtual representation.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Shape

If orthogonal profiles are used to extract shape from side views, then shape can be traced as outline, but the recessed or shrouded nozzle prevents camera introduction

Engineering Contradiction:
Improvedrop shapeVSAvoidcamera access
Core Design Contradiction:
ShapeVSEase of operation

Solution Approach 1:

The patent creates a virtual copy of the nozzle interior and meniscus through synthetic video frame generation. This digital twin allows observation and measurement of the meniscus shape from positions and angles that would be physically inaccessible to real cameras.

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The patent replaces the physical camera system with a virtual graphics simulator that can be positioned anywhere in 3D space. This substitution eliminates the mechanical constraint of camera access to the recessed nozzle while still providing shape measurement capability.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

3Loss of information

If conventional imaging techniques are used on highly specular surfaces, then images can be captured, but the reflective surface makes shape reconstruction inaccurate

Engineering Contradiction:
Improveshape information lossVSAvoidshape reconstruction accuracy
Core Design Contradiction:
Loss of informationVSMeasurement precision

Solution Approach 1:

The patent generates a synthetic video frame that copies the expected appearance of the meniscus under known virtual lighting conditions. By comparing this controlled synthetic copy with the real video frame, the system can accurately reconstruct shape information that would be lost or distorted in direct imaging of the specular surface.

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The patent changes the lighting parameters in the virtual environment to create optimal viewing conditions for shape measurement. By controlling virtual light source positions and intensities in the graphics simulator, the system can generate synthetic frames with favorable illumination patterns that reveal meniscus shape information.

Inventive Principle:
Principle #35Parameter changes

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 accurate characterization of the meniscus behavior within the nozzle, enhancing the consistency and quality of jetted drops, and allowing for real-time control of the printing process to maintain high-quality 3D object formation.

Implementation Method 1

an electrical current flows through a metal coil, which produces time-varying magnetic fields that induce eddy currents within a reservoir of liquid metal compositions

Methodology Applied
Scientific EffectElectromagnetic induction: Electromagnetic Induction

Implementation Method 2

Coupling between magnetic and electric fields within the liquid metal results in Lorentz forces that cause drops of the liquid metal to be ejected

Methodology Applied
Scientific EffectLorentz force: Lorentz Force

Data Source

PatentUS11958112B2Characterizing liquid reflective surfaces in 3D liquid metal printing
Publication Date: 2024.04.16 GENESEE VALLEY INNOVATIONS LLC
  • US11958112B2 patent drawing
  • US11958112B2 patent drawing
  • US11958112B2 patent drawing

AI summary

A three-dimensional (3D) printer includes a nozzle and a camera configured to capture a real image or a real video of a liquid metal while the liquid metal is positioned at least partially within the nozzle. The 3D printer also includes a computing system configured to perform operations. The operations include generating a model of the liquid metal positioned at least partially within the nozzle. The operations also include generating a simulated image or a simulated video of the liquid metal positioned at least partially within the nozzle based at least partially upon the model. The operations also include generating a labeled dataset that comprises the simulated image or the simulated video and a first set of parameters. The operations also include reconstructing the liquid metal in the real image or the real video based at least partially upon the labeled dataset.