Electron Emitter Geometry Assessment Using AI Similarity Analysis

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Solution Overview

Problem

Current methods for assessing the component quality of electron emitters, particularly thermionic emitters, are inadequate as they fail to provide a comprehensive and standardized evaluation of geometry and deformation, leading to incomplete parameterization and potential undetection of deformations, which affects the assessment of component lifetime and performance.

Innovation Solution

A computer-implemented method that uses an electron emitter image dataset and geometry model to calculate geometry information, ascertain similarity with other emitters, and assess component quality, incorporating an AI model trained via machine learning to link geometry information with performance data for improved differentiation and quality assessment.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If comprehensive parameterization of electron emitter geometry is performed using measuring machines, then measurement precision and completeness are improved, but measuring time and device complexity increase significantly

Engineering Contradiction:

Improvegeometry measurement precisionVSAvoidmeasuring time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces mechanical measuring machines with optical imaging systems (cameras, microscopes) to capture electron emitter geometry. Images are processed through AI models to extract geometric parameters, substituting mechanical contact measurement with non-contact optical measurement that is faster and causes no vacuum dwell time

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent creates digital copies (images) of the electron emitter geometry and processes these copies through AI models to extract measurement data. This allows comprehensive geometry assessment without physically measuring the actual component, eliminating the need for prolonged vacuum exposure during measurement

Inventive Principle:

Principle #26Copying

2Ease of operation

If selective measurement of electron emitter geometry is performed to reduce manual effort, then ease of operation is improved, but measurement precision and completeness deteriorate

Engineering Contradiction:

Improvemanual measurement effortVSAvoidgeometry assessment completeness

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The system performs automatic image processing and geometric parameter extraction using AI models without requiring manual measurement operations. The AI model autonomously identifies features, extracts parameters, and assesses geometry quality, making the process both easier to operate and more comprehensive

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent transforms the measurement approach from selective point measurements to comprehensive image-based parameter extraction. By changing from manual coordinate input to automated image analysis, the system achieves complete geometry characterization with minimal human intervention

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If comprehensive geometry parameterization is performed under atmospheric pressure, then measurement precision is improved, but vacuum component dwell time increases which affects component quality

Engineering Contradiction:

Improvegeometry parameterization accuracyVSAvoidvacuum component quality

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent uses optical imaging systems that can operate through vacuum windows or in vacuum environments, eliminating the need to break vacuum for measurement. Images are captured and processed externally, allowing geometry assessment without compromising vacuum integrity or component quality

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces an intermediary imaging system that bridges the gap between vacuum environment and external measurement equipment. Optical images serve as intermediaries, transferring geometry information from the vacuum-sealed electron emitter to external AI processing systems without requiring vacuum breach

Inventive Principle:

Principle #24Intermediary (Mediator)

4Productivity

If AI models are used to assess component quality from image data, then productivity is improved, but device complexity increases

Engineering Contradiction:

Improvequality assessment efficiencyVSAvoidAI model integration complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent develops universal AI models that can process multiple types of images (microscope, camera, scanner) and extract various geometric parameters across different electron emitter configurations. This multi-functionality consolidates multiple specialized tools into a single system, improving productivity while managing complexity through standardization

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20240303803A1Method for assessing a component quality of an electron emitter

Publication Date: 2024.09.12 SIEMENS HEALTHINEERS AG

AI summary

One or more example embodiments of the present invention relates to a computer-implemented method for assessing a component quality of an electron emitter as a function of an ascertained degree of similarity with at least one further electron emitter.