Digital Twin Modeling Using Modal Verification and Simplified Geometry

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Solution Overview

Problem

Existing digital twin technologies require significant computational resources and large data volumes, making them inefficient for evaluating components' applicability across different machine specifications.

Innovation Solution

A method and system for building digital twin models that reduce data volume and computational demands by simplifying geometric models using modal analysis and eigenvalue/eigenvector comparisons, defining a digital twin model based on similarity verification.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If a detailed virtual model of the physical object is created, then the model accuracy is improved, but the data computation requirement increases

Engineering Contradiction:

Improvemodel accuracyVSAvoiddata computation requirement

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The patent segments the virtual model into essential geometric features and dynamic characteristics only, separating critical parameters (eigenvalues, eigenvectors) from non-essential detailed geometry. This segmentation maintains model accuracy for dynamic analysis while reducing overall data volume by excluding redundant geometric details.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent extracts only the essential dynamic characteristics (eigenvalues and eigenvectors) from the complete virtual model, taking out the critical information needed for dynamic analysis while removing unnecessary detailed geometric data. This extraction process reduces data computation requirements while preserving model accuracy for its intended purpose.

Inventive Principle:

Principle #2Taking out (Extraction)

2Measurement precision

If a detailed virtual model of the physical object is created, then the model accuracy is improved, but the operational processing resource increases

Engineering Contradiction:

Improvemodel accuracyVSAvoidoperational processing resource

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent segments the virtual model into essential geometric features and dynamic characteristics only, separating critical parameters (eigenvalues, eigvectors) from non-essential detailed geometry. This segmentation maintains model accuracy for dynamic analysis while reducing overall data volume by excluding redundant geometric details.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Inventive Principle:

Principle #2Taking out (Extraction)

3Productivity

If a simplified geometric solid model is used, then the data processing speed is improved, but the model verification complexity increases

Engineering Contradiction:

Improvemodel building speedVSAvoidverification process complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces complex geometric verification with modal analysis-based verification. Instead of verifying detailed geometric accuracy, the system uses modal analysis to compute eigenvalues and eigenvectors and compares them with actual measurement data, substituting a more efficient verification approach that is better suited to the purpose of dynamic characteristic analysis.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent changes the verification parameters from detailed geometric parameters to dynamic characteristic parameters (eigenvalues and eigenvectors). This parameter transformation simplifies the verification process by focusing on the most critical dynamic properties rather than exhaustive geometric details, reducing verification complexity while maintaining model effectiveness.

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 significantly reduces data and computational requirements while enabling effective evaluation of component suitability for diverse machine applications.

Implementation Method 1

calculating a set of model eigenvalues and a set of model eigenvectors by a modal analysis method according to second size data of the simplified geometric solid, the second position data and the material data

Methodology Applied

Scientific EffectModal analysis: Resonance

Implementation Method 2

the step (B) and obtaining the first position data from the component image are performed by a finite element method (FEM) or continuum mechanics

Methodology Applied

Scientific EffectFinite element method: Segmentation

Data Source

PatentUS12626028B2Method and system for building digital twin models

Publication Date: 2026.05.12 HIWIN TECH CORP

AI summary

A method and a system for building digital twin models allow the setting of a shape and dimensions of a simplified geometric solid corresponding to a component of a feeding system; after sampling the solid to obtain second position data, calculates a set of model eigenvalues and a set of model eigenvectors by a modal analysis method according to a material data of the component, the second position data and second size data of the solid; and defines the solid as a digital twin model of the component when it is determined by a modal verification method that a set of actual eigenvectors of the component is similar to the set of model eigenvectors. Data amounts of the second position and size data are far less than data amounts of first position and size data of an image of the component.