Spectral Data Mapping for Unknown Material Prediction

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Solution Overview

Problem

Existing technologies fail to generate spectral data for materials where such data has not been measured, limiting the analysis of unknown materials with desired performance characteristics.

Innovation Solution

An information processing device and method that utilize dimension reduction techniques to project spectral data into two-dimensional maps, identify unknown data points, and convert them into spectral data, enabling the generation of spectral data for unknown materials without direct measurement.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If spectral data is measured from known materials only, then measurement accuracy is ensured, but the ability to obtain spectral data for unknown materials with desired performance is lost

Engineering Contradiction:

Improvespectral data accuracyVSAvoidcapability to obtain spectral data for unknown materials

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The patent creates a virtual copy of spectral data by mapping unknown material characteristics to the two-dimensional space formed by principal components from measured materials. This allows generation of spectral data for unknown materials without direct measurement, resolving the contradiction between measurement accuracy and adaptability to unknown materials

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent introduces principal component analysis as an intermediary that transforms spectral data into a two-dimensional map. This intermediary representation enables the system to handle unknown materials by mapping them to the established principal component space, bridging the gap between measured and unmeasured materials

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of operation

If dimension reduction is applied to map spectral data to two-dimensional space, then data visualization and analysis are improved, but information loss may occur

Engineering Contradiction:

Improvedata analysis capabilityVSAvoidspectral data information

Core Design Contradiction:

Ease of operationVSLoss of information

Solution Approach 1:

The patent transforms high-dimensional spectral data into a two-dimensional space using principal component analysis. This dimensionality change enables effective visualization and analysis while the patent compensates for potential information loss by using the principal components as a basis for generating spectral data of unknown materials

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS12614321B2Information processing device, information processing method, and non-transitory computer-readable storage medium for measured and unknown material

Publication Date: 2026.04.28 TOYOTA JIDOSHA KK

AI summary

An information processing device includes a non-transitory memory and a processor coupled to the non-transitory memory. The processor is configured to: set respective spectral data measured from each of plural materials as an instance of vector data; apply a dimension reduction technique to plural instances of vector data so as to generate two-dimensional map data in which each of the plural instances of vector data is projected two-dimensionally as each of plural plot points; identify unknown data indicating a plot point that is different from a plot point already present on the two-dimensional map data; convert the unknown data into converted spectral data; and output the converted spectral data.