Automated Workpiece Material Classification via Spatial Frequency Analysis

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Solution Overview

Problem

Manual input of material type and surface condition by operators in machine tools often leads to inferior processing outcomes due to inaccuracies, as existing methods lack automation for precise determination.

Innovation Solution

Automated determination of material type and surface condition using spatial frequency domain analysis of images, incorporating anisotropy and reflectance data, with the aid of neural networks or template matching for classification, and optimized processing parameter selection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If manual input of material type and surface condition by operator is used, then ease of operation is improved, but measurement precision deteriorates

Engineering Contradiction:

Improveease of operationVSAvoidmeasurement precision

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent replaces the manual mechanical input system with an automated optical measurement system. An illuminating device illuminates the workpiece surface, and an image recording device captures images that are automatically analyzed to determine material type and surface condition, eliminating manual input errors while maintaining ease of operation through automation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service by allowing the workpiece itself to provide the information needed for identification. The workpiece surface properties (reflectivity, spatial frequency characteristics) automatically reveal material type and surface condition when illuminated and imaged, without requiring external manual input or intervention.

Inventive Principle:

Principle #25Self-service

2Measurement precision

If automated determination using spatial frequency domain analysis is implemented, then measurement precision is improved, but device complexity increases

Engineering Contradiction:

Improvemeasurement precisionVSAvoiddevice complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary evaluation device that performs spatial frequency domain analysis. This intermediary component processes the raw image data through Fourier transformation and statistical analysis to extract material identification features, bridging the gap between simple image capture and accurate material classification without requiring complex direct measurement systems.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system transforms the image data from the spatial domain to the spatial frequency domain through Fourier transformation. This parameter change in the data representation allows for more effective extraction of material characteristics through statistical analysis of frequency distributions, improving measurement precision while using standard image processing techniques.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If automated classification system is implemented, then productivity is improved, but loss of time for data processing increases

Engineering Contradiction:

ImproveproductivityVSAvoidloss of time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs preliminary action by capturing multiple images at different exposure times before final analysis. This preliminary image acquisition with varied exposure settings ensures that sufficient information is captured in advance, allowing for rapid and accurate material identification without requiring repeated measurements or adjustments during processing.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The automated system enables continuous operation by eliminating manual intervention steps. The image recording device continuously captures images, and the evaluation device continuously processes the data to determine material type and surface condition, maintaining uninterrupted workflow and maximizing productivity without significant time loss.

Inventive Principle:

Principle #20Continuity of useful action

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

Enables accurate and automated classification of material types and surface conditions, improving processing outcomes by optimizing parameters such as advance rate and laser power, reducing human error and enhancing processing efficiency.

Implementation Method 1

The determination is carried out on the basis of at least one image converted into the spatial frequency domain... The illumination of the surface of the workpiece is typically bright-field incident illumination, in which the illuminating radiation is reflected directly back into the observation direction from the surface of the workpiece.

Methodology Applied

Scientific EffectLight reflection: Reflection

Data Source

PatentUS10115190B2Determining a material type and/or a surface condition of a workpiece

Publication Date: 2018.10.30 TRUMPF WERKZEUGMASCHINEN GMBH & CO KG

AI summary

This disclosure relates to methods and apparatuses for determining a material type and/or a surface condition of a workpiece. A surface of the workpiece is illuminated with illuminating radiation. At least one image of the illuminated surface is recorded. The material type and/or the surface condition of the workpiece is determined on the basis of a statistical analysis of the at least one image converted into a spatial frequency domain.