Deflectometric Shape Detection for Rough and Glossy Surfaces

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Solution Overview

Problem

Current methods cannot effectively detect the shape of objects with optically rough, glossy, and optically smooth surfaces using a single device or method, particularly challenging in industries like automobile construction where painted components exhibit diffuse scattering, glossy, and reflective properties.

Innovation Solution

A method and device utilizing at least one camera and one or two linear lighting elements, with relative movement between the elements, to capture a sequence of images of the object surface, allowing for the evaluation of local surface inclinations and optical properties, including scattering properties, to detect shape and defects on various surface types.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If a single optical detection method is used, then the device complexity is reduced, but the measurement precision deteriorates because different methods are required for different surface types

Engineering Contradiction:
Improvedevice complexityVSAvoidmeasurement precision
Core Design Contradiction:
Device complexityVSMeasurement precision

Solution Approach 1:

The patent implements a universal optical detection device that can handle all three surface types (optically rough, glossy, and optically smooth) using a single deflectometric setup. The system achieves multi-functionality by recording image sequences during relative movement and evaluating local surface inclinations through computational processing, eliminating the need for multiple specialized devices while maintaining measurement precision across different surface optical properties

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Ease of operation

If traditional single-method optical detection is used, then the ease of operation is improved, but the adaptability deteriorates because the method cannot handle multiple surface types

Engineering Contradiction:
Improveease of operationVSAvoidadaptability
Core Design Contradiction:
Ease of operationVSAdaptability or versatility

Solution Approach 1:

The patent employs dynamic relative movement between the object and the optical detection device, recording image sequences during this movement. The system adapts to different surface types through computational evaluation of the dynamic image data, calculating local surface inclinations from the sequence of images. This dynamic approach enables the system to handle diverse surface optical properties while maintaining ease of operation through automated processing

Inventive Principle:
Principle #15Dynamics

3Measurement precision

If deflectometric methods are used for smooth surfaces, then the measurement precision is improved, but the reliability deteriorates when applied to rough or glossy surfaces

Engineering Contradiction:
Improvemeasurement precisionVSAvoidreliability
Core Design Contradiction:
Measurement precisionVSReliability

Solution Approach 1:

The patent performs preliminary actions by recording multiple images during relative movement before final evaluation. This creates a comprehensive data set that captures surface information from multiple angles and positions. The subsequent computational evaluation of this pre-recorded data enables reliable and precise shape detection for all surface types, including rough and glossy surfaces that would fail with traditional single-shot deflectometric methods

Inventive Principle:
Principle #10Preliminary 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 precise detection and testing of optically rough, glossy, and smooth surfaces, including those with multiple reflections, by providing information on surface inclinations and defects, suitable for applications like automotive paint inspection and optical element testing.

Implementation Method 1

The deflectometric methods are based on the law of reflection or refraction, which describes the relationship between the incident beam, the surface normal and the reflected or transmitted beam.

Methodology Applied
Scientific EffectReflection: Reflection

Implementation Method 2

The deflectometric methods are based on the law of reflection or refraction, which describes the relationship between the incident beam, the surface normal and the reflected or transmitted beam.

Methodology Applied
Scientific EffectRefraction: Refraction

Implementation Method 3

Due to this property, optically rough surfaces show an undirected, diffuse scattering of light.

Methodology Applied
Scientific EffectScattering: Scattering

Data Source

PatentEP3017273B1Method and device for optical shape recognition and/or examination of an object
Publication Date: 2019.03.27 SAC SIRIUS ADVANCED CYBERNETICS
  • EP3017273B1 patent drawingFigure 1a~1b
  • EP3017273B1 patent drawingFigure 2
  • EP3017273B1 patent drawingFigure 3

AI summary

The invention relates to a method for optical shape recognition and/or examination of an object (G) having the following steps: arranging at least one camera (K), at least one linear illumination element (B1, B2) and an object (G) relative to one another in such a way that an object surface (3) can be illuminated by the at least one illumination element and can be recorded by the camera (K); effecting a relative movement at least between two elements selected from a group consisting of the object (G), the at least one illumination element (B1, B2) and the camera (K), wherein a direction of movement encloses an angle different from 0° with the at least one illumination element (B1, B2); recording an image sequence (11) of the object surface (3) with the camera (K) during the relative movement, wherein the surface (3) of the object is imaged in an image plane of the camera (K); illuminating the surface (3) of the object during the lighting of the image plane with the at least one illumination element (B1, B2), and evaluating the recorded image sequence (11) with regard to local surface inclinations and/or local optical characteristics of the object surface (3).