Aeronautical Component CT Registration Using Gradient-Weighted Alignment

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Solution Overview

Problem

Existing non-destructive testing methods for aeronautical parts, particularly those made of three-dimensionally woven carbon fiber composites, face inaccuracies due to poor contour extraction and meshing in areas with low energy, leading to registration errors and unequal weighting of different part areas, resulting in suboptimal alignment of tomographic volumes with CAD models.

Innovation Solution

A method involving tomographic imaging, surface generation, gradient field calculation, and registration optimization using a similarity criterion based on the correlation of surface normals with volume gradients, which bypasses surface extraction and emphasizes areas with higher gradients for accurate alignment.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If traditional contour extraction and meshing methods are used for registration, then the process is simpler to implement, but the accuracy deteriorates in areas with low energy

Engineering Contradiction:
Improveease of implementationVSAvoidregistration accuracy
Core Design Contradiction:
Ease of manufactureVSMeasurement precision

Solution Approach 1:

The invention extracts only the necessary information (gradient field characteristics and normal vectors) from the tomographic volume, rather than performing full contour extraction and meshing. This selective extraction maintains implementation simplicity while avoiding the accuracy problems associated with traditional methods in low-energy areas

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The invention changes the registration approach from using extracted contours and meshes to using gradient field parameters and normal vectors directly. This parameter transformation allows the method to achieve higher accuracy without significantly increasing implementation complexity

Inventive Principle:
Principle #35Parameter changes

2Ease of operation

If uniform weighting is applied to all areas during registration, then the process is more straightforward, but the alignment precision deteriorates in poorly defined areas

Engineering Contradiction:
Improvesimplicity of registration processVSAvoidalignment precision
Core Design Contradiction:
Ease of operationVSManufacturing precision

Solution Approach 1:

The invention applies different weighting to different areas of the part based on their gradient strength. Areas with stronger gradients (better defined) receive higher weight, while areas with weaker gradients (poorly defined) receive lower weight. This local differentiation improves alignment precision without significantly complicating the registration process

Inventive Principle:
Principle #3Local quality

Solution Approach 2:

The weighting scheme is dynamic rather than static, automatically adjusting the importance of different regions based on their gradient characteristics. This allows the registration process to adapt to local variations in data quality, improving precision while maintaining operational simplicity

Inventive Principle:
Principle #15Dynamics

3Ease of manufacture

If surface extraction is performed to obtain contours for registration, then the traditional registration process can be applied, but errors accumulate in areas with low energy

Engineering Contradiction:
Improvecompatibility with traditional methodsVSAvoidregistration reliability
Core Design Contradiction:
Ease of manufactureVSReliability

Solution Approach 1:

The invention extracts gradient field information and normal vectors directly from the tomographic volume without performing surface extraction. This selective extraction of essential geometric information maintains compatibility with traditional registration concepts while eliminating the error accumulation problem associated with surface extraction in low-energy areas

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

Instead of extracting surfaces from volumes and then registering, the invention inverts the approach by using volume-based gradient fields and normal vectors directly for registration. This inversion eliminates the intermediate surface extraction step that causes error accumulation, while still achieving reliable alignment

Inventive Principle:
Principle #13The other way round (Inversion)

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 method achieves robust and accurate registration of tomographic volumes with CAD models, minimizing errors and ensuring precise alignment by emphasizing areas with stronger gradients, thereby enhancing the integrity verification of aeronautical parts.

Implementation Method 1

a tomograph whose X-ray generator emits a beam that passes through the part being examined. This beam is then analyzed, after attenuation, by a detection system

Methodology Applied
Scientific EffectX-ray attenuation: X-Ray

Implementation Method 2

calculation of a gradient field of the volume and generation of a vector field normal to said surface

Methodology Applied
Scientific EffectGradient computation:

Implementation Method 3

optimizing a similarity criterion defined by a function taking into account the correlation between the normal vectors of the normal vector field of the surface displaced by a transformation and the gradient of the gradient field of the volume

Methodology Applied
Scientific EffectVector correlation:

Data Source

PatentEP3381013B1Method of non-destructive checking of a component for aeronautics
Publication Date: 2026.02.11 SAFRAN SA
  • EP3381013B1 patent drawingFigure 1~2
  • EP3381013B1 patent drawingFigure 3~4b
  • EP3381013B1 patent drawingFigure 5

AI summary

The invention relates to a method of non-destructive checking of a component for aeronautics, the method comprising the following steps of acquiring a volume by tomographic imaging, of generating by computer simulation a surface corresponding to the component to be analysed, of registering the volume and the surface (by optimizing a similarity criterion defined by a function taking into account the correlation between normal vectors of a field of normal vectors of the surface displaced by transformation and a gradient of a gradient field of the volume, said optimization being performed as a function of transformations for determining the optimal transformation which maximizes the similarity criterion, of storing the optimal transformation, of establishing the correspondence between the surface and the volume obtained with the aid of the optimal transformation.