FR3125156B1 - NON-DESTRUCTIVE CONTROL OF A PART - Google Patents
NON-DESTRUCTIVE CONTROL OF A PART Download PDFInfo
- Publication number
- FR3125156B1 FR3125156B1 FR2107556A FR2107556A FR3125156B1 FR 3125156 B1 FR3125156 B1 FR 3125156B1 FR 2107556 A FR2107556 A FR 2107556A FR 2107556 A FR2107556 A FR 2107556A FR 3125156 B1 FR3125156 B1 FR 3125156B1
- Authority
- FR
- France
- Prior art keywords
- defect
- image
- image element
- probability value
- scores
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000007547 defect Effects 0.000 abstract 8
- 238000013528 artificial neural network Methods 0.000 abstract 1
- 238000004364 calculation method Methods 0.000 abstract 1
- 238000000034 method Methods 0.000 abstract 1
- 238000009659 non-destructive testing Methods 0.000 abstract 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
Landscapes
- Engineering & Computer Science (AREA)
- Quality & Reliability (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Image Analysis (AREA)
Abstract
L’invention concerne un procédé et un système de contrôle non destructif d’une pièce à partir d’une image (9) de ladite pièce (11), ladite image étant formée par un ensemble d’éléments d’images, caractérisé en ce qu’il comporte: - un module de classification (5) comprenant un ensemble de réseaux de neurones (51), configuré pour classifier un ensemble de scores de défaut pour chaque élément d’image, et - un module de calcul (7) configuré pour : - déterminer pour chaque élément d’image, un indicateur de défaut maximal à partir dudit ensemble de scores de défaut correspondant, - calculer pour chaque élément d’image une valeur de probabilité de défaut en fonction de l’indicateur de défaut maximal, - attribuer un label de défaut à tout élément d’image ayant une valeur de probabilité de défaut qui dépasse un seuil élémentaire prédéterminé, et - rejeter ladite pièce (11) au cas où le nombre d’éléments d’image présentant des labels de défaut dépasse un seuil global prédéterminé. Figure pour l’abrégé : Figure 1.The invention relates to a method and a system for non-destructive testing of a part from an image (9) of said part (11), said image being formed by a set of image elements, characterized in that that it comprises: - a classification module (5) comprising a set of neural networks (51), configured to classify a set of defect scores for each image element, and - a calculation module (7) configured for: - determining for each image element, a maximum defect indicator from said set of corresponding defect scores, - calculating for each image element a defect probability value as a function of the maximum defect indicator, - assign a defect label to any image element having a defect probability value which exceeds a predetermined elementary threshold, and - reject said part (11) in case the number of image elements presenting defect labels exceeds a predetermined global threshold. Figure for abstract: Figure 1.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FR2107556A FR3125156B1 (en) | 2021-07-12 | 2021-07-12 | NON-DESTRUCTIVE CONTROL OF A PART |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FR2107556A FR3125156B1 (en) | 2021-07-12 | 2021-07-12 | NON-DESTRUCTIVE CONTROL OF A PART |
FR2107556 | 2021-07-12 |
Publications (2)
Publication Number | Publication Date |
---|---|
FR3125156A1 FR3125156A1 (en) | 2023-01-13 |
FR3125156B1 true FR3125156B1 (en) | 2023-11-10 |
Family
ID=77999095
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
FR2107556A Active FR3125156B1 (en) | 2021-07-12 | 2021-07-12 | NON-DESTRUCTIVE CONTROL OF A PART |
Country Status (1)
Country | Link |
---|---|
FR (1) | FR3125156B1 (en) |
Family Cites Families (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20180322623A1 (en) * | 2017-05-08 | 2018-11-08 | Aquifi, Inc. | Systems and methods for inspection and defect detection using 3-d scanning |
US10672588B1 (en) * | 2018-11-15 | 2020-06-02 | Kla-Tencor Corporation | Using deep learning based defect detection and classification schemes for pixel level image quantification |
US10755401B2 (en) * | 2018-12-04 | 2020-08-25 | General Electric Company | System and method for work piece inspection |
SE1930421A1 (en) * | 2019-12-30 | 2021-07-01 | Unibap Ab | Method and means for detection of imperfections in products |
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2021
- 2021-07-12 FR FR2107556A patent/FR3125156B1/en active Active
Also Published As
Publication number | Publication date |
---|---|
FR3125156A1 (en) | 2023-01-13 |
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Legal Events
Date | Code | Title | Description |
---|---|---|---|
PLFP | Fee payment |
Year of fee payment: 2 |
|
PLSC | Publication of the preliminary search report |
Effective date: 20230113 |
|
PLFP | Fee payment |
Year of fee payment: 3 |