CONTROLLING EQUIPMENT AGAINST ITS DIGITAL MODEL

Abstract

The invention proposes a simple, precise, fast and automatic method and control system to verify the suitability between a manufactured piece of equipment and its digital model previously created.The system according to the invention comprises a scanner configured to produce a three-dimensional point cloud (21) representative of said equipment (19), as well as a processor and a memory configured to: -superimpose said point cloud (21) on said digital model (17), -coordinate said point cloud (21) to polychrome images (22) captured during the scanning of the equipment and stored in a memory, -break said point cloud (21) into several sets of points (21a-21c), each set of points corresponding to an object identified in the polychrome images, -establish a correspondence between said sets of points and nodes (231) of a tree structure (23) identifying the digital model, and -evaluate an adequacy between the point cloud (21) and the digital model by analyzing said correspondence between said sets of points and said nodes of the tree structure.

Description

It should be noted that scanner 3 is advantageously an active non-contact scanner, currently available on the professional market (such as FARO, CO-Scan, SURPHASER, etc.), suitable for probing equipment by emitting light radiation onto it and detecting the reflection. More specifically, the scanner is advantageously a laser or infrared scanner that is moved around the object to be scanned. The scanner records its own movement by measuring the shift in its own position. Alternatively, the scanner is fixed and the equipment is scanned by a laser beam or strip, and the distances between the scanner and the points on the surface of the equipment are determined by triangulation. The scanning process involves collecting a series of measurement points representing the distances between the scanner and the scanned equipment. These measurement points establish precise data on the shape of the equipment 19 and, after processing by the scanner supplier's software, produce a monochrome or polychrome point cloud 21 that can be displayed on the screen 15. More specifically, the processing of measurement points relies on a succession of recorded polychrome images. Indeed, to process the colorization of the point cloud, the scanner and associated software use polychrome images of the equipment captured and recorded by the scanner in parallel with the acquisition of the measurement points. Thus, the scanning automatically generates a series of information grouped into a series of folders. These folders contain a first set including all the polychrome image sequences and a second set including the measurement points that generate the point cloud 21 representing the equipment 19. At stages E2-E5, computer 5 is configured to process the data relating to the point cloud collected by scanner 3 and to compare them with those of the digital model previously stored in memory 9. Indeed, at step E2, the processor 7 is configured to position the point cloud 21 on the digital model 17 and to display the resulting overlay on the screen 15 to the best of the geometric dimensions taken from the equipment and drawn in the DMU (matching of shapes and dimensions). Advantageously, the point cloud 21 is cleaned before being superimposed on the digital model 17. This cleaning consists of removing superfluous points as well as those not belonging to the equipment 19 and of no interest for the study and analysis in progress. At step E3, the processor 7 is configured to use the sequence of polychrome images 22 captured during the three-dimensional scan and stored in memory 9 to establish an L1 link or coordination between the point cloud 21 and these polychrome images 22. It should be noted that with a known pattern recognition software, it is easy to isolate particular objects in the sequence of polychrome images 22. Thus, by associating the space of the polychrome images 22 with the space of the point cloud 21, it is then easy to identify the different sets of points within the point cloud 21 that correspond to these particular objects. Indeed, it suffices to determine, for each object isolated in the polychrome images 22, the points in the point cloud 21 which have this object as their image (in the mathematical sense). In other words, the coordination between the space of polychrome images 22 and the point cloud space 21 allows, with a lower cost of computational steps, to carry out a precise subdivision of the point cloud 21 into several relevant sets as will be described later in steps E4, E41 and E42. More specifically, processor 7 establishes this coordination by synchronizing the succession of polychrome images 22 with the point cloud 21 according to the successive capture dates of these polychrome images 22. At step E4, the processor 7 is configured to split the point cloud 21 into several point sets 21a-21c representing different objects of the equipment 19. More specifically, each point set corresponds to a particular object identified in the polychrome images. Fig. 4 schematically illustrates an example of a method for splitting the point cloud 21, according to an embodiment of the invention. According to this embodiment, the processor 7 is configured to subdivide the point cloud 21 using the identification between the polychrome image space 22 and the point cloud space 21 realized in step E3. In particular, at step E41, processor 7 is configured to identify or isolate objects exhibiting elementary or specific physical characteristics or parameters (e.g., specific geometric shapes, colors, positions, pixels, etc.) within the polychrome images 22. This identification can be performed using a known shape and / or color recognition technique or software. It should be noted that recognition software is suitable for rapidly identifying the various elementary physical characteristics between two representations using loops. At step E42, the processor 7 is configured to subdivide the point cloud 21 into several point sets 21a-21c by associating each point set with a corresponding object identified in the polychrome images. In other words, thanks to the L1 link established at step E3 between the point cloud 21 and the polychrome images 22, the processor 7 can find the point packet that corresponds to each particular object identified at step E41 in the polychrome images 22. Thus, the different point sets 21a-21c can be distinctly reproduced by the processor 7 at step E4 (Fig. 3) and a cloud broken into several parts 21a-21c corresponding to several objects can, therefore, be displayed on screen 15. Next, at step E5 (Fig. 3) the processor 7 is configured to establish a correspondence between the point sets 21a-21c resulting from the bursting of the point cloud 21 and the nodes 231a-231c of the tree structure 23 identifying the digital model 17. The correspondence between the point sets 21a-21c and the nodes of the tree structure can be defined by constructing a new tree structure of logical nodes linked to the point cloud and in parallel with that identifying the digital model. Furthermore, the point sets 21a-21c can be advantageously saved in initial files organized according to a tree structure. This allows links to be easily established between these initial files and existing secondary files associated with the predetermined tree structure of the digital model. Figs. 5A-5D illustrate the previous steps concerning equipment installed on board an aircraft. In particular, Fig. 5A illustrates a physical equipment 219 consisting of a set of pipes and cables mounted on board an aircraft. Fig. 5B illustrates a point cloud 211 resulting from the scanning of equipment 219 and representing in monochrome the various pipes and cables of this equipment. Fig. 5C illustrates the breakdown of the point cloud 211 into several sets of points 211a-211e corresponding to the different elements constituting the equipment 219. A first set of points 211a corresponds to a first pipe, a second set 211b corresponds to a fixing rivet, a third set 211c corresponds to a comb or support which holds all the pipes and cables, a fourth set 211d corresponds to a nut and a fifth set 211e corresponds to a second pipe, etc. Fig. 5D illustrates the correspondence between the point sets 211a-211e resulting from the splitting of the point cloud 211 of Fig. 5C and the nodes 231a-231e of the tree structure 223. At step E6 (Fig. 3), the processor 7 is configured to analyze the correspondence between the sets of points and the nodes of the tree structure to evaluate the adequacy or concordance between the point cloud 21 and the digital model 17. This adequacy involves the evaluation of a gap el between each set of points of the point cloud 21 and the part of the model associated with the node corresponding to this set of points. Advantageously, the adequacy is represented by a multicolor digital representation of the point cloud 21 on the digital model 17. More specifically, the digital model 17 is represented in a first color (e.g., red), the point cloud 21 in a second color (e.g., green), and each part of the representation where the difference between the digital model 17 and the point cloud 21 exceeds a predetermined tolerance threshold is represented in a third color (e.g., yellow). Parts of the representation where the difference is less than the predetermined tolerance threshold are represented in the first or second color. For example, the tolerance threshold has a value between approximately 0.5 mm and 5 mm. Note that the differences between the points of the three-dimensional point cloud 21 and the corresponding points of the digital model can be evaluated using a function known in CAD software such as CATIA. Alternatively, the adequacy is represented by a multicolor and nuanced digital montage of the point cloud 21 on the digital model 17. In this case, the digital model 17 is represented in a first color (e.g., red), and the point cloud 21 in a second color (e.g., green). Each part of the montage showing a positive difference between the digital model and the point cloud is represented by a third color (e.g., yellow) but nuanced according to a first chromatic scale proportional to the measured positive difference. Furthermore, each part of the montage showing a negative difference between the digital model and the point cloud is represented by a fourth color (e.g., blue) nuanced according to a second chromatic scale proportional to the absolute value of the measured negative deviation. Figs. 6A-6C schematically illustrate an example of a digital mounting of a three-dimensional point cloud on a corresponding digital model, according to an embodiment of the invention. In particular, Fig. 6A illustrates the digital model 117 of a lavatory bowl intended for installation on board an aircraft. This model is represented monochrome in a first color (e.g., red). Fig. 6B illustrates the three-dimensional point cloud 321 of the equipment (i.e., the bowl) after its manufacture. The point cloud 321 is represented monochrome in a second color different from the first (e.g., green). Finally, Fig. 6C illustrates the superimposition of the three-dimensional point cloud 321 onto the digital model 117 of the bowl. The setup illustrated in Fig. 6C shows that points with a deviation greater than the predetermined tolerance threshold are represented by a third color (e.g., yellow). Furthermore, points with a deviation less than the predetermined tolerance threshold are represented by the same color as that of the point cloud 321 (i.e., green).the second color) while points not belonging to point cloud 321 but belonging to digital model 171 are represented by the same color as the latter (i.e. the first color). Fig. 7 schematically illustrates another example of a digital mounting of a point cloud on a corresponding digital model, according to another embodiment of the invention. This example illustrates the superimposition of a three-dimensional point cloud onto the digital model of a structure in an aircraft containing pipes and cables. Each perfectly superimposed part of the assembly (i.e., with a zero difference) is represented by a first color (e.g., green). Each part of the assembly with a positive difference between the digital model and the point cloud is represented by a second color (e.g., yellow), but shaded according to a first chromatic scale (ranging from 28,000 mm to 50,500 mm) proportional to the measured positive difference. For example, a very light second color signifies a small difference, while A second, very dark color signifies a large discrepancy. Furthermore, each part of the assembly exhibiting a negative discrepancy between the digital model and the point cloud is represented by a third color (for example, blue) shaded according to a second chromatic scale (ranging here from -37,000 mm to -50,500 mm) proportional to the absolute value of the measured negative discrepancy. Thus, a very light third color signifies a small discrepancy, while a very dark third color signifies a large discrepancy. Furthermore, the digital model 17 is advantageously configured to model not only the equipment 19 but also its immediate environment (i.e., the location designated for the physical installation of the equipment). This allows verification of the actual layout of the equipment 19 in relation to its environment before physical installation. Naturally, the same steps as those in Fig. 3 are also applied to the environment, since the latter is part of the digital model 17. In addition, the evaluation of the fit between the point cloud 21 and the digital model 17 also includes verifying the integration of the equipment 19 within its designated environment. Thus, the fit between the point cloud 21 and the digital model 17 also involves evaluating distances (for example, using CATIA software) between the point cloud 21 and the portion of the digital model 17 modeling the equipment's immediate surroundings. Indeed, Fig. 8 illustrates an example of mounting the three-dimensional point cloud 421 of a set of pipes onto a digital model 217 representing the set of pipes in its environment on board an aircraft. This mounting shows a gap el of 9.456 mm between a pipe 421a from the point cloud 421 and the corresponding pipe 217a from the model 217, as well as a distance dl of 29.535 mm between the pipe 421a from the point cloud and part 217b modeling a structural wall of the aircraft. This allows verification that the distance is respected and analysis of the impact of a difference between the theoretical model (3D model) and the actual equipment, given that any friction between the equipment and surrounding elements can cause damage to sealing or insulation, etc. Furthermore, the adequacy between the point cloud 21 and the digital model 17 advantageously involves verifying the correspondence between the sets of points 21a-21c and nodes 231a-231c of the tree structure 23. In particular, processor 7 is configured to check if a node exists for each set of points. This determines whether each object is mounted in its correct position and that there are no mounted objects not included in the digital model. Indeed, a visual and / or audible alert is triggered by an output device 13 if a set of points does not correspond to a node in the digital model's tree structure. Similarly, an alert is also issued in the event that a node in the tree structure 23 of the digital model 17 has no antecedent in the point sets 21a-21c of the point cloud 21. This makes it possible to determine the case where an element represented in the digital model does not exist in the physical equipment. Furthermore, processor 7 is advantageously configured to clean up the point cloud 21 by acting on the nodes of the corresponding tree structure 23. Indeed, any part of the point cloud 21 considered unnecessary by the operator can be eliminated or hidden simply by deleting or masking the node corresponding to that part. The examples given above relate to aircraft applications, but of course, any other application is possible as soon as it is necessary to integrate equipment manufactured outside of an environment into that environment.

Claims

DEMANDS 1. A method for controlling equipment (19) previously modeled by a three-dimensional digital mock-up (17), said digital mock-up being identified by a tree structure (23) of logical nodes, characterized in that said method comprises the following steps: -three-dimensional scanning of the equipment (19), said scanning producing a three-dimensional point cloud (21) representative of said equipment (19), -superposition of said point cloud (21) onto said digital model (17), -coordination between said point cloud (21) and polychrome images (22) captured during the scanning of the equipment, -breakdown of said point cloud (21) into several sets of points (21a-21c) using said coordination, each set of points corresponding to an object identified in the polychrome images, -establishing a correspondence between said sets of points and the nodes (231) of the tree structure (23), and -evaluation of the adequacy between the point cloud (21) and the digital model by analyzing said correspondence between said sets of points and said nodes of the tree structure.

2. A method according to claim 1, characterized in that said digital model (17) is adapted to model said equipment and its environment knowing that the same steps of the method are applied to the environment, and in that the method further comprises a step of verifying the integration of said equipment into its environment according to said suitability.

3. A method according to claim 1 or 2, characterized in that the correspondence between the point cloud (21) and the digital model comprises: -an evaluation of discrepancies (el) between each set of points in the point cloud (21) and the part of the digital model (17) associated with the node corresponding to said set of points, and / or -an evaluation of distances (dl) between the point cloud and the part of the digital model modeling the environment surrounding the equipment.

4. A method according to any one of the preceding claims, characterized in that the coordination between said point cloud (21) and the polychrome images (22) is achieved by synchronizing the polychrome images with the point cloud according to successive capture dates of said polychrome images.

5. A method according to any one of the preceding claims, characterized in that the splitting of the point cloud (21) into several sets of points (21a-21c) comprises the following steps: -identification of objects exhibiting basic physical characteristics in polychrome images, and -subdivision of the point cloud (21) into said sets of points (21a-21c) by associating each set of points with a corresponding object identified in the polychrome images.

6. A method according to any one of the preceding claims, characterized in that the correspondence between said sets of points and the nodes of the tree structure is defined by a construction of a new tree structure of logical nodes linked to the point cloud in parallel with that identifying the digital model.

7. A method according to any one of the preceding claims, characterized in that it comprises issuing an alert if a set of points does not have a corresponding node in the tree structure of the digital model and / or in the case where a node in the tree structure (23) of the digital model (17) has no antecedent in the point sets of the point cloud (21).

8. A method according to any one of the preceding claims, characterized in that it comprises: -a backup of the point sets in initial files organized according to the tree structure, and -establishing links between the aforementioned first files and second files associated with the tree structure of the digital model.

9. A method according to any one of the preceding claims, characterized in that the adequacy is represented by a digital mounting of the point cloud (21) on the digital model (17), the digital model being represented according to a first color, the point cloud being represented according to a second color and each part of the mounting presenting a deviation between the digital model and the point cloud greater than a predetermined tolerance threshold being represented by a third color.

10. A method according to any one of claims 1 to 8, characterized in that the adequacy is represented by a digital montage of the point cloud (21) on the digital model (17), the digital model being represented according to a first color, the point cloud being represented according to a second color, each part of the montage presenting a positive difference between the digital model and the point cloud being represented by a third color shaded according to a first chromatic scale, and each part of the montage presenting a negative difference between the digital model and the point cloud being represented by a fourth color shaded according to a second chromatic scale.

11. Control system for equipment (19) previously modeled by a three-dimensional digital mock-up (17), said digital mock-up being identified by a tree structure (23) of logical nodes, characterized in that said system comprises a scanner configured to produce a three-dimensional point cloud (21) representative of said equipment (19), as well as a processor and memory configured to: -superimpose said point cloud (21) onto said digital model (17), -coordinate said point cloud (21) to polychrome images (22) captured during the scanning of the equipment and stored in a memory, -to split said point cloud (21) into several sets of points (21a-21c), each set of points corresponding to an object identified in the polychrome images, -establish a correspondence between said sets of points and the nodes (231) of the tree structure (23), and -evaluate the suitability between the point cloud (21) and the digital model by analyzing said correspondence between said sets of points and said nodes of the tree structure.

12. Control system according to claim 11, characterized in that said digital model (17) is adapted to model said equipment and its environment, and in that the processor is further configured to verify the integration of said equipment into its environment by evaluating distances (dl) between the point cloud and the part of the digital model modeling the environment near the equipment.

13. Computer program comprising code instructions for implementing the control method according to any one of claims 1 to 10 when executed by a processor.

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