IMPROVED METHOD FOR AUTOMATED DETERMINATION OF THE DEPTH OF A DEFECT DETECTED ON THE SURFACE OF AN OBJECT, AND SYSTEM CONFIGURED TO EXECUTE THE METHOD.

Abstract

The invention relates to a method for the automated inspection of a surface (AS) of a solid object such as, for example, an aircraft surface (AS) (100); the method employing a step of detecting a defect (D) of said surface (AS) represented as a depth map image (S), successive depth profile analyses (DPi) aimed at determining a depth (Pi) for each of said depth profiles (DPi), and then a determination of a "final" depth (P) of a defect from all the depths (Pi) of said profiles. The invention further relates to a system (1) configured to perform the method. Advantageously, it is thus possible to automatically determine the depth of flatness defects in an aircraft surface (AS) (100) with a level of accuracy not yet achieved. Fig. 5

Description

Title of the invention: IMPROVED METHOD FOR AUTOMATED DETERMINATION OF THE DEPTH OF A DEFECT DETECTED ON THE SURFACE OF AN OBJECT, AND SYSTEM CONFIGURED TO EXECUTE THE METHOD. technical field

[0001] The present invention relates to an improved method for the automated determination of the depth of a defect on the surface of an object, which surface is, for example, the surface of an aircraft component; the defect being detected from information previously obtained from a surface inspection device to which a detection method is applied. The invention further relates to a system configured to perform such a method. PREVIOUS STATE OF THE ART

[0002] Automated inspection and quality control methods used in industry often lead to significant time savings in product manufacturing stages. This is particularly advantageous for equipment whose manufacture requires a large number of components and manufacturing steps, where increased production rate is often desired. Surface inspection of aircraft during manufacturing or maintenance operations is common, and there is a need for automated means of inspecting and detecting potential surface defects, enabling a level of perception and detection at least as high as, or even higher than, that of the human eye, for detecting very small surface defects during manufacturing or maintenance operations.

[0003] Although available detection tools and methods reliably detect surface defects on objects, measured values ​​for the depth of a surface defect often vary substantially depending on the tool or method used. Furthermore, when a surface defect is detected next to a surface-arranged feature present in the vicinity of the defect, such as a rivet, the presence of the feature exhibiting a surface variation complicates the determination of the defect depth.

[0004] The situation can be improved. Description of the invention

[0005] An object of the present invention is to increase the measurement accuracy of the depth of a surface defect detected by means of automated inspection. of object surfaces, for example aircraft surfaces, with detection means capable of detecting a surface defect.

[0006] To this end, a method is proposed for determining the depth of a surface defect of an object, said surface being digitally instantiated in the form of a distance map between a measured real surface of said object and a sensor of a surface inspection system configured to obtain said digitally instantiated surface by a scanning operation of said real surface, said method comprising detecting said defect in said surface by delimiting a portion called the "defect zone" of said digitally instantiated surface, said method being characterized in that it further comprises: - (i) a determination of the center of said defect, - (ii) a determination of a plurality of defect depth profiles, each of said depth profiles being respectively established following a path through said defect zone of the digitally instantiated surface along a predetermined straight trajectory passing through said center, each of said depth profiles being further determined with reference to a trajectory different from the trajectory determined for the other profiles among said plurality of profiles, - (iii) a determination of a maximum depth and a confidence index for each of said depth profiles determined, then, - (iv) a determination of said depth of said surface defect from said maximum depths determined and said confidence indices determined with reference to each of said depth profiles.

[0007] Advantageously, and thanks to the proposed method, it is possible to improve the characterization of a surface defect on an object and, where appropriate, to undertake corrective actions. For example, it is possible to optimize maintenance operations or adaptations to the manufacturing methods of the object exhibiting a defect based on the depth of the defect, the latter being able to be determined with a higher level of precision.

[0008] The method according to the invention may further have the following additional characteristics, considered alone or in combination:

[0009] - A determination of the maximum depth of a depth profile according to the The process includes an interpolation operation in the relevant depth profile.

[0010] - Determining the depth of the surface defect from the depths maxima, each determined in reference to a profile, includes a weighted median calculation.

[0011] - The method further includes a step of notifying the presence of said defect detected in said surface.

[0012] Another object of the invention is a method for manufacturing an aircraft component comprising a method for determining the depth of a defect as previously described, and a step for modifying the surface presenting the defect from at least one piece of information representative of the defect.

[0013] The invention also relates to a system for determining the depth of a surface defect of an object, said surface being digitally instantiated in the form of a distance map between a measured real surface of said object and a sensor of a surface inspection system configured to obtain said digitally instantiated surface by a scanning operation of said real surface, said system comprising electronic circuitry configured to detect said defect in said surface by delimiting a portion called the "defect zone" of said digitally instantiated surface, said system further comprising electronic circuitry configured to: - (i) a determination of the center of said defect, - (ii) a determination of a plurality of defect depth profiles, each of said depth profiles being respectively established following a path through said defect zone of the digitally instantiated surface along a predetermined straight trajectory passing through said center, each of said depth profiles being further determined with reference to a trajectory different from the trajectory determined for the other profiles among said plurality of profiles, - (iii) a determination of a maximum depth and a confidence index for each of said depth profiles determined, then, - (iv) a determination of said depth of said surface defect from said maximum depths determined and said confidence indices determined with reference to each of said depth profiles.

[0014] The system according to the invention may further have the following additional characteristics, considered alone or in combination: - The system includes electronic circuitry configured to operate a determination of a maximum depth of a predetermined depth profile, which determination includes an interpolation operation in a determined depth profile. - The system includes electronic circuitry configured to perform a determination of the depth of the surface defect from the maximum depths determined each in reference to a profile, the determination of the depth of the surface defect including a weighted median calculation. - The system includes electronic circuitry configured to operate a notification of the presence of the defect detected in the inspected and analyzed surface.

[0015] Another object of the invention is a computer program product comprising program code instructions to execute steps of a process as previously described when these instructions are executed by a processor of a system for determining the depth of a surface defect of a solid object.

[0016] Finally, an object of the invention is a storage device comprising a computer program product as mentioned above. Brief description of the drawings

[0017] [Fig.1] schematically illustrates an automated inspection system for the condition of a surface of a solid object according to one embodiment;

[0018] [Fig.2] schematically illustrates an aircraft with surfaces that can be inspected using the system shown in [Fig.1];

[0019] [Fig.3] is a schematic representation of a set of information representative of the surface of a solid object and taking the form of a type image of depth map, (or distances) used as input data of the automated inspection system already represented on [Fig.1];

[0020] [Fig.4] is a flowchart illustrating steps of an automated process for determining the depth of a surface defect of a solid object, carried out in the automated inspection system already shown in [Fig.1], according to one embodiment;

[0021] [Fig.5] illustrates details of an overall step in determining the depth of a defect described in relation to [Fig.4];

[0022] [Fig.6] is a diagram illustrating an example of the architecture of a data processing unit comprising electronic circuitry configured to perform the process described in relation to [Fig.4], according to one embodiment;

[0023] [Fig.7] schematically illustrates a defect in a defect detection zone of a digitally instantiated inspected surface, according to one embodiment;

[0024] [Fig.8] illustrates a depth profile of a defect along a determined trajectory and according to an embodiment;

[0025] [Fig.9] illustrates a generalization of a depth profile as already shown in [Fig.8]; and,

[0026] [Fig. 10] illustrates a particular case of a defect depth profile, according to an embodiment, of a nature to cause a specific treatment of this profile.

[0027] DETAILED STATEMENT OF IMPROVEMENTS

[0028] Figure 1 represents an automated inspection system 1 for the condition of a surface AS of a solid object according to one embodiment. The automated inspection system 1 comprises a sensor device 10 connected to a processing unit 12 via a communication link 11. According to one embodiment, the communication link 11 is wired. According to another embodiment, the communication link 11 is configured to operate wirelessly. According to one embodiment, the sensor device 10 is a camera or scanner operating as a distance sensor configured to deliver a set of data of the type "3D point cloud," this data then being representative of the inspected surface AS, or more precisely of the surface condition of the inspected surface AS. The distance sensor device 10 performs distance measurements between a reference point that it includes and a plurality of points on a surface of a solid object.In one embodiment, each point in the 3D point cloud is instantiated as a pair of x and y coordinates considered in combination with a distance value S(x, y) relative to the camera positioned with reference to the normal to the tangent plane to the inspected surface AS within the measurement field of the sensor 10 (camera or scanner, for example). For each inspected area of ​​the surface AS, a 3D point cloud S(x, y) can be transmitted by the sensor device 10 to the processing unit 12 via the communication link 11. This 3D point cloud S(x, y) constitutes initial information representing the shape of the inspected surface AS (also referred to here as the "surface state"). In other words, this 3D point cloud S (x, y) constitutes a depth (or distance) map determining a set of distances for points on the surface AS observed and inspected in the measurement field of the sensor device 10.The processing unit 12 is configured to perform successive processing operations from this initial information, in order to characterize surface defects present in the inspected surface AS, such as dents and reliefs of various shapes and sizes (impacts, scratches, embossments, hollows, etc.).

[0029] [Fig.2] illustrates an example of an inspected surface AS of an aircraft 100. According to the example described in relation to [Fig.2], the surface AS is a surface of a fuselage element of the aircraft 100. Obviously, this example is not limiting and the automated inspection system 1 can be useful for inspecting many surfaces of an aircraft, including in particular the fuselage and the wing.

[0030] Figure 3 schematically illustrates a data structure comprising the aforementioned information, stored in the form of a matrix S of values, each element of which S(X, Y) is determined and stored with reference to X and Y coordinates of a plane. For example, an element S(XI, YI) represents the distance between the sensor device 10 and a point on the surface AS whose The position is determined in space by the coordinates XI and Yl. In one embodiment, the value matrix S further constitutes an image of the distances respectively measured for the different points of the matrix S. For example, the brighter a point in the image is, the greater the distance between the corresponding point on the inspected surface AS and the distance measuring sensor of the sensor device 10, or vice versa. The term "corresponding point on the inspected surface" here refers to a point on the inspected surface AS that is representative of a given point in the image (or matrix) S. Thus, the structuring of the initial information obtained constitutes a 3D to 2D transformation of the inspected surface AS into an image S that can undergo processing by the processing unit 12 in order to detect the presence of any defects in the inspected surface AS.

[0031] Figure 4 describes steps in a method for determining the depth of a surface defect, performed by and in the processing unit 12 of the automated inspection system 1, according to a particular and non-limiting embodiment of the invention.

[0032] A step S0 is an initial (or initialization) step at the end of which all the circuits and elements of the automated inspection system 1 are energized, normally powered, configured, and operational. In particular, the sensor device 10 is positioned on a support or by an operator facing an area of ​​the inspected surface AS, and initial information representing the surface condition of the inspected surface AS is transmitted by the sensor device 10 to the processing unit 12. This initial information constitutes an "image matrix" of the analyzed portion of the surface AS and forms a digital instance of the surface AS, referred to herein as surface S or image matrix S.

[0033] During a defect detection step SI, a blurring (or smoothing) operation is first performed on the matrix (or image) S, which is instantiated by the initial information obtained by the processing unit 12. In one embodiment, the blurring operation applies a blurring radius between 5 mm and 15 mm, preferably with a blurring radius of 10 mm. The resulting matrix or image constitutes new information, representative of the surface AS, in the form of a blurred image matrix. Subsequently, a triple derivation of the blurred image matrix applied to the information obtained from the blurring is performed.The term "triple derivation" here refers to three successive derivation operations applied to the image matrix representing the inspected surface AS (or an area or portion of this surface), using respectively three different derivation operators (first a gradient, then a Hessian matrix, and finally a specific derivation operator).

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[0045] According to one embodiment, the aforementioned triple differentiation, which comprises three successive differentiation operations using three differentiation operators respectively, is decomposed as follows: A first derivation (of the triple derivation) performs a gradient calculation of the inspected surface, which is expressed in the form ^s(x,y) as . dy sx 57 where S(x, y) is the image matrix after blurring obtained at the end of step SI of blurring. A second derivation (of the triple derivation) performs a matrix calculation Hessian, which is expressed in the form: H(x,y) = SXx SXy .Syx Syy WHERE ù S(x,y) ; ù2S(x,y) ; 3 ; and (FS(x,y) , sxx ​​= -^r- sxy - Syy = —^— allowing the determination of local variations in flatness: &(x,y) = S2XX + Sxy Then a third derivation (of the triple derivation) operates a so-called "third-order" derivation, using an operator defining a rate of change of the previously determined local flatness variations, capable of highlighting defects, including very small ones, by inserting the resulting information into a module for detecting possible defects in a subsequent step. The operator defining a rate of change of the previously determined local flatness variations can be expressed as: ' Sxxx 4" Syy • Syyx SXX ' + Syy ' Syyy Finally, the detection of one or more potential defects D present in the inspected surface AS is performed using a defect detection module. In one embodiment, the defect detection module is implemented by the processing unit 12. In another embodiment, the defect detection module is a Va(x, y ) = 2 ■ A YOLO (You Only Look Once) type neural network. This module implements a well-known computer vision algorithm capable of detecting predetermined objects in an image in a single scan (a single "look") by simultaneously performing detection and classification. The YOLO algorithm operates using the image matrix S resulting from three successive derivations after blurring and provides information enabling the identification and localization of any surface defects present via the instantiation of bounding boxes, each with a corresponding The probability of a defect being present in the area delimited by the bounding box of the image matrix resulting from the three derivations. The defect(s) D detected in the image matrix S can therefore be subjected to further processing, independently of each other.

[0046] Obviously, the detection method detailed above is described as an example of an embodiment and other embodiments or variants can be used to detect one or more surface defects of an object, for example via other automated processes or through information obtained via a user interface by an operator analyzing a surface condition using a specific tool for visualizing this surface condition.

[0047] During step S2, the defect(s) D detected in the surface AS are characterized by processing and analyzing the image matrix S to define their dimensions, including the depth of each defect D. For the sake of simplicity in this description, it is assumed for the remainder of this description that only one defect D is detected in the image matrix S and therefore in the surface or portion of surface AS. In reality, several defects could be detected in a surface or portions of surfaces AS. The operations specific to the characterization of the defect D in the surface AS are described in the remainder of this description, in relation to [Fig. 5] and Figures [Fig. 7] to [Fig. 10].

[0048] Once the depth of the defect(s) D has been precisely determined, the presence of the detected defect(s) can be notified, via system 1 or a third-party device, during a step S3. In one embodiment, such notification occurs when the absolute value of the detected defect depth exceeds a predefined threshold value. It is considered here that a depth value can describe a defect such as a dent or a raised feature in the inspected and analyzed surface AS. Thus, a negative depth value indicates the presence of a raised feature. Notification of the presence or severity of a defect advantageously allows for the control or organization of manufacturing process modifications and / or maintenance operations related to the surface or portion of the surface AS.

[0049] Figure 5 illustrates details of operations performed in the aforementioned step S2 in relation to a defect D detected in the surface AS, the depth of which must be determined with high precision. Thus, step S2 is a sequence of substeps S20, S21, and S22 aimed successively and respectively at determining a center of the detected defect D (step S20), then at determining a plurality of depth profiles Pi in a defect zone Z containing the defect D, such as, for example, a bounding box Z instantiated by its coordinates in the image matrix S (step S21) or a more extensive zone Z comprising the area delimited by a bounding box resulting from a defect detection process, and then at determining a depth P, called "final" of the defect D, from depths Pi determined for each of the depth profiles (step S22).

[0050] More specifically, during step S20, a specific method already known is applied to the Z zone to determine the lowest or highest point of the image matrix S in the Z zone, which point is referred to here as the "center" of the defect under consideration. According to one embodiment, the Z zone used extends beyond a bounding box containing a defect D to be analyzed, so as to be able to consider the state of the surface around the defect D for the purpose of subsequent processing (for example, processing such as a numerical interpolation of a surface profile damaged by a defect).

[0051] According to a particular embodiment, the method used for this purpose is a gradient descent algorithm, also commonly called the gradient algorithm, which minimizes a differentiable real-valued function defined in a Euclidean space. The gradient descent algorithm is then applied to the numerically instantiated surface S. It is an iterative algorithm that proceeds by successive improvements. According to the algorithm, at the current point, a displacement is performed in a direction opposite to the gradient, so as to decrease the function. The same principle is applied to find the highest point of a defect by minimizing the opposite of the function. These operations allow the determination of a center C with coordinates Xc, Yc of the defect D in the image matrix S.

[0052] This embodiment is not limiting, and other embodiments can be used to determine the center C of a defect. For example, an evaluation can be performed by an operator working on an enlarged view of a defect area, who then designates, via a digital tool operating on the digitally instantiated surface, the center C of a given defect.

[0053] It is then possible to determine a plurality of straight paths (lines) passing through the center C of the defect D, along which depth profiles DPi are determined in step S21. To understand how these depth profiles DPi are determined, [Fig. 7] illustrates a plurality of lines L1, L2, and L3 used to determine depth profiles DPI, DP2, and DP3, which allow us to determine the local variation in the depth of the defect D during a traverse of each of the lines L1, L2, and L3 in the Z-zone delimiting the defect D. The lines L1, L2, and L3 pass through the center C. Here, the number of lines Li, and therefore the number of depth profiles DPi, is intentionally limited for the sake of simplifying the illustration. However, according to a particular embodiment, many depth profiles DPi are determined, for example, several dozen.According to a particular and non-limiting embodiment, sixty depth profiles are determined along sixty straight lines passing through the center C and oriented so as to present . Each line forms an angle of 3° with respect to its neighboring lines. It is therefore possible to determine distances (or depths, or altitudes) Zpl (absolute or relative) for each point on the line L1 within the Z region of the image matrix S. Similarly, it is possible to determine distances (or depths, or altitudes) Zp2 for each point on the line L2 within the Z region of the image matrix S, and it is possible to determine distances (or depths, or altitudes) Zp3 for each point on the line L3 within the Z region of the image matrix S. These sequences of values ​​constitute profiles DPI, DP2, and DP3 respectively, with reference to the lines L1, L2, and L3. The DPI profile is a sequence of Zpl depth values ​​along the line L1, the DP2 profile is a sequence of Zp2 depth values ​​along the line L2, and so on.More generally, it is possible to determine a DPi profile constituting a sequence of Zpi values ​​along an ith straight line Li crossing the zone Z passing through the center C.

[0054] Figure 8 illustrates an example of a depth profile DPI along the line L1, and Figure 9 illustrates more generally an example of a depth profile DPi along a line Li. Each profile presents a sequence MS of measured values ​​(and therefore of values ​​in the image matrix S), referred to here as the profile portion MS, as well as a sequence of values ​​obtained by interpolating these values, referred to here as the interpolated profile portion IS. Thus, the interpolated profile portion of a profile presupposes what this depth profile would be if determined in the absence of surface defects. The maximum depth difference between the MS portion and the IS portion, in the direction of the normal, is the depth of the profile under consideration.

[0055] Thus, in [Fig. 7], PI is the depth of the defect D along (or according to) the profile DPI, and in [Fig. 9], Pi is the depth of the defect D along (or according to) the profile DPi. It should also be noted that a depth profile can exhibit several successive variations in slope (change of sign of the derivative), indicating the presence of a particular relief. An example of a depth profile DPj illustrates in [Fig. 10] two adjacent cavities of respective depths Pj and P'j along a profile determined along a straight line Lj. Such a profile DPj can originate from the singular shape of a defect or from the presence of any element near that defect.

[0056] Returning to step S21 in relation to [Fig.5], and once the profiles DPI, DP2 and DP3 have been determined, the respective depths PI, P2 and P3 of these profiles are determined by numerical analysis so that in step S22 a "final" value P of the depth of the defect D can be determined from all the depths of the profiles DPI, DP2 and DP3.

[0057] According to one embodiment, a weighted median calculation is used to determine the so-called "final" depth P of the defect D from the respective depths PI, P2 and P3 of the profiles DPI, DP2 and DP3.

[0058] According to one embodiment, weightings can be introduced in the form of confidence indices k assigned to the different depth profiles determined. For example, when a depth profile exhibits variations that suggest the presence of two very close defects, or of an object or element (for example, a rivet) in the immediate vicinity of a defect, as illustrated in relation to [Fig. 10], a weighting factor or reduced confidence index k (for example, k = 0.05) is assigned to the depth profile concerned (and therefore to the depth value determined in relation to this profile) so as to reduce its weight in the calculation of the weighted median. In the absence of such a feature in a given profile, a nominal value is assigned to the confidence index k associated with the profile (for example, k = 1).

[0059] Once the depth P of the defect D has been determined, the subsequent, possibly conditional, treatments of step S3 are carried out.

[0060] According to one embodiment, when an iterative gradient descent algorithm is used in step S20 to determine what the center C of a defect D to be analyzed is, i.e. the lowest point or the highest point of the surface of a surface defect of an object, steps S21 and S22, respectively of determining a plurality of depth profiles of the defect and of determining a maximum depth and a confidence index for each of the depth profiles determined, then, of determining the depth of the surface defect from the maximum depths determined and the confidence indices determined with reference to each of the depth profiles, are carried out for each of the iterations of the iterative gradient descent algorithm.

[0061] According to another embodiment, the center C of a defect D to be analyzed is initially determined at step S20 as being the center of a bounding box delimiting an area including the defect D at the end of a detection process, then sequences of steps S21 and S22 are repeated successively by determining, for each new iteration, a center C corrected from the point determined as being the lowest or the highest at the end of the previous iteration of a sequence of steps S21 and S22, and this until a maximum value of depth or relief is obtained.

[0062] Advantageously and cleverly, the use of a plurality of depth profiles, along rectilinear trajectories each oriented differently in the area of ​​a defect, makes it possible to identify and distinguish depth profile orientations according to which a single defect (hollow or bump) appears in the profile compared to other depth profile orientations according to which several surface variations (hollows or bumps) appear in the profile. Such a distinction advantageously allows these two types of profiles to be considered in different ways (for example by establishing weightings) and ultimately to eliminate disturbances in a depth (or relief) measurement, coming from elements normally present in the vicinity of an analyzed defect (for example a rivet, a junction between two neighboring surface elements, etc.).

[0063] Fig. 6 schematically illustrates an example of the internal architecture of the processing unit 12 of the automated inspection system 1, configured to perform the process described above.

[0064] According to the hardware architecture example shown in [Fig.6], the processing unit 12 then comprises, connected by a communication bus 129: a processor or CPU (“Central Processing Unit”) 121; a RAM (“Random Access Memory”) 122; a ROM (“Read Only Memory”) 123; a storage unit such as a hard disk drive (or a storage media reader, such as an SD card reader (“Secure Digital”) 124; a communication interface module 125 enabling the processing unit 12 to communicate with remote devices such as a surface inspection device or devices at manufacturing or maintenance sites.

[0065] The processor 121 of the processing unit 12 is capable of executing instructions loaded into the RAM 122 from the ROM 123, external memory (not shown), a storage medium (such as an SD card), or a communication network. When the processing unit 12 is powered on, the processor 121 is capable of reading instructions from the RAM 122 and executing them. These instructions form a computer program causing the processor 121 of the processing unit 12 to implement all or part of an automated inspection process as previously described.

[0066] All or part of such an automated surface inspection method, for example for aircraft surfaces, can then be implemented in software form by executing a set of instructions by a programmable machine, for example a DSP (Digital Signal Processor) or a microcontroller, or be implemented in hardware form by a dedicated machine or component, for example an FPGA (Field-Programmable Gate Array) or an ASIC (Application-Specific Integrated Circuit). In general, the processing unit 12 includes electronic circuitry configured to implement an automated inspection method for the surfaces of solid objects. Obviously, the processing unit 12 also includes all the elements usually present in a system comprising a control unit and its peripherals, such as a power supply circuit, a circuit power monitoring, one or more clock circuits, a reset circuit, input / output ports, interrupt inputs, bus drivers, this list is not exhaustive.

Claims

Demands

1. A method for determining the depth (P) of a surface defect (D) (AS) of an object (100), said surface being digitally instantiated as a distance map (S) between a measured actual surface (AS) of said object and a sensor of a surface inspection system (10) configured to obtain said digitally instantiated surface (S) by a scanning operation of said actual surface (AS), said method comprising detecting said defect (D) in said surface (S) by delimiting a portion called the "defect zone" (Z) of said digitally instantiated surface (S), said method being characterized in that it further comprises: - (i) determining a center (C) of said defect (D), - (ii) determining (S2) a plurality of depth profiles (DPi) of the defect (D),each of said depth profiles being respectively established following a path through said defect zone (Z) of the digitally instantiated surface along a predetermined rectilinear trajectory (Li) passing through said center (C), each of said depth profiles (DPi) being further determined with reference to a trajectory different from the trajectory determined for the other profiles among said plurality of profiles, - (iii) a determination (S3) of a maximum depth (Pi) and a confidence index (k) for each of said depth profiles (DPi) determined, then, - (iv) a determination of said depth (P) of said surface defect (D) from said maximum depths (Pi) determined and said confidence indices (k) determined with reference to each of said depth profiles (DPi).

2. A method according to claim 1, wherein a determination of said maximum depth of a depth profile comprises an interpolation operation in said depth profile.

3. A method according to any one of claims 1 and 2, wherein said determination of said depth of said surface defect from said maximum depths each determined with reference to a profile includes a weighted median calculation.

4. A method according to any one of claims 1 to 3, further comprising a step of notifying the presence of said defect detected in said surface.

5. A method for manufacturing an aircraft component comprising a method for determining the depth of a defect according to any one of claims 1 to 4, and a step for modifying said surface from at least one representative piece of information of said defect.

6. A system for determining the depth of a surface defect of an object, said surface being digitally instantiated as a distance map between a measured real surface of said object and a sensor of a surface inspection system configured to obtain said digitally instantiated surface by a scanning operation of said real surface, said system comprising electronic circuitry configured to detect said defect in said surface by delimiting a portion called the "defect zone" of said digitally instantiated surface, said system being characterized in that it further comprises electronic circuitry configured to: - (i) determine the center of said defect by applying a gradient descent algorithm to said defect zone of said digitally instantiated surface, - (ii) determine a plurality of defect depth profiles,each of said depth profiles being respectively established following a path through said defect zone of the digitally instantiated surface along a predetermined straight trajectory passing through said center, each of said depth profiles being further determined with reference to a trajectory different from the trajectory determined for the other profiles among said plurality of profiles, - (iii) a determination of a maximum depth and a confidence index for each of said depth profiles determined, then, - (iv) a determination of said depth of said surface defect from said maximum depths, determined and said confidence indices determined with reference to each of said depth profiles.

7. System according to claim 6, the system further comprising electronic circuitry configured to perform a determination of a maximum depth of a predetermined depth profile comprising an interpolation operation in a determined depth profile.

8. System according to any one of claims 6 and 7, the system further comprising electronic circuitry configured to perform a determination of said depth of said surface defect from said maximum depths each determined with reference to a profile, said determination of said depth of said surface defect comprising a weighted median calculation.

9. System according to any one of claims 6 to 8, further comprising electronic circuitry configured to operate a notification of the presence of said defect detected in said surface.

10. Product computer program comprising program code instructions for executing steps of a process according to any one of claims 1 to 5 when said instructions are executed by a processor of a system for determining the depth of a surface defect of a solid object.

11. Storage device comprising a computer program product according to claim 10.

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