Mapping method for monitoring the state of and / or geolocating a buried, half-buried or submerged structure, and associated geolocation method

Abstract

The invention relates to a mapping method for monitoring the state of and / or geolocating a buried, half-buried or submerged structure, as well as to an associated geolocation method, such that, according to the invention, the mapping method comprises a step of scanning a zone to be monitored, a step of acquiring magnetic field data and position data by means of the magnetometers associated with position sensors, a step of processing the measurements from the acquisition step in order to correct the data according to environmental parameters during the data acquisition step and a step of generating an interactive magnetic data map that allows an operator to remove, add and / or modify one or more surfaces directly on the interactive magnetic data map.

Description

[0001] DESCRIPTION

[0002] Title: Mapping method for monitoring the condition and / or geolocation of a buried, semi-buried or submerged structure and associated geolocation method

[0003] Technical field

[0004] The present invention relates to a mapping method for monitoring the condition and / or geolocation of a buried, semi-buried or submerged structure. The present invention will find its main application for the three-dimensional geolocation of pipes or pipelines for the transfer of liquids or gases.

[0005] However, the present invention may also be used for the detection and geolocation of other types of structures or for broader geophysical purposes. In addition, the invention may also advantageously be used for the external control of structures in order to remotely determine the state of a buried or semi-buried structure.

[0006] Prior art

[0007] Geolocation of buried structures is a well-known and widely documented challenge for network operators. Updating the geolocation of a structure is particularly important, particularly to enable excavation work to be carried out near it, or to verify the integrity of a structure.

[0008] The geolocation of a structure is made necessary by various factors including a lack of precision when installing the structure, poor recording of the structure's position, loss of archives or even ground movements, causing the structure to move.

[0009] To carry out this geolocation, we know of prospecting devices using different technologies such as radio detection, radar, lidar, or even techniques based on the measurement of magnetic fields.

[0010] These devices physically consist of vehicles such as trolleys, measuring rods or even drones, equipped with sensors, they make it possible to provide, with varying degrees of precision or errors, the geolocation of the structure. Each technique has usage constraints and limits, particularly with regard to the vertical or horizontal precision of the geolocation of the structure.

[0011] Generally speaking, these devices allow the generation, from the measurements taken by the sensors and a geolocation system, of a set of geolocation points of the structure allowing the creation of a 2D or 3D geolocation map. A first disadvantage of these devices is that they do not allow the resolution of geolocation problems in the case of the presence of several nearby structures and for example when pipelines are close together or even locally overlap. The presence of several structures in particular can thus lead to aberrations in the generation of the geolocation map which are sources of errors for the operator.

[0012] A second disadvantage of these devices is that the quality of the measurements varies depending on the terrain, the environment or even the signature of the structure which is not constant.

[0013] For example, the measurement of magnetometers can be distorted by the presence of metallic or magnetic objects other than the structure and locally modifying the magnetic field.

[0014] This variation in the accuracy of the measurements affects the accuracy of the geolocation map of the structure in places without the user knowing which parts of the map are possibly less accurate or imperfect.

[0015] The present invention aims to overcome the aforementioned drawbacks in the field of geolocation using magnetometers. It thus constitutes an improvement to geolocation techniques using magnetic fields from a vehicle equipped with magnetometers. It should be remembered that this geolocation technique using magnetometers is based on the precise magnetic mapping of the surface which overhangs the source of a potential magnetic field other than that of the Earth, called a magnetic anomaly field.

[0016] This mapping of magnetic anomalies allows, from a physical model, based on the nature of the measured source, to infer the position of the source from the emitted magnetic signal. This source can be either magnetic (magnetization) or electromagnetic, for example, by injecting an electric current into the source using a current generator.

[0017] Subject of the invention

[0018] A first aim of the present invention is to resolve all or part of the technical problems linked to the aforementioned prior art.

[0019] Another aim of the present invention is to propose a mapping method making it possible to propose an interactive map of magnetic data which can be modified manually to improve the quality of the geolocation of a structure.

[0020] Another object of the present invention is to propose a mapping method making it possible to propose an interactive map of magnetic data making it possible to visualize at least two separate structures in order to generate a location map of at least one of the structures. Another object of the present invention is to propose a mapping method proposing an interactive map of magnetic data making it possible to distinguish several zones so as to generate a location map with different levels of precision or resolution.

[0021] Summary of the invention

[0022] The invention aims to protect a mapping method for monitoring the condition and / or locating a buried, semi-buried or submerged structure comprising a metallic or magnetic material in which the following steps are carried out using a vehicle equipped with magnetometers:

[0023] - a step of scanning an area to be controlled,

[0024] - a step of acquiring magnetic field and position data by magnetometers associated with position sensors,

[0025] - a step of processing the measurements from the acquisition step to correct the data according to environmental parameters during data acquisition,

[0026] - a step of generating an interactive map of magnetic data allowing an operator to delete, add and / or modify one or more surfaces directly on the interactive map of magnetic data.

[0027] The present invention further aims to protect a method for locating a buried, semi-buried or submerged structure comprising a metallic or magnetic material in which the following are produced, from the interactive map of magnetic data obtained by the mapping method as mentioned above:

[0028] - a manual optimization step to delete, add or modify at least one zone directly on the interactive map of magnetic data,

[0029] - a step of generating a location map of the structure by using the modified interactive map of magnetic data and at least one model linking the magnetic field of a structure to its spatial position.

[0030] Description of figures

[0031] The present invention will be better understood by reading a detailed example of embodiment with reference to the appended figures, provided by way of non-limiting example, among which

[0032] [Fig.l]

[0033] Figure 1 represents an example of a schematic embodiment of a device according to the invention, in perspective view, [Fig.2] Figure 2 represents a schematic view of the electronic card for implementing the method according to the invention,

[0034] [Fig.3]

[0035] Figure 3 represents an example of the implementation of the scanning and magnetic data acquisition steps in top view,

[0036] [Fig.4]

[0037] Figure 4 represents the example embodiment of Figure 3 in sectional view,

[0038] [Fig.5]

[0039] Figure 5 represents an example of a vehicle trajectory over an area to be controlled in graphic form, [Fig.6]

[0040] Figure 6 shows an example of unfiltered magnetic data measurements versus time in graphical form,

[0041] [Fig.7]

[0042] Figure 7 shows an example of fusion between magnetic data and position data for each profile,

[0043] [Fig.8]

[0044] Figure 8 shows three examples of interactive magnetic data maps,

[0045] [Fig.9a] [Fig.9b] [Fig.9c]

[0046] Figures 9a, 9b and 9c represent respectively an interactive map of the magnetic data including an anomaly A, this same interactive map with the deletion of the data relating to the anomaly and a new interactive map of the magnetic data corrected for anomaly A, [Fig.10]

[0047] Figure 10 shows an example of a geolocation map with resolution indication by area, obtained from the modified interactive magnetic data map.

[0048] Detailed description

[0049] The present invention aims to protect a mapping method for monitoring the condition and / or locating a buried, semi-buried or submerged structure.

[0050] Referring to Figure 1, we see an exemplary embodiment of a drone 1 equipped with sensors 2. In other embodiments, another type of vehicle known to those skilled in the art may be used as a tool for carrying out prospecting and control and in particular a trolley mounted on wheels or tracks, motorized or not. In the exemplary embodiment of Figure 1, the sensors 2 are sensors of the following types: positioning sensors 3 with at least one remote sensing sensor, a GNSS position sensor, an inertial unit comprising a gyroscope and an accelerometer, and magnetic sensors 4 for measuring the magnetic field.

[0051] The positioning sensors 3 record the movements of the drone 1 and allow the acquisition of the positions of the drone 1 during the scanning step of the area to be inspected, while the magnetic sensors 4 allow the acquisition of magnetic field data. These magnetic sensors 4 are advantageously arranged by being spaced horizontally by 5 to 15 cm depending on the vehicle. The arrangement and number of magnetic sensors 4 make it possible to record the magnetic environment of the pipeline to be inspected in the three directions of space.

[0052] All the positioning and magnetic field measurement data are collected and processed by an electronic card as shown in Figure 2 with an analog-digital conversion step for the measurements and data synchronization.

[0053] According to the mapping method, a scanning step is first carried out over an area to be controlled. In the rest of the application, the term "area" will be understood to mean the geographical area(s) scanned by the vehicle. This step also makes it possible to carry out, at the same time, the step of acquiring magnetic field and position data by magnetometers associated with position sensors.

[0054] Different possibilities for scanning the area to be controlled are possible, the choice by the operator is made according to the type of mapping expected and whether or not he has prior knowledge of the positioning of the structure to be controlled.

[0055] Referring to Figure 3, we see an example of an advantageous embodiment of a path of a drone 1 scanning the surface directly above the structure to be geolocated. In this example, a so-called profile scan is carried out; this scan makes it possible to produce a dense and complete map of the magnetic anomaly generated by a buried source.

[0056] In Figure 3, the inspection area is shown by dotted lines, the thin line corresponds to the path of drone 1 while the thick line represents the structure to be inspected. The drone's path is substantially centered on the structure and follows a route allowing magnetic recording along surface strips substantially parallel to the structure.

[0057] The scanning step is thus carried out by successive parallel strips substantially in the main axis of the structure, the width of each strip depending on the spacing between the magnetic field sensors and the resolution to be obtained, the width of the scanned area depending on the vertical distance between the magnetic field sensors and the center of the structure. A set of conditions links the different parameters cited in Fig. 3. The minimum inspection zone is centered on the structure to be inspected. Its half-width is a function of l, corresponding to the distance between the acquisition plane and the center of the structure to be detected. The width between each profile b is a function of the width of the measuring bar used and the desired resolution for the magnetic card.

[0058] In another embodiment, the scanning step will consist of a so-called traverse scan. This type of scanning can be used in particular before the so-called profile scan in order to pre-locate the structure more quickly in a large search area. In this mode, the width of the traverses carried out by the drone 1 must be greater than the width of the minimum inspection zone 2a. The distance between two traverses depends on the desired density of points per meter.

[0059] During the scanning step, the method performs the step of acquiring magnetic field and position data. This step can be performed on all or part of the route followed by the drone 1 during scanning and makes it possible to record the data necessary for mapping.

[0060] The method then consists of carrying out a step of processing the measurements from the acquisition step to correct the data according to environmental parameters during data acquisition.

[0061] Data processing may include various steps to correct position data, magnetic data, or to enable frequency filtering based on disturbing emissions in certain frequencies during data acquisition. These steps are carried out after data acquisition by the drone 1.

[0062] The processing may further include processing prior to data acquisition, namely calibration to compensate for magnetic sources linked to the vehicle. The calibration protocol for magnetic sensors is advantageously carried out before or after a series of measurements. The purpose of calibration is to calculate the errors intrinsic to triaxial magnetometers in order to compensate for them and allow a more precise measurement of the standard. There are 9 errors to be determined, including the sensitivity S (si, S2, S3), the non-orthogonality of the coil axes (angles ui, U2, us) and the bias / offset O = (01, 02, 03) for each of the 3 components (Fi, F2, F3) of the measured magnetic field. The relationship linking the output of the sensors F = (Fi, F^Fs), the measured magnetic field, and B = (Bi, 62,63) the real magnetic field corresponds to:

[0063] F = S x P x B + O

[0064] With

[0065] If 0 0

[0066] S = [ 0 s20 ] 0 0 s3 1 0 p — [— siniii cosiii sinu2sinu3

[0067] Donc

[0068] B = P- 1 x S -1 X (F - O)

[0069] From this definition of the real magnetic field, it is sufficient to find the parameter nonuplet that minimizes the difference between the measured magnetic field intensity and that of the real magnetic field. The calibration step makes it possible to compensate for magnetic sources due to the measurement vector (batteries, structure, etc.). The protocol consists of rotating the vector carrying the magnetometers in all directions of space on a point where the magnetic field intensity is quasi-constant. To do this, the calibration step involves moving the vehicle in several directions of space while recording measurements of a substantially constant magnetic field to modify the acquisition parameters so as to minimize the difference between the real magnetic field intensity and the intensity measured by the magnetometers.

[0070] The data processing step also includes, once the position data has been acquired, advantageously a step of correcting the navigation data.

[0071] This step of correcting the navigation data is carried out by correcting the position recorded by the drone on the one hand and on the other hand by correcting the attitude measurement of the latter. Advantageously, the method uses, for the position correction, a method of correcting the position of a moving vehicle and in particular of a drone 1 from a fixed base. For this purpose, a base is placed on a reliably known position, it is this base which sends the necessary corrections by radio to the processing means, the data being able to be transmitted in real time.

[0072] To obtain reliable measurements, it is also important to make corrections to the data based on the attitude of the drone 1. For this purpose, the use of the inertial unit is planned for monitoring the rotational and translational movements of the drone on itself. The attitude correction makes it possible to match the magnetic vectors (Bx, By, Bz) of the magnetometers with the unique terrestrial magnetic reference frame called NED, north (north), east (east), down (down). This attitude correction includes on the one hand an estimation of the attitude by the gyroscope of the inertial unit and on the other hand a correction by the accelerometer of the inertial unit. The gyroscope attitude estimations make it possible to judge rapid movements.

[0073] The gyroscope can be represented by this quaternion: S w = [Ow x w y w z] The variation in orientation of the gyroscope relative to the Earth's reference frame results in:

[0074] EV = -2EV®S W

[0075] We can write that the derivative of the quaternion over time describing the change in orientation of the gyroscope with respect to the NED frame of reference representing the attitude of one of our machines is: where "est, t — 1" is the estimate of the previous rotation.

[0076] These estimates are considered accurate on short time scales. However, gyroscopic data diverge slightly over time, and this affects the calculations, even with the removal of sensor biases. The accelerometer is used to obtain a better attitude by compensating for the gyroscopic time drift.

[0077] A stabilizing term is added, calculated based on the current quaternion, the measured and corrected acceleration, the average of the magnetic data, and the values ​​of Earth's gravity and magnetic field determined by the GNSS coordinates of the inspected location. This vector is the gradient of the function that calculates the difference between the measurements placed in the reference frame corresponding to the quaternion and the expected values. A small multiple of this vector is therefore removed so that the quaternion is modified towards the starting quaternion. Then, the quaternion is updated using the gradient method, with this product of the attitude quaternion and that of the gyroscopic vector multiplied by the time step.

[0078] Figure 5 represents an example of position measurements after processing in graphic form, we thus see represented five substantially parallel profiles corresponding to the movement of the drone 1 The horizontal sections at the bottom and top of figure 5 correspond to the anonymized GNSS antenna data of latitude in ordinate and longitude in abscissa. Let us recall that the GNSS system makes it possible to determine the position and speed of a point on the surface or in the vicinity of the Earth, by processing the radio signals coming from several artificial satellites, received at this point.

[0079] According to an advantageous characteristic of the invention, the data processing step further comprises a frequency filtering step. This filtering step is useful in the event of disturbance of a frequency by the environment; filtering the frequency or frequency range makes it possible to eliminate the disturbance and to keep the measurements in the frequencies most suited to the detection and location of the structure. Another advantage of this filtering is the possibility of focusing only on an interval of the spectrum to highlight a frequency range. According to a non-limiting embodiment, a filtfilt type filtering is used, applied to the Euclidean norm of the components of each magnetometer; this type of filtering comprises a first filtering, an inversion of the signal, a second filtering and a new inversion. The digital filtering is zero phase.

[0080] The calculation of the coefficients used for filtering is carried out by a digital filtering algorithm with finite duration impulse response.

[0081] Advantageously, the filters are configured according to the following configurations: Bandpass: applied to one or more frequency ranges of interest. This can be the injection frequency or a detectable frequency, isolated and carried by the structure inspected (eg 50 / 60 Hz or one of its harmonics).

[0082] For single frequencies or frequency ranges to isolate the two cutoff frequencies f ci and f C 2 are equal to ±1 Hz of the frequency or interval of interest and of order 1000;

[0083] Low pass: cutoff frequency f c = 2 Hz and of order 1000;

[0084] 1000th order band rejector (Notch) for 50 Hz and its harmonics.

[0085] Figure 6 shows an example of magnetic data measurements after processing in graphical form. This is data after processing, according to a Euclidean norm of the three components of each magnetic sensor (in nT) as a function of time (in seconds) and then with bandpass filtering of each magnetic sensor as a function of time.

[0086] From the measurement processing step of the acquisition step to correct the data according to environmental parameters during data acquisition, the mapping method comprises a step of generating an interactive map of the magnetic data. This interactive map of the magnetic data allows an operator to delete, add and / or modify one or more surfaces directly on the interactive map of the magnetic data. In the step of generating the interactive map of the magnetic data, the processing means merge the position data as represented in Figure 5 with the magnetic data as represented in Figure 6.

[0087] To perform the fusion, the position data are linearly interpolated at the same frequency as the magnetic data, and advantageously at 2000 Hz, so that each magnetic data item is linked to a spatial position.

[0088] The parallel profiles are then selected by pruning the transitions, i.e. the paths to move from one profile to another and represented in Figure 5 by the substantially horizontal parts. The positions of each sensor are deduced relative to the antenna taking into account the geometry of the sensor bar, the chosen inter-sensor spacing and the direction of travel. Referring this time to Figure 7, we find in graphical form the fusion of the data and the correspondence between the position data and the magnetic data. This is data in Euclidean form of the magnetic sensors (in nT) on the central profile (#3), as a function of time (in s). To constitute the interactive map of the magnetic data, we apply a modeling algorithm advantageously of the Gridfit type developed on Matlab.This type of algorithm allows to model a surface from the merged data in the form of z = (x, y) as represented in figure 7. However, other surface modeling algorithms are also possible to obtain the interactive magnetic map. Other programming languages ​​such as Python can also be used to model the surface.

[0089] We thus obtain, by referring this time to Figure 8, an interactive map of the magnetic data which can be analyzed and modified by the operator. Different types of processing allow the obtaining of interactive maps according to the needs of the operator. Thus, in Figure 8 we find from left to right three examples of magnetic maps, relating to a single recording, with respectively a map obtained according to a normalized mode of the signal, a map obtained with a norm centered on the median, and a third interactive map of the magnetic data obtained with a filtered norm.

[0090] According to the invention, the generated interactive magnetic data map can be modified by an operator. This feature allows the operator to replace the magnetic data of at least one selected surface with simulated data obtained by interpolation from the data in the vicinity of the selected surface, ensuring data continuity on the interactive magnetic data map.

[0091] The generation of an interactive map of magnetic data is particularly interesting because it allows an operator to visually analyze the magnetic data which, in a number of cases, present errors or anomalies not only impossible to detect on a structure location map but which modify the calculation of the real position of the structure and distort the structure location map.

[0092] The generation of the interactive magnetic data map also allows the operator to identify sources of errors or phenomena of interest in the vicinity of the pipeline that may or may not threaten the integrity of the pipeline. Once the analysis has been carried out by the operator, the latter can correct or eliminate these errors, or even evaluate the accuracy of certain surfaces, which considerably improves the quality of the location map that can be produced from the interactive magnetic data map.

[0093] Referring to Figures 9a, 9b and 9c, we see respectively represented an interactive map of the magnetic data including an anomaly A (Figure 9a), this same interactive map with the deletion of the data relating to anomaly A (Figure 9b) and a new interactive map of the magnetic data corrected for anomaly A (Figure 9c).

[0094] In Figure 9a, this is typically the signature of an anomaly due to a high-frequency disturbance from a current generator. Indeed, if the detection of metal structures is facilitated when a current is injected at the level of the latter, there is, at the injection point, a magnetic anomaly generated by the current generator and the transmission cables to the structure.

[0095] When the injection point is located in the location search area, the measurement of the magnetic field around the injection point does not correspond solely to the magnetic response of the structure but includes a component linked to the signal injection device. Ordinarily, a location map is generated without correction of the magnetic anomaly, which induces errors in locating the structure in the area around the injection point. The present invention makes it possible to overcome this drawback; thus, from the interactive magnetic data map, the person skilled in the art can identify this anomaly on the interactive magnetic data map and correct it.

[0096] We can see by referring to figure 9b that the surface of the interactive magnetic data map corresponding to the anomaly marked A has been removed.

[0097] To ensure continuity of data on the interactive map of magnetic data, according to the invention, the step of generating an interactive map of magnetic data makes it possible to replace the magnetic data of at least one deleted surface with simulated data obtained by interpolation from the data near the deleted surface.

[0098] Referring this time to Figure 9c, we see that the simulated data allow the junction to be made at the level of the deleted surface. According to a first embodiment, the simulated data are obtained by linear interpolation. However, other types of interpolation are also possible, including cubic interpolation.

[0099] The modified interactive magnetic data map shown in Figure 9c will then be used to produce the location map of the structure.

[0100] It is interesting to note that, according to an advantageous embodiment, each surface modification generates the creation of a new interactive map of the magnetic data. All or part of the interactive maps is stored in a memory comprising the data common to the interactive maps and for each modified interactive map the simulated data of each modified surface.

[0101] Thus, in this embodiment, the interactive map of magnetic data shown in Figure 9a and the data attached to it are stored in a memory, as well as the new interactive map shown in Figure 9c and the simulated data of the modified surface. In another embodiment, only the modified interactive map corresponding to Figure 9c can be stored, the simulated data overwriting the original data relating to the surface of the anomaly deleted by the operator in the memory.

[0102] In another embodiment, a map of type 9c is not produced and the modified interactive map is simply the interactive map in which the data are deleted as shown in Figure 9b. In this case, the calculation of the simulated data will only take place to allow the transition to the location map so that the latter does not present an undetermined surface. Advantageously, the simulated surfaces of the location map may present a distinctive element and in particular a particular color.

[0103] Many types of anomaly, such as the example of an anomaly due to disturbances linked to an injection point, can also be analyzed and treated.

[0104] The processing may consist of deleting the surface identified as containing an anomaly, it may also consist, in addition to or in replacement of the deletion of a surface, of indicating on the interactive map precision levels. The precision levels will be indicated by the operator according to the magnetic data or GNSS positioning performance from the precision level associated with each frame of the GNSS signal, the type and density of the anomalies detected.

[0105] For example, anomalies caused by the presence of several structures can be detected and processed on the interactive magnetic data map by the operator. A typical case is the existence of two pipelines close to each other, i.e. at a distance of less than ten meters. In this case, the monitoring and location of one pipeline is disrupted by the presence of the other pipeline. The second pipeline creates a magnetic disturbance that interacts with the magnetic signal of the pipeline of interest. The measured magnetic signal is therefore the result of the signals from each pipeline and their mutual interaction. Without generating an interactive data map, it is not possible to take into account, let alone decorrelate, the contribution of each pipeline in the resulting signal.The location of the first pipeline is therefore distorted; in general, it is shifted towards the second pipeline, which impacts geolocation performance. The generation of the interactive map allows the operator to identify successions of quasi-parallel magnetic traces that interact with each other. Once the pipeline to be followed has been identified, it is possible to at least partially remove the magnetic data specific to the second pipeline. The operator can also assign a lower resolution level on the interactive map for the areas of the map corresponding to the coexistence of the two pipelines.

[0106] This type of anomaly, due to the presence of a structure, is also present in the case of geolocation of a pipeline using an injected current. Indeed, given the state of the pipelines, they may have electrical insulation defects. It is therefore common that in the event of an electrical insulation defect, the current injected into the pipeline of interest is partially dispersed onto a second pipeline or, more generally, onto a second nearby structure. In this case, the magnetic data acquired by the magnetic sensors have a component corresponding to the current dispersed in the second pipeline, which, in the case of generating a direct geolocation map, leads to location errors.From the interactive map of magnetic data, the operator is again able to remove the magnetic data corresponding to the dispersion, this data appearing in the form of magnetic points of lower intensity compared to the signal coming from the first pipe. The interactive map generation step thus makes it possible to generate a modified interactive map which then allows the production of an improved geolocation map.

[0107] Another type of anomaly that can be noted is the presence of buried or visible point ferromagnetic objects, these objects leave a visible signature on the interactive map with finished magnetic surfaces close to the magnetic surface corresponding to the structure. Here again the operator can modify the interactive map of magnetic data to optimize the geolocation map, by deleting the corresponding surfaces. He can also, in particular, in case of doubt about the analysis of the interactive map, indicate lower levels of precision for the corresponding surfaces, which will generate a differentiated precision display of the location of the structure on the geolocation map.

[0108] On this subject, referring to Figure 10, we see a geolocation map of a pipeline with a bend. This map advantageously includes the site identification elements and includes an upper banner in grayscale. The different grayscales correspond to the display of the accuracy of the positioning of the structure. In particular, the lightest gradient on the right may indicate a geolocation accuracy of less than 10 cm, the central gradient may indicate an accuracy of between 10 and 40 cm and the gradient on the left an accuracy greater than 40 cm.

[0109] Of course, other types of display are also possible, notably by directly indicating, per surface, the numerical value of the positioning precision as assessed by the operator.

[0110] The geolocation method obtained by the mapping method thus comprises a first optimization step for deleting, adding or modifying at least one zone directly on the interactive magnetic map and a second step for generating a geolocation map of the structure by using the modified interactive magnetic map and a model linking the magnetic field of a structure to its spatial position. Furthermore, advantageously the geolocation method comprises, as described above, a step for identifying the level of resolution of at least one surface of the interactive map of the magnetic data and a step for generating a geolocation map with a display of the precision of the geolocation of the structure from the interactive magnetic map and a model linking the magnetic field of a structure to its spatial position.

[0111] Advantageously, the models used for the transition from the modified interactive map to the geolocation map use 2D algorithms such as Least Squares, Powell or Tikhonov or even 3D algorithms such as sphere search.

[0112] Of course, other features of the invention could also have been envisaged without departing from the scope of the invention defined by the claims below. As an example, in an alternative embodiment, the optimization step for deleting, adding or modifying at least one surface directly on the interactive map of the magnetic data could be carried out automatically using processing using artificial intelligence.

Claims

DEMANDS 1. Mapping method for monitoring the condition and / or geolocating a buried, semi-buried or submerged structure comprising a metallic or magnetic material, characterized in that the following steps are carried out from a vehicle equipped with magnetometers: - a step involving scanning an area to be controlled, - a step involving the acquisition of magnetic field and position data by magnetometers associated with position sensors, - a processing step of the measurements from the acquisition step to correct the data according to environmental parameters during data acquisition, - a step of generating an interactive magnetic map of magnetic data allowing an operator to delete, add and / or modify one or more surfaces directly on the interactive magnetic data map.

2. Mapping method according to claim 1 wherein the scanning step is carried out by successive parallel bands substantially in the main area of ​​the structure, the width of each band depending on the spacing between the magnetic field sensors and the resolution to be obtained, the width of the scanned area depending on the vertical distance between the magnetic field sensors and the center of the structure.

3. Mapping method according to either of claims 1 and 2 wherein the processing step includes a preliminary calibration step to compensate for magnetic sources related to the vehicle, said step comprising moving the vehicle in several directions in space while recording measurements of a substantially constant magnetic field to modify the acquisition parameters so as to minimize the difference between the intensity of the actual magnetic field and the intensity measured by the magnetometers.

4. Mapping method according to any one of claims 1 to 3 wherein the processing step includes a navigation data correction step and / or a magnetic data compensation step and / or a frequency filtering step.

5. Mapping method according to any of the preceding claims, wherein a current injection step is carried out at the structure level during the magnetic field data acquisition step.

6. A mapping method according to any one of the preceding claims, wherein the step of generating the interactive magnetic map of the magnetic data allows the magnetic data of at least one selected surface to be replaced by data Simulated data obtained by interpolation from data near the selected surface ensures data continuity on the interactive magnetic data map. A mapping method according to claim 6, wherein the interpolation for calculating the simulated data is linear or cubic interpolation. A mapping method according to either of claims 6 and 7, wherein each surface modification generates a new interactive magnetic data map, all or part of the interactive maps being stored in a memory containing the data common to the interactive maps and, for each modified interactive magnetic data map, the simulated data of each modified surface.Method for geolocating a buried, semi-buried or submerged structure comprising a metallic or magnetic material, in which magnetic data is obtained from the interactive map by the mapping method according to any one of the preceding claims:. - an optimization step to delete, add or modify at least one surface directly on the interactive magnetic data map, - a step of generating a geolocation map of the structure using the modified interactive map and a model linking the magnetic field of a structure to its spatial position. A geolocation method according to the preceding claim 9, wherein the optimization step comprises modifying at least one area of ​​the interactive map of magnetic data corresponding to measurement and / or processing anomalies. A geolocation method according to either of claims 9 and 10 comprising: - a step to identify the level of accuracy of at least one area of ​​the interactive magnetic data map, - a step of generating a geolocation map with a display of the accuracy of the geolocation of the work from the interactive magnetic map and a model linking the magnetic field of a work to its spatial position.

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