Evaluation Method and System for Scanning Imaging Performance of Coplanar Capacitive Sensors

Abstract

This invention relates to a method and system for evaluating the scanning imaging performance of a coplanar capacitance sensor, belonging to the field of coplanar capacitance sensors, and solves the problem that evaluating the scanning imaging performance of coplanar capacitance sensors in the prior art requires a large amount of time. The method for evaluating the scanning imaging performance of a coplanar capacitance sensor according to this invention includes: acquiring a sensitivity distribution map of the target sensor on a surface layer at a preset detection depth; extracting high-sensitivity concentrated areas from the sensitivity distribution map of the surface layer as a meta-image; and evaluating the scanning imaging performance of the target sensor on the surface layer based on the meta-image. The meta-image proposed in this invention can reflect the correlation between the coplanar capacitance sensor and the reconstructed image quality at the corresponding detection depth. Directly evaluating the scanning imaging performance of the coplanar capacitance sensor based on the meta-image can save time and improve evaluation efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coplanar capacitive sensor, and in particular to a method and system for evaluating the scanning imaging performance of a coplanar capacitive sensor. BACKGROUND

[0002] The coplanar capacitive sensor (CCS) is a new type of dielectric detection sensor emerging in recent years, which has the advantages of low cost, high sensitivity, non-invasive and non-destructive. In 2006, Diamond first introduced the CCS scanning technology into the field of non-destructive testing, and realized the damage scanning imaging of materials such as organic glass, carbon fiber and concrete by using a pair of rectangular electrodes. The CCS scanning imaging technology has shown extensive research value and application potential in the fields of composite material detection, corrosion under insulation, moisture detection, surface detection and concrete detection.

[0003] The coplanar capacitive sensor includes a coplanar array capacitive sensor and a single electrode pair coplanar capacitive sensor. The coplanar array capacitive sensor increases the observation area and obtains more measurement data by arranging multiple electrodes, and the single electrode pair coplanar capacitive sensor scans the measured object in two-dimensional sequence to obtain measurement data. At present, due to the complexity of the probe boundary conditions and the edge electric field of the coplanar capacitive sensor, the electric field soft field effect has not been accurately analyzed. There is no correlation model between the coplanar capacitive sensor and the quality of its scanning reconstruction image in the prior art, and the evaluation of the scanning imaging performance of the coplanar capacitive sensor depends on the final scanning imaging results obtained by finite element simulation or experiment. However, the final scanning imaging results obtained by finite element simulation or experiment require a large amount of time. SUMMARY

[0004] In view of the above analysis, the embodiments of the present application aim to provide a method and system for evaluating the scanning imaging performance of a coplanar capacitive sensor, so as to solve the technical problem that a large amount of time is required to evaluate the scanning imaging performance of the coplanar capacitive sensor in the prior art.

[0005] In one aspect, the embodiments of the present application provide a method for evaluating the scanning imaging performance of a coplanar capacitive sensor, which comprises:

[0006] obtaining a sensitivity distribution map of a target sensor on a surface layer at a preset detection depth;

[0007] extracting a high-sensitivity concentrated area in the sensitivity distribution map of the surface layer as a meta-image;

[0008] evaluating the scanning imaging performance of the target sensor on the surface layer according to the meta-image.

[0009] Based on the further improvement of the above method, the high sensitivity concentrated area in the sensitivity distribution map of the surface layer is extracted as a meta image, comprising:

[0010] The high sensitivity concentrated area in the sensitivity distribution map of the surface layer is extracted as a meta image by Otsu method.

[0011] Based on the further improvement of the above method, the high sensitivity concentrated area in the sensitivity distribution map of the surface layer is extracted by Otsu method, comprising the following steps:

[0012] The number of each sensitivity value in the sensitivity distribution map is counted;

[0013] The probability distribution of each sensitivity value in the whole sensitivity distribution map is calculated;

[0014] The threshold value under the maximum inter-class variance is calculated according to the objective function;

[0015] According to the threshold value, the sensitivity distribution map is image segmented to extract the high sensitivity concentrated area.

[0016] Based on the further improvement of the above method, the sensitivity distribution of the target sensor on the surface layer at the preset detection depth is obtained, comprising the following steps:

[0017] The measurement domain of the target sensor is divided into finite element grid in three-dimensional space;

[0018] The sensitivity matrix of the measurement domain of the target sensor in three-dimensional space is obtained based on the finite element analysis method;

[0019] The sensitivity distribution map on the surface layer at the preset detection depth is extracted from the sensitivity matrix.

[0020] Based on the further improvement of the above method, the sensitivity matrix is calculated according to the following formula:

[0021]

[0022] In the formula, S is the sensitivity matrix; is the potential distribution of the measurement domain when the first electrode is excited and the second electrode is grounded; is the potential distribution of the measurement domain when the second electrode is excited and the first electrode is grounded; V1 is the voltage when the first electrode is excited; V2 is the voltage when the second electrode is excited; I, J and K are the total number of division of the measurement domain in x direction, y direction and z direction, respectively, and i, j and k are the coordinates of the solving unit in x direction, y direction and z direction, respectively;

[0023] The first electrode and the second electrode are two electrodes in an electrode pair of the target sensor respectively; the z direction is a detection depth direction, the x direction and the y direction are two directions perpendicular to the z direction, and the x, y and z satisfy the right-hand rule.

[0024] Based on the further improvement of the above method, the scanning imaging performance of the target sensor on the surface layer is evaluated according to the area of the meta image.

[0025] The scanning imaging performance of the target sensor on the surface layer is evaluated according to the area of the meta image.

[0026] Based on the further improvement of the above method, the scanning imaging performance of the target sensor on the surface layer is evaluated according to the area of the meta image.

[0027] The smaller the area of the meta image is, the better the scanning imaging performance of the target sensor on the surface layer is.

[0028] Based on the further improvement of the above method, the method further comprises:

[0029] The scanning interval of the coplanar capacitive sensor in scanning imaging is set according to the size of the meta image.

[0030] Based on the further improvement of the above method, the scanning interval of the coplanar capacitive sensor in scanning imaging is set according to the size of the meta image.

[0031] When the coplanar capacitive sensor scans the measured object along a preset direction, the scanning interval in the preset direction is smaller than the size of the meta image along the preset direction.

[0032] In another aspect, an embodiment of the present application provides a scanning imaging performance evaluation system of a coplanar capacitive sensor, the system comprising:

[0033] A sensitivity distribution map acquisition module is configured to acquire a sensitivity distribution map of a target sensor on a surface layer at a preset detection depth;

[0034] An extraction module is configured to extract a high-sensitivity concentrated area in the sensitivity distribution map of the surface layer as a meta image, so as to establish an association model between the target sensor and the reconstructed image quality of the target sensor at the detection depth; and

[0035] An evaluation module is configured to evaluate the scanning imaging performance of the target sensor on the surface layer according to the meta image.

[0036] Based on the further improvement of the above system, the extraction module extracts the high-sensitivity concentrated area in the sensitivity distribution map of the surface layer by using the Otsu method.

[0037] Compared with the prior art, the present application can achieve at least one of the following beneficial effects:

[0038] 1、 The meta image provided by the present application can reflect the correlation between the coplanar capacitive sensor and the reconstructed image quality at the corresponding detection depth, thereby providing a basis for the scanning imaging performance evaluation and optimized design of the coplanar capacitive sensor.

[0039] 2、 In the present application, the scanning imaging performance of the coplanar capacitive sensor is evaluated directly according to the meta image, without the need to obtain the final scanning imaging result through finite element simulation or experiment, thereby being able to save time and improve the evaluation efficiency.

[0040] 3、 The Otsu algorithm is used to extract the meta image from the sensitivity distribution image, which is simple in calculation and fast in speed, and can effectively perform threshold segmentation on the sensitivity distribution image.

[0041] In the present application, the above technical solutions can be combined with each other to achieve more preferred combination schemes. Other features and advantages of the present application will be described in the subsequent specification, and some advantages will become apparent from the specification or be understood through the implementation of the present application. The purposes and other advantages of the present application can be achieved and obtained through the contents specifically indicated in the specification and the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0042] The accompanying drawings are included to provide a further understanding of the present application and are incorporated in and constitute a part of this specification, illustrate embodiments of the present application and together with the description serve to explain the principles of the present application. In the drawings:

[0043] Figure 1 Flow chart of the modeling method for the scanning imaging of the coplanar capacitive sensor of the embodiment of the present application;

[0044] Figure 2 Schematic diagram of the finite element grid division of the measurement domain of the coplanar capacitive sensor of the embodiment of the present application;

[0045] Figure 3a Sensitivity distribution schematic diagram of certain four different detection depth surface layers of the coplanar capacitive sensor of the embodiment of the present application;

[0046] Figure 3b Schematic diagram of the meta image of certain four different detection depth surface layers of the coplanar capacitive sensor in the embodiment of the present application;

[0047] Figure 4 Schematic diagram of the relationship between the meta image size, the scanning pitch and the reconstructed image quality in the embodiment of the present application;

[0048] Figure 5This is a schematic diagram showing the structure, meta-image, and imaging results of four different coplanar capacitive sensors in an embodiment of the present invention, as well as the scanning results of the same object under test.

[0049] Figure label:

[0050] 10 - Coplanar capacitance sensor; 20 - Measurement domain; 30 - Sensitivity distribution map; 40 - Meta-image;

[0051] 50 - The object being tested;

[0052] 101 - Third sensor; 102 - Fourth sensor; 103 - Fifth sensor;

[0053] 104 - Sixth sensor;

[0054] 401 - First-dimensional image; 402 - Second-dimensional image; 403 - Third-dimensional image;

[0055] 404 - Fourth Element Image. Detailed Implementation

[0056] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0057] like Figure 1 As shown in the figure, this embodiment of the invention provides a method for evaluating the scanning imaging performance of a coplanar capacitance sensor. The method includes:

[0058] Step 1: Obtain the sensitivity distribution map 30 of the target sensor on the surface layer at the preset detection depth;

[0059] Step 2: Extract the high-sensitivity concentrated region from the sensitivity distribution map 30 of the surface layer as the meta-image 40;

[0060] Step 3: Evaluate the scanning imaging performance of the target sensor on the surface layer based on the meta-image 40.

[0061] Compared with existing technologies, the meta-image proposed in this invention can reflect the correlation between the coplanar capacitance sensor 10 and the quality of its reconstructed image at the corresponding detection depth, providing a basis for the evaluation and optimization design of the scanning imaging performance of the coplanar capacitance sensor 10. In this invention, the scanning imaging performance of the coplanar capacitance sensor 10 is directly evaluated based on the meta-image 40, without the need to obtain its final scanning imaging results through finite element simulation or experiments, thereby saving time and improving evaluation efficiency.

[0062] The sensitivity matrix (Jacobi matrix) of the measurement domain 20 of the coplanar capacitive sensor 10 is generally considered as an inherent property of the sensor and does not change with the change of the medium distribution of the measurement domain 20 as an approximate linear mapping of the output capacitance signal and the medium distribution of the measurement domain 20. Thus, the scanning reconstructed image of the coplanar capacitive sensor 10 can be considered as being superimposed with the sensitivity matrix of the coplanar capacitive sensor 10 in a certain scanning interval and manner. In a figurative way, the size and the writing strength of a brush determine the details and the level of the picture that can be drawn by the brush. Therefore, the sensitivity matrix as the "brush" of the scanning image determines the scanning image quality to a certain extent. In fact, the distribution of the sensitivity matrix of the sensor is uneven. Research shows that the elements with high sensitivity values in the matrix are generally concentrated in the adjacent edge region, which plays a decisive role in the output signal. Therefore, in the embodiment of the present application, the high-sensitivity concentrated region in the sensitivity matrix is regarded as a basic unit of scanning imaging, and is defined as a meta-image 40, so as to evaluate the scanning imaging performance of the coplanar capacitive sensor 10.

[0063] In the present application, the scanning imaging performance of the coplanar capacitive sensor 10 is evaluated according to the meta-image 40, that is, the quality of the reconstructed image that can be obtained by the coplanar capacitive sensor 10 is evaluated according to the meta-image 40. The imaging performance of the target sensor at the detection depth, that is, the imaging performance of the target sensor when the measured object 50 is at the detection depth.

[0064] It should be noted that in the embodiment of the present application, the coplanar capacitive sensor 10 is generally a single-electrode coplanar capacitive sensor 10, as shown in FIG. 3, which obtains a reconstructed image by scanning the measured object 50.

[0065] In step 2, the high-sensitivity concentrated region in the sensitivity distribution map 30 in the surface layer is extracted by a threshold method. The threshold method includes a fixed threshold method, an adaptive threshold method, and an Otsu method, and the Otsu method is preferred.

[0066] In one embodiment, in step 2, the high-sensitivity concentrated region in the sensitivity distribution map 30 in the surface layer is extracted by the Otsu method.

[0067] The Otsu algorithm, also known as the maximum inter-class variance method, is an algorithm for determining the threshold value of image binarization segmentation, and is currently considered as the best method for solving the global threshold value of an image. The basic principle is to divide the pixel points in the image into C1 and C2 two classes according to the threshold T, and after adjusting the threshold T, if there is the largest inter-class variance between the two classes at this time, then this threshold is the best threshold.

[0068] Specifically, the high-sensitivity concentrated region in the sensitivity distribution map 30 of the surface layer is extracted by the Otsu method, including the following steps:

[0069] Step 201: count the number of each sensitivity value in the sensitivity distribution map;

[0070] Step 202: calculate the probability distribution of each sensitivity value in the entire sensitivity distribution map 30;

[0071] Step 203: calculate the threshold under the maximum inter-class variance according to the objective function;

[0072] Step 204: image segmentation of the sensitivity distribution map 30 according to the threshold, and extract the high sensitivity centralized area.

[0073] In the embodiment of the present application, the Otsu algorithm is used to extract the meta-image 40 from the sensitivity distribution map 30, which is simple and fast in calculation, and can effectively perform threshold segmentation on the sensitivity distribution map 30.

[0074] Further, in the Otsu algorithm, the objective function in step 203 is:

[0075]

[0076] In the formula, is the inter-class variance; w0 and w1 are the ratios of the number of sensitivity values of the two classes separated by the threshold to the total number, satisfying w0+w1=1; M0 and M1 are the average values of the sensitivity values of the two classes.

[0077] In one embodiment, the sensitivity distribution of the target sensor on the surface layer at the preset detection depth is obtained by the following steps:

[0078] Step 101: finite element meshing is performed on the measurement domain 20 of the target sensor in three-dimensional space.

[0079] Step 102: the sensitivity matrix of the measurement domain 20 of the target sensor in three-dimensional space is obtained based on the finite element analysis method.

[0080] Step 103: the sensitivity distribution map 30 on the surface layer at the preset detection depth is extracted from the sensitivity matrix.

[0081] In the embodiment, the sensitivity matrix of the measurement domain 20 of the target sensor in three-dimensional space is obtained based on the finite element analysis method, so that the sensitivity distribution map 30 on the surface layer at each detection depth can be obtained.

[0082] In step 102, the sensitivity matrix is calculated according to the following formula:

[0083]

[0084] In the formula, S is the sensitivity matrix; a potential distribution of the measurement domain 20 when the first electrode is excited and the second electrode is grounded; a potential distribution of the measurement domain 20 when the second electrode is excited and the first electrode is grounded; V1 is a voltage when the first electrode is excited; V2 is a voltage when the second electrode is excited; I, J and K are respectively total numbers of divisions of the measurement domain 20 in x direction, y direction and z direction, i, j and k are respectively coordinates of the solving unit in x direction, y direction and z direction.

[0085] wherein the first electrode and the second electrode are respectively two electrodes in an electrode pair of the target sensor; the z direction is a detection depth direction, the x direction and the y direction are two directions perpendicular to the z direction, and x, y and z satisfy the right-hand rule.

[0086] Hereinafter, a co-planar capacitive sensor 10 with one rectangular electrode is taken as an example for illustration.

[0087] Figure 2 A measurement domain 20 of a co-planar capacitive sensor 10 is shown in FIG. 2, and the measurement domain 20 is meshed by finite elements to solve a sensitivity matrix in three-dimensional space. After obtaining the sensitivity matrix, a sensitivity distribution map 30 on a surface layer at different detection depths can be obtained as required, for example Figure 3a The sensitivity distribution maps 30 of four surface layers at different detection depths of the co-planar capacitive sensor 10 are shown in FIG. 3. Then, the high-sensitivity concentrated regions of the four surface layers are extracted by using the Otsu method to obtain corresponding meta images 40, as shown in FIG. 4. Figure 3b Further, the scanning imaging performance of the sensor at different detection depths can be evaluated according to the meta images 40 of the surface layers.

[0088] In one embodiment, step 3: evaluating the scanning imaging performance of the target sensor on the surface layer according to the area of the meta image 40.

[0089] Specifically, in step 3, the smaller the area of the meta image 40, the better the scanning imaging performance of the target sensor on the surface layer.

[0090] On the contrary, the larger the area of the meta image 40, the worse the scanning imaging performance of the target sensor on the surface layer.

[0091] As shown in FIG. 5, the larger the area of the meta image 40, the worse the scanning imaging performance of the sensor. Figure 3b

[0092] In addition, it should be noted that other features of the meta image 40, such as shape, also have an impact on the imaging performance of the co-planar capacitive sensor 10.

[0093] ​The method further comprises: step 4: setting a scanning interval of the coplanar capacitive sensor 10 during scanning imaging according to the size of the meta-image 40.

[0094] Specifically, when the coplanar capacitive sensor 10 scans the measured object 50 along a preset direction, the scanning interval in the preset direction is smaller than the size of the meta-image 40 along the preset direction.

[0095] For example, when the coplanar capacitive sensor 10 scans and images, scanning is performed in a row-column manner, and the distance between two rows or two columns is referred to as a scanning interval. The smaller the scanning interval, the higher the scanning accuracy.

[0096] The size of the meta-image 40 along the row direction is defined as l x , and the size of the meta-image 40 along the column direction is defined as l y ; the distance between two columns during scanning imaging of the coplanar capacitive sensor 10 is defined as a column scanning interval s x , and the distance between two rows is defined as a row scanning interval s y . The size of the meta-image 40 and the scanning interval should satisfy: s x =k×l x , s y =k×l y , and 0 x k<1. For example, k can take values of 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, etc.

[0097] The basic principle of scanning imaging and the relationship between the size of the meta-image 40, the scanning interval, and the quality of the reconstructed image will be described below. Figure 4 The pixel value of the reconstructed image of the coplanar capacitive sensor 10 depends on the size of the output capacitance value of the scanning point, which is simplified as the overlapping area between the meta-image 40 and the target in Figure 4 .

[0098] As shown in Figure 4 , the measured object 50 is placed in the scanning area, and two coplanar capacitive sensors 10, such as a first sensor and a second sensor, are used to scan the measured object 50. For ease of description, it is assumed that the meta-image 40 of each sensor is circular, and the row scanning interval is equal to the column scanning interval during scanning of the two sensors, i.e., s x =s y . The diameter of the meta-image 40 of the first sensor is r1, and s x =s y =0.5r1, s x =s y =r1, and s x =s yThe object 50 was scanned with a scanning interval of 1.5r1, and the resulting reconstructed images were T11, T12, and T13. The primitive image 40 of the second sensor has a diameter of r2, where r2 < r1, and was scanned using s... x =s y =0.5r², s x =s y =r2 and s x =s y The object under test 50 was scanned with a scanning interval of 1.5r2, and the resulting reconstructed images were T21, T22 and T23.

[0099] according to Figure 5 It can be seen that the quality of the reconstructed image is related to the size of the meta-image 40 and the scanning interval. A smaller meta-image 40 and scanning interval produce a better quality reconstructed image. Compared to the object 50, the smaller the meta-image 40, the more accurate the quantitative features of the target are obtained.

[0100] On the other hand, embodiments of the present invention provide a scanning imaging performance evaluation system for a coplanar capacitance sensor. The system includes: a sensitivity distribution map acquisition module, an extraction module, and an evaluation module. The sensitivity distribution map acquisition module acquires a sensitivity distribution map 30 of the target sensor on a surface layer at a preset detection depth; the extraction module extracts high-sensitivity concentrated areas from the sensitivity distribution map 30 of the surface layer as a meta-image 40; and the evaluation module evaluates the scanning imaging performance of the target sensor on the surface layer based on the meta-image 40.

[0101] Preferably, the extraction module extracts the high-sensitivity concentrated region in the sensitivity distribution map 30 of the surface layer as the meta-image using the Otsu method.

[0102] Example I

[0103] In this embodiment, the imaging results of four coplanar capacitive sensors with different structures scanning the same object are compared to illustrate the feasibility of using the meta-images obtained by the scanning imaging performance evaluation method and system of the present invention to evaluate the scanning imaging performance of coplanar capacitive sensors.

[0104] In this embodiment, all four coplanar capacitance sensors 10 are single-electrode pair coplanar capacitance sensors 10, such as... Figure 5 As shown, the four coplanar capacitive sensors 10 are the third sensor 101, the fourth sensor 102, the fifth sensor 103, and the sixth sensor 104. The electrode of the third sensor 101 is rectangular, while the electrodes of the other three sensors are triangles of different sizes. Figure 5The first sub-image 401, the second sub-image 402, the third sub-image 403 and the fourth sub-image 404 corresponding to the four sensors respectively are shown below the four sensors, and the imaging results T31, T32, T33 and T34 are also shown.

[0105] According to Figure 5 It can be seen that the area of the sub-image of the third sensor 101 is the largest, and the stretching and artifact problem of the reconstructed image thereof is more serious; while the area of the sub-image of the sixth sensor 104 is the smallest, and the quality of the reconstructed image thereof is the best. The result verifies the feasibility of directly evaluating the scanning image quality by using the sub-image model of the coplanar capacitive sensor, and provides a practical basis for the imaging performance evaluation and optimal design of the coplanar capacitive sensor.

[0106] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiments can be completed by a computer program instructing relevant hardware, and the program can be stored in a computer readable storage medium. The computer readable storage medium includes a magnetic disk, an optical disk, a read-only memory, a random access memory, etc.

[0107] The above description is only the preferred embodiment of the present application, but the protection scope of the present application is not limited to this. Any changes or replacements within the technical scope disclosed by the present application can be easily thought by those skilled in the art, and should be covered within the protection scope of the present application.

Claims

1. A method of evaluating the scanning imaging performance of a co-planar capacitive sensor, characterized in that, The method comprises: obtaining a sensitivity distribution map of a target sensor on a surface layer at different preset detection depths; counting the number of each sensitivity value in the sensitivity distribution map; calculating the probability distribution of each sensitivity value in the entire sensitivity distribution map; extracting a high-sensitivity concentrated area in the sensitivity distribution map of the surface layer as a meta-image by Otsu method; evaluating the scanning imaging performance of the target sensor on the surface layer according to the area of the meta-image; setting the scanning interval of the coplanar capacitive sensor during scanning imaging according to the size of the meta-image.

2. The method of claim 1, wherein, The extraction of the high-sensitivity concentrated area in the sensitivity distribution map of the surface layer by Otsu method comprises the following steps: calculating the threshold value under the maximum inter-class variance according to the objective function; performing image segmentation on the sensitivity distribution map according to the threshold value to extract the high-sensitivity concentrated area.

3. The method of evaluating scanning imaging performance according to claim 1 or 2, characterized by, The obtaining of the sensitivity distribution of the target sensor on the surface layer at different preset detection depths comprises the following steps: performing finite element grid division on the measurement domain of the target sensor in three-dimensional space; obtaining the sensitivity matrix of the measurement domain of the target sensor in three-dimensional space based on the finite element analysis method; extracting the sensitivity distribution map on the surface layer at different preset detection depths from the sensitivity matrix.

4. The method of claim 3, wherein, The sensitivity matrix is calculated according to the following formula: where S is a sensitivity matrix; a potential distribution of the measurement field when the first electrode is excited and the second electrode is grounded; a potential distribution of the measurement field when the second electrode is excited and the first electrode is grounded; V1 is a voltage when the first electrode is excited; V2 is a voltage when the second electrode is excited; I, J and K are respectively total numbers of divisions of the measurement field in x direction, y direction and z direction, i, j and k are respectively coordinates of the solving unit in x direction, y direction and z direction; wherein the first electrode and the second electrode are two electrodes in an electrode pair of the target sensor; the z direction is the detection depth direction, the x direction and the y direction are two directions perpendicular to the z direction, and x, y and z satisfy the right-hand rule.

5. The method of evaluating scanning imaging performance according to claim 1 or 2, characterized by, The evaluation of the scanning imaging performance of the target sensor on the surface layer according to the area of the meta-image comprises: The smaller the area of the meta-image, the better the scanning imaging performance of the target sensor on the surface layer.

6. The method of claim 1, wherein, The setting of the scanning interval of the coplanar capacitive sensor during scanning imaging according to the size of the meta-image comprises: When the coplanar capacitive sensor scans the measured object along a preset direction, the scanning interval in the preset direction is smaller than the size of the meta-image along the preset direction.

7. A system for evaluating the scanning imaging performance of a co-planar capacitive sensor, characterized by The system comprises: a sensitivity distribution map acquisition module for obtaining a sensitivity distribution map of a target sensor on a surface layer at different preset detection depths; an extraction module for counting the number of each sensitivity value in the sensitivity distribution map, calculating the probability distribution of each sensitivity value in the entire sensitivity distribution map, extracting a high-sensitivity concentrated area in the sensitivity distribution map of the surface layer as a meta-image by Otsu method, and establishing a correlation model between the target sensor and the reconstructed image quality thereof at the detection depth; and an evaluation module for evaluating the scanning imaging performance of the target sensor on the surface layer according to the area of the meta-image, and setting the scanning interval of the coplanar capacitive sensor during scanning imaging according to the size of the meta-image.

Images