Material distribution pattern detection method and device based on array type interdigital capacitors

Abstract

The invention relates to a material distribution pattern detection method and device based on array interdigital capacitors, and the method comprises the steps: determining the area coverage rate of a target material and a capacitance mapping relation coefficient of the capacitance variation of at least one interdigital capacitor unit; measuring the capacitance of each point on at least one interdigital capacitor unit, and determining an influence coefficient matrix of the material placed at the capacitance of each point; obtaining a capacitance matrix of each row and column coordinate in the target full array, and determining a material coverage rate on at least one interdigital capacitor unit according to the capacitance matrix and a preset material distribution matrix; and detecting the distribution pattern of the material, and processing the material coverage rate to generate a continuous material distribution map of the material. Therefore, the problems that in the related technology, single-point measurement can only reflect local material level information and cannot capture non-uniform distribution on the surface of the material, fluctuation of the dielectric constant of the material can remarkably affect the capacitance value, consequently, measurement errors are caused, and a single-point sensor is difficult to track complex form changes in real time are solved.

Description

Technical Field

[0001] The present application relates to the field of capacitive sensor measurement technology, and in particular to a material distribution morphology detection method and device based on array-type interdigital capacitance. Background Art

[0002] Real-time monitoring of material level (such as powder accumulation height and liquid level) and surface shape is a key technology for ensuring production safety, optimizing process flows, and ensuring process control. Traditional level measurement methods include mechanical (such as weight detection), ultrasonic, radar, and capacitive. Capacitive sensors are widely used due to their non-contact, simple structure, and low cost. However, existing capacitive level measurement technology still has significant limitations, especially in terms of measurement accuracy and applicability for complex material shapes.

[0003] In related technologies, capacitive sensors mostly use a single-point or single-pole plate structure, which indirectly reflects the measured material concentration (or material proportion) by detecting changes in capacitance values. For example, by combining the equivalent dielectric constant model of different oil-water mixed media, the relationship between the water content of the oil and the dielectric constant of the mixed oil is established. The relationship between capacitance and dielectric constant is used to calculate the formula between the water content of the oil and the total capacitance value of the detected interdigital capacitors, and the water content of the oil is obtained by the total capacitance value of the detected interdigital capacitors. For example, based on the capacitance information of the corresponding surface in the box collected by the capacitive sensor, the snow cover inside the box and the snow cover on the solar panel are determined. For example, based on the capacitance change relationship corresponding to the material at different material level heights, a capacitive measurement system is constructed.

[0004] However, in related technologies, single-point measurement can only reflect local material level information and cannot capture the uneven distribution of the material surface (such as slopes, depressions or arches formed by accumulation in non-fluid silos). Fluctuations in the dielectric constant of the material (such as humidity changes and composition differences) will significantly affect the capacitance value, resulting in measurement errors. For rapidly changing material levels (such as high-speed flow or discharge scenarios), single-point sensors are difficult to track complex morphological changes in real time, and improvement is urgently needed. Summary of the Invention

[0005] The present application provides a material distribution morphology detection method and device based on array-type interdigital capacitance to solve the problems in related technologies, such as single-point measurement can only reflect local material level information and cannot capture the non-uniform distribution of the material surface. Fluctuations in the dielectric constant of the material will significantly affect the capacitance value, resulting in measurement errors. For rapidly changing material levels, single-point sensors are difficult to track complex morphological changes in real time.

[0006] The first aspect of the present application provides a material distribution morphology detection method based on array-type interdigital capacitors, wherein an array-type interdigital capacitor is set on a target material, and the array-type interdigital capacitor is composed of at least one interdigital capacitor unit, wherein the method includes the following steps: based on the capacitance value of the target material and the at least one interdigital capacitor unit, determining the capacitance mapping relationship coefficient of the area coverage of the target material and the capacitance change of the at least one interdigital capacitor unit; based on the capacitance mapping relationship coefficient, placing materials with the same area coverage on the at least one interdigital capacitor unit in sequence, and measuring the capacitance of each point on the at least one interdigital capacitor unit, calculating the influence coefficient of the capacitance of each point, and determining the influence coefficient matrix of the material placed at the capacitance of each point based on the influence coefficient and a preset influence matrix; based on the influence coefficient matrix, obtaining the capacitance matrix of each row and column coordinate in the target full array by full array scanning, and determining the material coverage on the at least one interdigital capacitor unit according to the capacitance matrix and the preset material distribution matrix; detecting the distribution morphology of the material, and processing the material coverage according to the distribution morphology to generate a continuous material distribution map of the material.

[0007] Optionally, in one embodiment of the present application, an orthogonal wiring architecture and a multiplexer are set on the array-type interdigital capacitor, and the orthogonal wiring architecture includes a row bus group and a column bus group, the input end of the multiplexer is connected to the target controller, and the output end of the multiplexer is connected to the row bus group and the column bus group, wherein the method further includes: activating a single row bus in the row bus group to traverse each column bus in the column bus group according to the single row bus, generate a column bus traversal result, and measure the capacitance value of each point capacitor according to the column bus traversal result; or, activating a single column bus in the column bus group to traverse each row bus in the row bus group according to the single column bus, generate a row bus traversal result, and measure the capacitance value of each point capacitor according to the row bus traversal result.

[0008] Optionally, in one embodiment of the present application, the preset influence matrix is:

[0009]

[0010] in, Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j) and the capacitance at position (m,n) The ratio of

[0011] The influence coefficient matrix is:

[0012]

[0013] in, Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j) and the capacitance at position (m,n) ratio.

[0014] Optionally, in one embodiment of the present application, the capacitor matrix is:

[0015]

[0016] Among them, k C is the capacitance coefficient, is the material area coverage A at position (i, j) i,j ∈[0%,100%] and capacitance change ΔC i,j The capacitance mapping ratio, i.e. k C =ΔC i,j / A i,j , Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j) and the capacitance at position (m,n) The ratio of [x 1,1 ,…,x M,N ] T is the material distribution matrix to be determined, x i,j is the area coverage of the material to be determined at position (i, j), [C 1,1 ,…,C M,N ] T In order to obtain the capacitance matrix of each row and column coordinate unit through the full array scanning, C i,j is the actual measured capacitance value at position (i, j).

[0017] Optionally, in one embodiment of the present application, determining the capacitance mapping relationship coefficient between the area coverage of the target material and the capacitance change of the at least one interdigitated capacitance unit includes: measuring at least one area coverage calibration point of the target material to generate a measurement result, and calculating a weighted average value and a confidence interval of the capacitance coefficient based on the measurement result; establishing a target piecewise linear regression model based on the weighted average value and the confidence interval, and determining the capacitance mapping relationship coefficient based on the target piecewise linear regression model.

[0018] Optionally, in one embodiment of the present application, a capacitive sensor substrate is provided on the array-type interdigital capacitor, wherein the method further comprises: measuring the capacitance change of the at least one interdigital capacitor unit using the conductive layer signal layer of the capacitive sensor substrate and the polymer material insulating layer of the capacitive sensor substrate to generate measurement data results.

[0019] The second aspect of the present application provides a material distribution morphology detection device based on an array-type interdigital capacitor, wherein an array-type interdigital capacitor is set on the target material, and the array-type interdigital capacitor is composed of at least one interdigital capacitor unit, wherein the device includes: a determination module for determining a capacitance mapping relationship coefficient between the area coverage of the target material and the capacitance change of the at least one interdigital capacitor unit based on the capacitance value of the target material and the at least one interdigital capacitor unit; a measurement module for placing materials with the same area coverage on the at least one interdigital capacitor unit in sequence based on the capacitance mapping relationship coefficient, and measuring the capacitance of the at least one interdigital capacitor unit. The capacitance at each point on an interdigitated capacitance unit is calculated, and the influence coefficient of the capacitance at each point is calculated to determine the influence coefficient matrix of the material placed at the capacitance at each point based on the influence coefficient and a preset influence matrix; an acquisition module is used to obtain the capacitance matrix of each row and column coordinate in the target full array through full array scanning based on the influence coefficient matrix, and determine the material coverage on the at least one interdigitated capacitance unit according to the capacitance matrix and a preset material distribution matrix; a detection module is used to detect the distribution form of the material, and process the material coverage according to the distribution form to generate a continuous material distribution map of the material.

[0020] Optionally, in one embodiment of the present application, an orthogonal wiring architecture and a multiplexer are set on the array-type interdigital capacitor, and the orthogonal wiring architecture includes a row bus group and a column bus group. The input end of the multiplexer is connected to the target controller, and the output end of the multiplexer is connected to the row bus group and the column bus group, wherein the device also includes: a first activation module, used to activate a single row bus in the row bus group, so as to traverse each column bus in the column bus group according to the single row bus, generate a column bus traversal result, and measure the capacitance value of each point capacitor according to the column bus traversal result; or, a second activation module, used to activate a single column bus in the column bus group, so as to traverse each row bus in the row bus group according to the single column bus, generate a row bus traversal result, and measure the capacitance value of each point capacitor according to the row bus traversal result.

[0021] Optionally, in one embodiment of the present application, the preset influence matrix is:

[0022]

[0023] in, Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j) and the capacitance at position (m,n) The ratio of

[0024] The influence coefficient matrix is:

[0025]

[0026] in, Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j) and the capacitance at position (m,n) ratio.

[0027] Optionally, in one embodiment of the present application, the capacitor matrix is:

[0028]

[0029] Among them, k C is the capacitance coefficient, is the material area coverage A at position (i, j) i,j ∈[0%,100%] and capacitance change ΔC i,j The capacitance mapping ratio, i.e. k C =ΔC i,j / A i,j , Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j) and the capacitance at position (m,n) The ratio of [x 1,1 ,…,x M,N ] T is the material distribution matrix to be determined, x i,j is the area coverage of the material to be determined at position (i, j), [C 1,1 ,…,C M,N ] T In order to obtain the capacitance matrix of each row and column coordinate unit through the full array scanning, C i,j is the actual measured capacitance value at position (i, j).

[0030] Optionally, in one embodiment of the present application, the determination module includes: a calculation unit for measuring at least one area coverage calibration point of the target material to generate a measurement result, and calculating a weighted average value and a confidence interval of the capacitance coefficient based on the measurement result; a determination unit for establishing a target piecewise linear regression model based on the weighted average value and the confidence interval, and determining the capacitance mapping relationship coefficient based on the target piecewise linear regression model.

[0031] Optionally, in one embodiment of the present application, a capacitive sensor substrate is provided on the array-type interdigital capacitor, wherein the device further includes: a generation module for measuring the capacitance change of the at least one interdigital capacitor unit using the conductive layer signal layer of the capacitive sensor substrate and the polymer material insulating layer of the capacitive sensor substrate to generate measurement data results.

[0032] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the material distribution morphology detection method based on array-type interdigital capacitance as described in the above embodiment.

[0033] The fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the above-mentioned material distribution morphology detection method based on array-type interdigital capacitance.

[0034] The fifth aspect of the present application provides a computer program product, which stores a computer program. When the program is executed by a processor, it implements the above-mentioned material distribution morphology detection method based on array-type interdigital capacitance.

[0035] The multi-point measurement in the embodiment of the present application can better reflect the global information of the material level in the measured area than the single-point measurement, and can effectively capture the non-uniform distribution of the material surface (such as the slope, depression or arch phenomenon formed by accumulation in the non-fluid silo). Multi-point measurement can effectively reduce the sensitivity of local dielectric interference, that is, the data mutation and anomaly at the single-point position have less impact on the overall measurement results, which can effectively reduce the measurement error. It can be applied to areas with rapidly changing material levels (such as high-speed filling or discharge scenarios) to solve the problem that single-point sensors are difficult to track complex morphological changes in real time. Thus, it solves the problems in the related art that single-point measurement can only reflect local material level information and cannot capture the non-uniform distribution of the material surface, the fluctuation of the material dielectric constant will significantly affect the capacitance value, resulting in measurement errors, and the single-point sensor is difficult to track complex morphological changes in real time.

[0036] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0038] Figure 1 This is a flow chart of a material distribution morphology detection method based on array-type interdigital capacitance according to an embodiment of the present application;

[0039] Figure 2 1 is a schematic diagram of an array-type interdigital capacitor method according to one embodiment of the present application;

[0040] Figure 3 Schematic diagram of an interdigital capacitor unit according to one embodiment of the present application;

[0041] Figure 4 Schematic diagram of the detection of the arching phenomenon by array interdigital capacitance in Example 1;

[0042] Figure 5 This is a schematic diagram of the principle of detecting the arching phenomenon of the array interdigital capacitor in Example 1;

[0043] Figure 6 This is a schematic diagram of the installation of the array interdigital capacitor of Example 1;

[0044] Figure 7 This is a schematic diagram of the installation of the array interdigital capacitor of Example 3;

[0045] Figure 8 This is a schematic diagram of the installation of the array interdigital capacitor of Example 4;

[0046] Figure 9 Schematic diagram of a material distribution morphology detection device based on array-type interdigital capacitance according to an embodiment of the present application;

[0047] Figure 10 A schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0048] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0049] The following describes the material distribution morphology detection method and device based on array-type interdigital capacitance of the embodiment of the present application with reference to the accompanying drawings. In view of the related art mentioned in the above background technology, single-point measurement can only reflect local material level information and cannot capture the non-uniform distribution of the material surface. The fluctuation of the dielectric constant of the material will significantly affect the capacitance value, resulting in measurement errors. The problem that the single-point sensor is difficult to track complex morphological changes in real time, the present application provides a material distribution morphology detection method based on array-type interdigital capacitance, in which multi-point measurement can better reflect the global information of the material level in the measured area than single-point measurement, and can effectively capture the non-uniform distribution of the material surface (such as the slope, depression or arch phenomenon formed by accumulation in non-fluid silos), and multi-point measurement can effectively reduce the sensitivity to local dielectric interference, that is, the data mutation and anomaly at the single-point position have less influence on the overall measurement result, which can effectively reduce the measurement error, and can be applied to rapidly changing material level (such as high-speed filling or discharge scenes) areas to solve the problem that the single-point sensor is difficult to track complex morphological changes in real time. This solves the problems in related technologies, such as single-point measurement can only reflect local material level information and cannot capture the uneven distribution of the material surface. Fluctuations in the dielectric constant of the material will significantly affect the capacitance value, resulting in measurement errors. Single-point sensors are difficult to track complex morphological changes in real time.

[0050] Specifically, Figure 1 A schematic flow chart of a material distribution morphology detection method based on array-type interdigital capacitance provided in an embodiment of the present application.

[0051] like Figure 1 As shown, the material distribution morphology detection method based on array-type interdigital capacitors is provided on the target material. The array-type interdigital capacitors are composed of at least one interdigital capacitor unit and include the following steps:

[0052] In step S101 , a capacitance mapping coefficient between the area coverage of the target material and the capacitance variation of the at least one interdigital capacitor unit is determined based on the target material and the capacitance value of the at least one interdigital capacitor unit.

[0053] It is understandable that if Figure 2 As shown, the array-type interdigital capacitor in the embodiment of the present application is an array-type interdigital capacitor sensor. The array-type interdigital capacitor can be a sensing array composed of m×n interdigital capacitor units, each unit C i,j The row and column coordinates of are uniquely determined by i∈[1,m],j∈[1,n]; Figure 3 Schematic diagram of at least one interdigital capacitor unit, wherein the structural parameters of at least one interdigital capacitor unit satisfy: the ratio of the interdigital electrode width w to the spacing s w / s∈[0.2,5], the unit envelope size D and the electrode length L satisfy D / L≥1.1, and the adjacent unit spacing d≥3s.

[0054] In the actual implementation process, the embodiment of the present application can control the MUX to select the target unit C during the calibration measurement phase. i,j , cover the measuring material in the interdigital capacitor unit area and collect the capacitance value to establish the area coverage A i,j ∈[0%,100%] and capacitance change ΔC i,j Capacitance mapping coefficient k C =ΔC i,j / A i,j (abbreviated as k C is the capacitance coefficient).

[0055] The embodiment of the present application uses interdigital capacitance for measurement, which has the advantages of being non-contact, simple in structure, and low in cost.

[0056] Optionally, in one embodiment of the present application, the capacitance mapping relationship coefficient between the area coverage of the target material and the capacitance change of at least one interdigitated capacitance unit is determined, including: measuring at least one area coverage calibration point of the target material to generate a measurement result, and calculating the weighted average value and confidence interval of the capacitance coefficient based on the measurement result; establishing a target piecewise linear regression model based on the weighted average value and the confidence interval, and determining the capacitance mapping relationship coefficient based on the target piecewise linear regression model.

[0057] Among them, the embodiment of the present application can set no less than 5 area coverage calibration points (0%, 20%, 40%, 60%, 80%, 100%), and perform ≥3 repeated measurements on each area coverage calibration point to generate measurement results, and calculate the capacitance coefficient k based on the measurement results. C The weighted mean and confidence interval of k are used to establish the target piecewise linear regression model: C =αA, where α is determined by the least squares method, and the capacitance mapping relationship coefficient is determined according to the target piecewise linear regression model.

[0058] The embodiment of the present application uses an array-type interdigital capacitor. Multi-point measurement can better reflect the global information of the material level in the measured area than single-point measurement, and can effectively capture the non-uniform distribution of the material surface. Multi-point measurement can effectively reduce the sensitivity to local dielectric interference, that is, the data mutations and anomalies at a single point position have less impact on the overall measurement results, which can effectively reduce measurement errors. The use of interdigital capacitors for measurement has the advantages of non-contact, simple structure and low cost.

[0059] In step S102, based on the capacitance mapping relationship coefficient, materials that meet the same area coverage are placed on at least one interdigital capacitor unit in sequence, and the capacitance of each point on at least one interdigital capacitor unit is measured, and the influence coefficient of the capacitance at each point is calculated to determine the influence coefficient matrix of the material placed at each point capacitance based on the influence coefficient and the preset influence matrix.

[0060] In the actual implementation process, the embodiment of the present application can place materials that meet the same area coverage rate on each interdigital capacitor unit in sequence based on the capacitance mapping relationship coefficient, measure the capacitance of each point on each interdigital capacitor unit, and calculate the influence coefficient of the capacitance of each point:

[0061]

[0062] in, Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j). and the capacitance at position (m,n) The ratio of is the influence matrix of the position.

[0063] It should be noted that since different capacitors are connected to the same line, there is crosstalk between the capacitors, and changes in the non-connected capacitance value will also affect the dielectric constant.

[0064] The embodiment of the present application can determine the influence coefficient matrix of the material placed at each point capacitor based on the influence coefficient and the preset influence matrix, wherein, in one embodiment of the present application, the preset influence matrix for:

[0065]

[0066] in, Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j). and the capacitance at position (m,n) The ratio of

[0067] The matrix Dimension reduction and expansion, through full array scanning to obtain the influence coefficient matrix M of the measured material placed at each point β , the influence coefficient matrix is:

[0068]

[0069] in, Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j). and the capacitance at position (m,n) ratio.

[0070] In step S103, based on the influence coefficient matrix, the capacitance matrix of each row and column coordinate in the target full array is obtained by full array scanning, and the material coverage on at least one interdigital capacitance unit is determined according to the capacitance matrix and the preset material distribution matrix.

[0071] It can be understood that in the embodiment of the present application, the row and column coordinates in the target full array can be actual row and column coordinate units.

[0072] In the actual implementation process, the embodiment of the present application can obtain the capacitance matrix M of each row and column coordinate unit by scanning the entire array after calibration in the measurement and inverse problem solving stage: C , M C =[C 1,1 ,…,C M,N ] T , construct the matrix equation M C =k C M β X, where X is the material distribution matrix to be determined, X = [x 1,1 ,…,x M,N ] T .

[0073] In one embodiment of the present application, the capacitance matrix is expanded as follows:

[0074]

[0075] Among them, k C is the capacitance coefficient, is the material area coverage A at position (i, j) i,j ∈[0%,100%] and capacitance change ΔC i,j The capacitance mapping ratio, i.e. k C =ΔC i,j / A i,j , Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j). and the capacitance at position (m,n) The ratio of [x 1,1 ,…,x M,N ] T is the material distribution matrix to be determined, x i,j is the area coverage of the material to be determined at position (i, j), [C 1,1 ,…,C M,N ] T In order to obtain the capacitance matrix of each row and column coordinate unit through full array scanning, C i,j is the actual measured capacitance value at position (i, j).

[0076] Right now:

[0077]

[0078] By solving for each x k,l The material coverage on each capacitor unit can be obtained.

[0079] In step S104 , the distribution form of the material is detected, and the material coverage is processed according to the distribution form to generate a continuous material distribution map of the material.

[0080] Specifically, in the spatial interpolation stage, the embodiment of the present application can use a linear interpolation algorithm to process the material coverage of the adjacent unit gap area to generate a continuous material distribution map of the material.

[0081] Among them, the embodiment of the present application adopts a controller, which includes a computer with functions such as capacitance measurement, input and output interfaces, and a readable storage medium, and stores program instructions for the above content. The instruction configuration is:

[0082] (1) Generate a three-dimensional material distribution grayscale map, and the grayscale mapping relationship satisfies G = 255 × (1-x i,j / x max );

[0083] (2) Output dynamic change parameters, including: material change rate v = dx i,j / dt; spatial non-uniformity index U = σ / μ, where σ is the distribution variance and μ is the mean; characteristic parameter out-of-limit alarm signal.

[0084] The embodiments of the present application can reflect the global information of the material level in the measured area through multi-point measurement, can effectively capture the non-uniform distribution of the material surface, can be applied to rapidly changing material level areas, and solve the problem that single-point sensors are difficult to track complex morphological changes in real time.

[0085] Optionally, in one embodiment of the present application, an orthogonal wiring architecture and a multiplexer are set on the array-type interdigital capacitor, the orthogonal wiring architecture includes a row bus group and a column bus group, the input end of the multiplexer is connected to the target controller, and the output end of the multiplexer is connected to the row bus group and the column bus group, wherein the method further includes: activating a single row bus in the row bus group to traverse each column bus in the column bus group according to the single row bus, generate a column bus traversal result, and measure the capacitance value of each point capacitor according to the column bus traversal result; or, activating a single column bus in the column bus group to traverse each row bus in the row bus group according to the single column bus, generate a row bus traversal result, and measure the capacitance value of each point capacitor according to the row bus traversal result.

[0086] It can be understood that the orthogonal wiring architecture in the embodiment of the present application includes a row bus group and a column bus group, each row bus group is connected to the first polarity end (cathode or anode) of the corresponding row finger capacitor, and each column bus group is connected to the second polarity end (opposite to the first polarity) of the corresponding column finger capacitor; the input end of the multiplexer in the embodiment of the present application is connected to the target controller, and the output end of the multiplexer is connected to the row bus group and the column bus group.

[0087] During actual implementation, the embodiments of the present application may, in row selection mode: activate a single row bus in the row bus group to traverse the column buses in the column bus group according to the single row bus, generate a column bus traversal result, and measure the capacitance value of each point capacitor according to the column bus traversal result; or, in column selection mode: activate a single column bus in the column bus group to traverse the row buses in the row bus group according to the single column bus, generate a row bus traversal result, and measure the capacitance value of each point capacitor according to the row bus traversal result.

[0088] The orthogonal scanning period T satisfies T≤1 / (2f max ), where f max It is the highest frequency of dynamic changes of the material being measured.

[0089] The embodiments of the present application can achieve highly robust real-time reconstruction of material morphology by optimizing electrode arrangement and designing data fusion algorithms, which has a positive effect in the fields of bulk material storage, transportation process monitoring, and intelligent manufacturing.

[0090] Optionally, in one embodiment of the present application, a capacitive sensor substrate is provided on the array-type interdigital capacitor, wherein the method further comprises: measuring the capacitance change of at least one interdigital capacitor unit using the conductive layer signal layer of the capacitive sensor substrate and the polymer material insulating layer of the capacitive sensor substrate to generate measurement data results.

[0091] It is understood that the sensor substrate in the embodiment of the present application includes a conductive layer signal layer etched with an m×n interdigital electrode array and a dielectric constant ε r ∈[1.5,20.5] polymer material insulating layer.

[0092] As a possible implementation method, the embodiment of the present application can use the conductive layer signal layer of the capacitance sensor substrate and the polymer material insulating layer of the capacitance sensor substrate to measure the capacitance change of at least one interdigital capacitance unit to generate measurement data results.

[0093] The embodiment of the present application measures the object to be measured through array-type interdigital capacitance, which can be applied to rapidly changing material level areas and solve the problem that single-point sensors are difficult to track complex morphological changes in real time.

[0094] Specifically, it can be combined Figures 4 to 8As shown, the working principle of the material distribution morphology detection method based on array-type interdigital capacitance in the embodiment of the present application is described in detail with a specific embodiment.

[0095] This application can be implemented in the following embodiments:

[0096] Example 1:

[0097] This embodiment is applied to the field of space exploration, specifically to the material monitoring scenario of the powder (such as lunar soil, Martian soil) storage and supply system in the extraterrestrial exploration mission. Figure 4 and Figure 5 As shown in the figure, inside the powder storage funnel, in response to the bridging and arching phenomenon that may occur during the powder process, an innovative array-type interdigital capacitance sensing technology is used to achieve real-time monitoring of material morphology. When bridging and arching occur, the material distribution near the inner wall of the funnel will produce obvious regional differences (such as the formation of local "holes" without material). Based on the principle of array capacitance sensing, this application realizes the reconstruction of the material morphology near the funnel through distributed array interdigital capacitance detection.

[0098] like Figure 6 As shown in the figure, a multi-layer PCB sensor module is integrated on the inner surface of the long hypotenuse of the trapezoidal feeding funnel (dimensions 230mm×140mm). The module uses a four-layer FR-4 substrate structure (effective detection area 206mm×126mm), where: the inner layer of the substrate is configured with a 5×8 array of interdigital capacitors, with a unit envelope size of 25mm×25mm, and a copper interdigital circuit with an electrode width w and spacing s of 0.3μm. The spacing l between adjacent unit capacitors is 5mm, and the electrode lines converge to the outer layer to set the cathode / anode bus interface (as shown in Figure 1). Figure 7 as shown), connected to the downstream multiplexer (MUX) through a shielded cable.

[0099] To implement the measurement method, the following components will be implemented:

[0100] S1. First, the computer controls the MUX to select the detection unit row by row, and performs array capacitance measurement under controlled conditions to calibrate the material coverage area-capacitance characteristic. Taking the first row and first column bus as an example, a precise material coverage experiment is performed to obtain the linear relationship between area coverage (0-100%) and relative capacitance change (capacitance coefficient):

[0101] k C =C / A

[0102] Among them, k C is the capacitance coefficient, C is the capacitance when there is no material, and A is the coverage area of the measured powder.

[0103] The experimental data of this embodiment were measured repeatedly for 5 times and the average value was obtained. The capacitance coefficient k C=15.3pF / 100%, establishing the unit baseline sensitivity parameter.

[0104] S2. Place the material on different electrode units under the experimental condition of full material coverage (100%), obtain the measured capacitance value of each array unit, and calculate the normalized influence coefficient based on the capacitance value of the row and column. For example, when the material is covered at position (1,1), the capacitance at position (1,2) is measured to be 3.1pF, then the influence coefficient is In this way, the influence coefficient matrix is finally obtained by traversing the measurement

[0105]

[0106] The matrix Dimensionality reduction and expansion are performed to obtain the influence coefficient matrix Mβ of the measured material placed at each point through full array scanning:

[0107]

[0108] S3. Finally, based on each element in the influence matrix, the relationship between each actually measured relative capacitance, the coefficient in the influence matrix, and the material coverage area can be obtained.

[0109] M C =k C M β X,

[0110] Where X is the material distribution matrix to be determined X=[x 1,1 ,…,x M,N ] T , the above formula is expanded into:

[0111]

[0112] Right now:

[0113]

[0114] By matrix inversion operation, a set of unique solutions [x 1,1 ,…,x M,N ] T , the material coverage on each capacitor unit can be obtained. S4 constructs a two-dimensional grayscale distribution map based on the solution results.

[0115] G i,j =255×(1-x i,j / x max )C i,j

[0116] like Figure 5As shown, under normal working conditions, the material will completely cover the surface of the capacitor, making the corresponding grayscale image appear black; when arching or bridging occurs, the grayscale image will appear white because the capacitor unit below is not covered by the material.

[0117] The adjacent areas of the capacitor are processed using a linear interpolation algorithm to process the cell gap area and generate a continuous material distribution grayscale image.

[0118] Ground simulation experiments have verified that this solution can quickly and in real time detect abnormal material accumulation within the hopper, with a response time of less than 200ms. When bridging occurs, the system can accurately identify areas with sudden changes in density gradient (eigenvalue variance Δσ² > 0.15). This embodiment successfully solves the technical challenges of non-contact material monitoring.

[0119] Example 2:

[0120] This embodiment targets storage bins within the feed system of industrial pulverized coal boilers. In thermal power generation systems, bridging and arching in pulverized coal bins can lead to feed interruptions, unstable boiler combustion, and even the risk of downtime. Traditional detection methods rely on bin vibration sensors or pressure transmitters, which suffer from low sensitivity, a high false alarm rate (approximately 15%-20%), and an inability to locate blockages in real time.

[0121] An 8×12 array of interdigital capacitance sensor modules was integrated on the inner wall of the trapezoidal funnel section of the middle storage bin (size 3.2m×1.8m). Based on the same method as in Example 1, the relationship between the concentration and capacitance of the coal powder at different surface positions was calibrated and a model was established to perform blockage pattern recognition.

[0122] Actual measurements on a 660MW supercritical unit have shown that the accuracy of arch formation warning has increased from 78% of the traditional method to 96.5%, the response time of arch breaking operation has been shortened to 0.8 seconds (15 times faster than manual operation), and the standard deviation σ of feed stability is less than 0.5%.

[0123] Example 3:

[0124] In the solid-liquid two-phase flow separation process in the chemical and energy fields, the surface vortex core morphology of the cyclone separator and the distribution of the outer particle phase layer directly affect the separation efficiency. Traditional methods rely on pressure differences or flow meters to indirectly determine the separation state, making it difficult to capture the dynamic changes of the particle layer in real time, resulting in delayed adjustment of the diversion ratio and large fluctuations in separation efficiency. However, the use of this application can effectively detect changes in the solid phase distribution.

[0125] An 8×10 array interdigital capacitance sensor module (base material is corrosion-resistant ceramic, electrode spacing is 0.5 mm, unit size is 20 mm×20 mm) is integrated on the outer wall of the cyclone separator (the area in contact with the particle phase layer). Figure 7 Dynamic control is achieved through the following steps:

[0126] 1. Under laboratory conditions, the nonlinear relationship between different particle layer thicknesses (0-15mm) and corresponding unit capacitance values was calibrated to establish a thickness-capacitance mapping model. The particle layer distribution matrix was obtained through full array scanning, and characteristic parameters were calculated:

[0127] Thickness gradient: When the thickness difference between adjacent cells Δh>3mm, the vortex core deviation warning is triggered;

[0128] Dynamic fluctuation index: The separation is unstable when the time domain variance of the unit capacitance value σ2>0.1 is determined;

[0129] 2. Closed-loop control: Input the above parameters into the PID controller and dynamically adjust the inlet flow split ratio (adjustment accuracy ±2%) to make the particle layer distribution tend to be uniform.

[0130] The results show that, after actual testing of a heavy oil separation system in a refinery, this solution increased the separation efficiency from 82.4% to 89.7%, and shortened the split ratio adjustment response time from 5-8 seconds in traditional methods to less than 0.5 seconds, effectively suppressing the particle backmixing phenomenon.

[0131] Example 4:

[0132] In the pharmaceutical and powder metallurgy fields, density uniformity of compressed tablets is a key quality indicator. Existing technologies rely on offline sampling and testing, which cannot detect localized looseness or overpressure defects in compressed tablets in real time, resulting in high scrap rates.

[0133] The array-type interdigital capacitance sensor (electrode material is hardened tungsten steel, unit size is 10mm×10mm, compressive strength is ≥1.5GPa) is embedded on the upper surface of the die. The specific implementation includes:

[0134] The powder compression density (1.2-2.8 g / cm 3 ) and the piecewise function relationship of the dielectric constant:

[0135] ε r =2.35+0.18ρ(ρ≤2.0g / cm 3 )

[0136] ε r＝ 2.71+0.05ρ(ρ>2.0g / cm 3 )

[0137] like Figure 8 As shown, based on the method of the present application, the powder compression density distribution is statistically analyzed, the array is scanned at a frequency of 100 Hz during the pressing process, the tablet density distribution map is reconstructed, and the uniformity coefficient is calculated: U = 1-σ / μ (target U ≥ 0.92).

[0138] Pressure compensation vector: Generates the compensation pressure ΔP of each hydraulic cylinder based on the density gradient distribution i (Adjustment range ±5MPa).

[0139] The multi-axis servo system then adjusts the indentation angle of the pressure head in real time (accuracy ±0.05°) to eliminate density distribution deviation.

[0140] The results show that after application in a certain cemented carbide blade production line, the density unevenness of the tablets was reduced from 7.3% to 1.8%, while the equipment utilization rate increased by 22%, achieving a breakthrough of 48 hours of continuous production with zero defects.

[0141] In addition to the above embodiments, the present invention can also be used to detect the height of the silo of an industrial pulverized coal furnace, slagging in pipelines and other closed containers.

[0142] According to the material distribution morphology detection method based on array-type interdigital capacitance proposed in the embodiment of the present application, multi-point measurement can better reflect the global information of the material level in the measured area than single-point measurement, and can effectively capture the non-uniform distribution of the material surface (such as the slope, depression or arch phenomenon formed by accumulation in non-fluid silos). Multi-point measurement can effectively reduce the sensitivity of local dielectric interference, that is, the data mutation and anomaly at a single point position have less impact on the overall measurement results, which can effectively reduce measurement errors. It can be applied to areas with rapidly changing material levels (such as high-speed filling or discharge scenarios) to solve the problem that single-point sensors are difficult to track complex morphological changes in real time. Thus, it solves the problem in the related art that single-point measurement can only reflect local material level information and cannot capture the non-uniform distribution of the material surface. The fluctuation of the dielectric constant of the material will significantly affect the capacitance value, resulting in measurement errors, and the problem that single-point sensors are difficult to track complex morphological changes in real time.

[0143] Next, a material distribution morphology detection device based on array-type interdigital capacitance proposed in accordance with an embodiment of the present application will be described with reference to the accompanying drawings.

[0144] Figure 9 Schematic diagram of the structure of the material distribution morphology detection device based on array-type interdigital capacitance according to an embodiment of the present application.

[0145] like Figure 9 As shown, the material distribution form detection device 10 based on array interdigital capacitance includes: a determination module 100 , a measurement module 200 , an acquisition module 300 and a detection module 400 .

[0146] Specifically, the determination module 100 is configured to determine a capacitance mapping coefficient between the area coverage of the target material and the capacitance variation of at least one interdigital capacitor unit based on the target material and the capacitance value of at least one interdigital capacitor unit.

[0147] The measurement module 200 is used to place materials with the same area coverage in sequence on at least one interdigital capacitor unit based on the capacitance mapping relationship coefficient, and measure the capacitance of each point on at least one interdigital capacitor unit, calculate the influence coefficient of the capacitance of each point, and determine the influence coefficient matrix of the material placed at each point capacitance based on the influence coefficient and the preset influence matrix.

[0148] The acquisition module 300 is used to obtain the capacitance matrix of each row and column coordinate in the target full array through full array scanning based on the influence coefficient matrix, and determine the material coverage on at least one interdigital capacitance unit according to the capacitance matrix and the preset material distribution matrix.

[0149] The detection module 400 is used to detect the distribution form of the material and process the material coverage according to the distribution form to generate a continuous material distribution map of the material.

[0150] Optionally, in one embodiment of the present application, an orthogonal wiring architecture and a multiplexer are set on the array-type interdigital capacitor, the orthogonal wiring architecture includes a row bus group and a column bus group, the input end of the multiplexer is connected to the target controller, and the output end of the multiplexer is connected to the row bus group and the column bus group, wherein the material distribution morphology detection device 10 based on the array-type interdigital capacitor also includes: a first activation module, used to activate a single row bus in the row bus group, so as to traverse each column bus in the column bus group according to the single row bus, generate a column bus traversal result, and measure the capacitance value of each point capacitor according to the column bus traversal result; or, a second activation module, used to activate a single column bus in the column bus group, so as to traverse each row bus in the row bus group according to the single column bus, generate a row bus traversal result, and measure the capacitance value of each point capacitor according to the row bus traversal result.

[0151] Optionally, in one embodiment of the present application, the preset influence matrix is:

[0152]

[0153] in, Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j). and the capacitance at position (m,n) The ratio of

[0154] The influence coefficient matrix is:

[0155]

[0156] in, Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j). and the capacitance at position (m,n) ratio.

[0157] Optionally, in one embodiment of the present application, the capacitance matrix is:

[0158]

[0159] Among them, k C is the capacitance coefficient, is the material area coverage A at position (i, j) i,j ∈[0%,100%] and capacitance change ΔC i,j The capacitance mapping ratio, i.e. k C =ΔC i,j / A i,j , Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j). and the capacitance at position (m,n) The ratio of [x 1,1 ,…,x M,N ] T is the material distribution matrix to be determined, x i,j is the area coverage of the material to be determined at position (i, j), [C 1,1 ,…,C M,N ] T In order to obtain the capacitance matrix of each row and column coordinate unit through full array scanning, C i,j is the actual measured capacitance value at position (i, j).

[0160] Optionally, in one embodiment of the present application, the determination module 100 includes: a calculation unit and a determination unit.

[0161] The calculation unit is used to measure at least one area coverage calibration point of the target material to generate a measurement result, and calculate the weighted average value and confidence interval of the capacitance coefficient based on the measurement result.

[0162] The determination unit is used to establish a target piecewise linear regression model according to the weighted average value and the confidence interval, and determine the capacitance mapping relationship coefficient according to the target piecewise linear regression model.

[0163] Optionally, in one embodiment of the present application, a capacitive sensor substrate is provided on the array-type interdigital capacitor, wherein the material distribution form detection device 10 based on the array-type interdigital capacitor further includes: a generation module.

[0164] The generating module is used to measure the capacitance variation of at least one interdigital capacitance unit by using the conductive layer and signal layer of the capacitance sensor substrate and the polymer material insulating layer of the capacitance sensor substrate to generate measurement data results.

[0165] It should be noted that the above explanation of the embodiment of the material distribution form detection method based on array-type interdigital capacitors is also applicable to the material distribution form detection device based on array-type interdigital capacitors in this embodiment, and will not be repeated here.

[0166] According to the material distribution morphology detection device based on array-type interdigital capacitance proposed in the embodiment of the present application, multi-point measurement can better reflect the global information of the material level in the measured area than single-point measurement, and can effectively capture the non-uniform distribution of the material surface (such as the slope, depression or arch phenomenon formed by accumulation in non-fluid silos). Multi-point measurement can effectively reduce the sensitivity to local dielectric interference, that is, the data mutation and anomaly at a single point position have less impact on the overall measurement results, which can effectively reduce measurement errors. It can be applied to areas with rapidly changing material levels (such as high-speed filling or discharge scenarios) to solve the problem that single-point sensors are difficult to track complex morphological changes in real time. Thus, it solves the problem in the related art that single-point measurement can only reflect local material level information and cannot capture the non-uniform distribution of the material surface. The fluctuation of the dielectric constant of the material will significantly affect the capacitance value, resulting in measurement errors, and the problem that single-point sensors are difficult to track complex morphological changes in real time.

[0167] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0168] A memory 1001 , a processor 1002 , and a computer program stored in the memory 1001 and executable on the processor 1002 .

[0169] When the processor 1002 executes the program, the material distribution form detection method based on array-type interdigital capacitance provided in the above embodiment is implemented.

[0170] Furthermore, the electronic device further includes:

[0171] The communication interface 1003 is used for communication between the memory 1001 and the processor 1002 .

[0172] The memory 1001 is used to store computer programs that can be run on the processor 1002 .

[0173] The memory 1001 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0174] If the memory 1001, processor 1002, and communication interface 1003 are implemented independently, the communication interface 1003, memory 1001, and processor 1002 can be connected to each other via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 10 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0175] Optionally, in a specific implementation, if the memory 1001, the processor 1002 and the communication interface 1003 are integrated on a chip, the memory 1001, the processor 1002 and the communication interface 1003 can communicate with each other through an internal interface.

[0176] The processor 1002 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0177] This embodiment further provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the above-mentioned material distribution morphology detection method based on array-type interdigital capacitance is implemented.

[0178] An embodiment of the present application further provides a computer program product on which a computer program is stored. When the program is executed by a processor, the above-mentioned material distribution morphology detection method based on array-type interdigital capacitance is implemented.

[0179] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0180] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of this application, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0181] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing a custom logical function or process step, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed in a different order than shown or discussed, including performing functions in a substantially simultaneous manner or in a reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0182] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or N wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program can be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing it in other suitable ways as necessary, and then storing it in a computer memory.

[0183] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0184] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0185] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0186] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A material distribution morphology detection method based on array interdigital capacitance, characterized in that: An array of interdigital capacitors is provided on a target material, wherein the array of interdigital capacitors is composed of at least one interdigital capacitor unit, wherein the method comprises the following steps: Determining a capacitance mapping relationship coefficient between an area coverage of the target material and a capacitance change of the at least one interdigital capacitor unit based on the capacitance values of the target material and the at least one interdigital capacitor unit; Based on the capacitance mapping relationship coefficient, materials with the same area coverage are sequentially placed on the at least one interdigital capacitor unit, and the capacitance of each point on the at least one interdigital capacitor unit is measured, and the influence coefficient of the capacitance of each point is calculated, so as to determine the influence coefficient matrix of the material placed at each point capacitance based on the influence coefficient and a preset influence matrix; Based on the influence coefficient matrix, a capacitance matrix of each row and column coordinate in the target full array is obtained by full array scanning, and a material coverage rate on the at least one interdigital capacitance unit is determined according to the capacitance matrix and a preset material distribution matrix; The distribution form of the material is detected, and the material coverage is processed according to the distribution form to generate a continuous material distribution map of the material.

2. The method according to claim 1, characterized in that An orthogonal wiring structure and a multiplexer are provided on the array-type interdigital capacitor, wherein the orthogonal wiring structure includes a row bus group and a column bus group, an input end of the multiplexer is connected to a target controller, and an output end of the multiplexer is connected to the row bus group and the column bus group, wherein the method further comprises: activating a single row bus in the row bus group to traverse each column bus in the column bus group according to the single row bus, generating a column bus traversal result, and measuring the capacitance value of each point capacitor according to the column bus traversal result; Alternatively, a single column bus in the column bus group is activated to traverse each row bus in the row bus group according to the single column bus to generate a row bus traversal result, and the capacitance value of each point capacitor is measured according to the row bus traversal result.

3. The method according to claim 1, characterized in that The preset impact matrix is: in, Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j) and the capacitance at position (m,n) The ratio of The influence coefficient matrix is: in, Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j) and the capacitance at position (m,n) ratio.

4. The method according to claim 3, characterized in that The capacitance matrix is: Among them, k C is the capacitance coefficient, is the material area coverage A at position (i, j) i,j ∈[0%,100%] and capacitance change ΔC i,j The capacitance mapping ratio, i.e. k C =ΔC i,j / A i,j , Place the material with the same area coverage at position (m,n) and measure the capacitance at position (i,j) and the capacitance at position (m,n) The ratio of [x 1,1 ,…,x M,N ] T is the material distribution matrix to be determined, x i,j is the area coverage of the material to be determined at position (i, j), [C 1,1 ,…,C M,N ] T In order to obtain the capacitance matrix of each row and column coordinate unit through the full array scanning, C i,j is the actual measured capacitance value at position (i, j).

5. The method according to claim 1, characterized in that The determining of a capacitance mapping relationship coefficient between the area coverage of the target material and the capacitance change of the at least one interdigital capacitor unit includes: Measuring at least one area coverage calibration point of the target material to generate a measurement result, and calculating a weighted average value and a confidence interval of the capacitance coefficient based on the measurement result; A target piecewise linear regression model is established according to the weighted average value and the confidence interval, and the capacitance mapping relationship coefficient is determined according to the target piecewise linear regression model.

6. The method according to claim 1, characterized in that A capacitive sensor substrate is provided on the array-type interdigital capacitor, wherein the method further comprises: The capacitance variation of the at least one interdigital capacitor unit is measured by utilizing the conductive layer and signal layer of the capacitance sensor substrate and the polymer material insulating layer of the capacitance sensor substrate to generate measurement data results.

7. A material distribution morphology detection device based on array interdigital capacitance, characterized in that: An array of interdigital capacitors is provided on a target material, wherein the array of interdigital capacitors is composed of at least one interdigital capacitor unit, wherein the device comprises: a determination module, configured to determine a capacitance mapping relationship coefficient between the area coverage of the target material and the capacitance variation of the at least one interdigital capacitor unit based on the capacitance value of the target material and the at least one interdigital capacitor unit; a measurement module, configured to sequentially place materials having the same area coverage on the at least one interdigital capacitor unit based on the capacitance mapping relationship coefficient, measure capacitance at each point on the at least one interdigital capacitor unit, calculate an influence coefficient of the capacitance at each point, and determine an influence coefficient matrix of the material placed at each capacitance point based on the influence coefficient and a preset influence matrix; an acquisition module, configured to acquire, based on the influence coefficient matrix, a capacitance matrix of each row and column coordinate in the target full array by full array scanning, and determine a material coverage rate on the at least one interdigital capacitance unit according to the capacitance matrix and a preset material distribution matrix; The detection module is used to detect the distribution form of the material and process the material coverage according to the distribution form to generate a continuous material distribution map of the material.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the material distribution morphology detection method based on array-type interdigital capacitance as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the material distribution morphology detection method based on array-type interdigital capacitance as described in any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that The computer program is executed to implement the material distribution morphology detection method based on array-type interdigital capacitance according to any one of claims 1 to 6.

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