Visual monitoring method, device, equipment and storage medium for conveyor belt wear

Abstract

The present application discloses a visual monitoring method, device, computer equipment and storage medium for conveyor belt wear, including receiving first thickness data of the conveyor belt uploaded by a laser sensor array, updating a data matrix based on the first thickness data; updating a corresponding first interpolation matrix based on the updated data matrix; determining RGBA color values ​​for rendering and display based on the thickness data in the updated first interpolation matrix, and updating and displaying a Bitmap image according to a color value matrix composed of RGBA color values. This solution converts the cover glue thickness collected by the sensor array into the RGBA value of a pixel image and generates a visual dynamic image display, which reflects the wear of the conveyor belt with changes in image color and depth, and realizes the conversion of rigid values ​​into intuitive visual image display.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of image display technology, and in particular to a method for visually monitoring conveyor belt wear for detecting the thickness of conveyor belt cover rubber. Background Art

[0002] Conveyor belts are large composite parts composed of rubber covering materials, skeleton materials, and interface bonding materials. They are widely used in material transportation in the fields of mining, steel smelting, building materials and cement, ports and terminals, thermal power generation, etc. Due to the complex and harsh operating conditions of conveyor belts, the conveyor belts are affected by materials during operation, and are in long-term contact and friction with conveyor rollers and materials, causing the conveyor belt covering rubber to wear or even fall off, delaying production and even threatening the lives of workers around the conveyor. On-site maintenance personnel need to regularly check the wear of the conveyor belts. Wear detection of the conveyor belts is particularly important. If abnormalities are found, the conveyor belts should be repaired and replaced according to technical requirements to ensure the normal operation of production operations.

[0003] The covering rubber is the top layer of the conveyor belt body. The material will eventually come into contact with the surface of the conveyor rubber, so the thickness of the top layer of covering rubber is the first thing that reflects the wear of the conveyor belt. In the related technology, the thickness of the covering rubber is usually observed by the naked eye by on-site conveyor maintenance personnel. This method is labor-intensive and easy to miss. Some methods also form several detection units by arranging several laser sensors above and below the cross section of the conveyor belt. During the rolling of the conveyor belt, the detection unit reports the covering rubber thickness value at the current cross-section position of the conveyor belt in real time. Although this method can detect in real time, it is not convenient for maintenance personnel to intuitively obtain and display the degree of wear of each part, which is not conducive to targeted maintenance. Summary of the invention

[0004] The embodiment of the present application provides a method, device, computer equipment and storage medium for visually monitoring conveyor belt wear. The technical solution is as follows:

[0005] In one aspect, the present application provides a method for visually monitoring conveyor belt wear, the method comprising:

[0006] Receiving first thickness data of the conveyor belt uploaded by the laser sensor array, and updating the data matrix based on the first thickness data; the laser sensor array is installed above the cross section of the conveyor belt, and the detection width is not less than the width of the conveyor belt, and the data matrix contains n groups of original thickness data for representing the covering rubber;

[0007] Based on the updated data matrix, the corresponding first interpolation matrix is ​​updated; the first interpolation matrix contains N groups of thickness data of the cover glue after interpolation conversion; N and n are positive integers;

[0008] Based on the thickness data in the updated first interpolation matrix, the RGBA color values ​​used for rendering and display are determined, and the Bitmap image is updated and displayed according to the color value matrix composed of the RGBA color values.

[0009] On the other hand, the present application provides a conveyor belt wear detection device, the device comprising:

[0010] A data matrix update module, used for receiving first thickness data of the conveyor belt uploaded by the laser sensor array, and updating the data matrix based on the first thickness data; the laser sensor array is installed above the cross section of the conveyor belt, and the detection width is not less than the width of the conveyor belt, and the data matrix contains n groups of original thickness data for representing the covering rubber;

[0011] An interpolation matrix updating module, used for updating a corresponding first interpolation matrix based on the updated data matrix; the first interpolation matrix contains N groups of cover glue thickness data after interpolation conversion; N and n are positive integers;

[0012] An image update module is used to determine the RGBA color values ​​used for rendering and display based on the thickness data in the first interpolation matrix after update, and to update and display the Bitmap image according to the color value matrix composed of the RGBA color values.

[0013] On the other hand, the present application provides a computer device, which includes a processor and a memory, wherein the memory stores at least one program, and the at least one program is loaded and executed by the processor to implement the method for visually monitoring conveyor belt wear described in the above aspect.

[0014] On the other hand, the present application provides a computer-readable storage medium, wherein the storage medium stores at least one instruction, and the at least one instruction is used to be executed by a processor to implement the method for visually monitoring conveyor belt wear as described in the above aspects.

[0015] On the other hand, an embodiment of the present application provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the visual monitoring method for conveyor belt wear provided in the above aspect.

[0016] The beneficial effects of the technical solution provided by the embodiment of the present application include at least: collecting the first thickness data of the covering rubber by receiving the sensor array, and constructing and updating the data matrix about the thickness of the covering rubber based on the first thickness data, and then updating the first interpolation matrix based on the updated data matrix; enlarging the data matrix to a suitable size for the purpose of facilitating observation and image rendering; and then converting the interpolated thickness data into the corresponding RGBA color value matrix to realize the visualization of the thickness data. That is, generating a visual dynamic image display, reflecting the wear of the conveyor belt with the changes in image color and depth, and realizing the conversion of rigid numerical values ​​into intuitive visual image display. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a schematic diagram of a scenario in which a sensor array provided in an embodiment of the present application detects conveyor belt wear;

[0018] Figure 2 is a flow chart of a method for visually monitoring conveyor belt wear provided in an embodiment of the present application;

[0019] Figure 3 is a schematic diagram of the interface of a bitmap image provided in an embodiment of the present application;

[0020] Figure 4 is a flow chart of a method for visually monitoring conveyor belt wear provided by another embodiment of the present application;

[0021] Figure 5 It is a schematic diagram of the interface of the presentation area of ​​the two-dimensional data matrix provided in an embodiment of the present application;

[0022] Figure 6 It is a schematic diagram of a process of updating a data matrix in a target area provided by an embodiment of the present application;

[0023] Figure 7 is a schematic diagram of determining an original position based on a target interpolation position provided in an embodiment of the present application;

[0024] Figure 8 is a flow chart of a method for visually monitoring conveyor belt wear provided by another embodiment of the present application;

[0025] Fig. 9 It is a structural block diagram of the conveyor belt wear detection device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0027] The term "multiple" as used herein refers to two or more than two. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects are in an "or" relationship.

[0028] Figure 1 This is a schematic diagram of a scenario in which the sensor array provided in the embodiment of the present application detects conveyor belt wear. The conveyor belt can be a transmission device in any industrial scenario. This solution uses the conveyor belt used for logistics detection as an example. A sensor array is formed by arranging a number of laser sensors above and below the conveyor belt cross section. During the rolling process of the conveyor belt, the sensor array reports the cover rubber thickness value at the current conveyor belt cross section in real time. For example Figure 1 In the example, a conveyor belt with a width of 1.2m is equipped with 7 detection laser sensor units S1-S7 to ensure that the entire width of the conveyor belt can be covered. The sensor array is connected to the computer device through the acquisition line. The computer device includes a display, which can process the received sensor data, convert the thickness data of the cover glue into image data and display it dynamically. The maintenance personnel judge the wear of the conveyor belt through the visual image displayed on the interface.

[0029] Figure 2 : is a flow chart of a method for visually monitoring conveyor belt wear provided in an embodiment of the present application, comprising the following steps:

[0030] Step 201: receiving first thickness data of the conveyor belt uploaded by the laser sensor array, and updating the data matrix based on the first thickness data.

[0031] like Figure 1 As shown in , the laser sensor array is installed above (or below) the cross section of the conveyor belt, and the detection width is not less than the width of the conveyor belt. The sensor acquisition frequency is set according to the running speed of the conveyor belt to ensure uniform data acquisition. When the covering rubber on the conveyor belt is severely worn, the value detected by the laser sensor changes greatly, which is the first thickness data of the conveyor belt. In this scheme, the data collected by the laser sensor array at one time is a set of first thickness data in the column direction of the conveyor belt. The data matrix is ​​a two-dimensional matrix used for subsequent interpolation updates and image display, which contains the original thickness data uploaded in the first n columns. The dimension of the data matrix is ​​an m*n matrix (m and n are positive integers), that is, it contains m rows and n columns of original thickness data. Each time the laser sensor array collects a column of thickness data, the computer device updates the data matrix based on the received first thickness data.

[0032] Step 202: Update the corresponding first interpolation matrix based on the updated data matrix.

[0033] Since the data matrix is ​​a matrix directly pieced together by N columns of thickness data, when the value of N is too small, it affects the result of computer rendering; when the value of N is too large, it affects the rendering efficiency of the computer, and the rendered image may have blurred points like mosaic effects. Therefore, this scheme needs to interpolate the data while selecting the N value. The interpolation process can enlarge the image by a certain proportion without affecting the image resolution and observation results, and can output an image of moderate size. The first interpolation matrix is ​​a matrix formed after the data matrix is ​​interpolated and transformed. Its purpose is to enlarge or reduce the original matrix dimension, generate a matrix dimension size suitable for image display, and then generate a color value matrix. Therefore, the dimension of the updated first interpolation matrix and the dimension of the data matrix may be different. The first interpolation matrix in this scheme contains N groups of thickness data of the cover glue after interpolation conversion, and the dimension of the first interpolation matrix is ​​an M*N matrix (M and N are positive integers).

[0034] Step 203: Determine the RGBA color value used for rendering and display based on the thickness data in the updated first interpolation matrix, and update and display the Bitmap image according to the color value matrix composed of the RGBA color values.

[0035] The first interpolation matrix is ​​a matrix set for image enlargement or reduction, and the values ​​inside it are still used to represent the thickness of the cover glue. The purpose of this solution is to output a Bitmap image and describe the wear of the conveyor belt through the color change of the image; and the sensor array is not a camera array and cannot capture color. Therefore, this solution needs to convert the updated interpolation data into RGBA color value data, that is, convert the first interpolation matrix into a color value matrix, and then convert the color value matrix into the corresponding pixel block to display and render the Bitmap image.

[0036] like Figure 3 As shown, in the Bitmap image, the thickness data of the cover glue originally collected is converted into color image data, and the color and transparency of each position in the image change according to the thickness value. During the continuous transmission of the conveyor belt, the laser sensor array continuously collects and uploads data, so the computer equipment continuously updates and renders the Bitmap image based on the collection frequency, and the maintenance personnel judge the wear of the conveyor belt according to the changes in the color depth of the image.

[0037] In summary, this solution collects the first thickness data of the cover rubber by receiving the sensor array, and constructs and updates the data matrix about the thickness of the cover rubber based on the first thickness data, and then updates the first interpolation matrix based on the updated data matrix; the data matrix is ​​enlarged to a suitable size for the purpose of facilitating observation and image rendering; and then the interpolated thickness data is converted into the corresponding RGBA color value matrix to realize the visualization of the thickness data. That is, a visual dynamic image display is generated, and the wear of the conveyor belt is reflected by the changes in image color and depth, realizing the conversion of rigid numerical values ​​into intuitive visual image display.

[0038] Figure 4 : is a flow chart of a method for visually monitoring conveyor belt wear provided by another embodiment of the present application, comprising the following steps:

[0039] Step 401, receiving the first thickness data of the conveyor belt uploaded by the laser sensor, and updating the first column thickness data based on the second column thickness data of the data matrix, and updating the second column thickness data based on the third column thickness data, until the nth column thickness data updates the n-1th column thickness data.

[0040] Since the laser sensor is fixed, the data matrix collected and maintained also corresponds to a fixed target area; and the conveyor belt moves dynamically, so the collection frequency needs to be set according to the moving direction and speed of the conveyor belt, and the data matrix needs to be updated one by one to ensure that the data in the data matrix is ​​the latest thickness data.

[0041] like Figure 5 As shown, the framed area is the presentation area of ​​the two-dimensional data matrix collected by the laser sensor array. As the conveyor belt changes, the image displayed on the computer device also changes accordingly.

[0042] Indicative, such as Figure 6 As shown, it is a schematic diagram of the process of updating the data matrix in the target area. In the m*n dimensional matrix, n sets of thickness data collected in the historical process are included. After the most recent set of first thickness data is collected, the entire data matrix needs to be updated and adjusted. Specifically, the second column thickness data is updated and replaced with the first column thickness data, and the third column thickness data updates the second column thickness data, until the nth column thickness data is updated with the n-1th column thickness data. That is, the data of the entire matrix moves forward by one column unit.

[0043] Step 402: Update the first thickness data uploaded by the sensor array as the nth column data of the data matrix to obtain an updated data matrix.

[0044] When the last n-th column of thickness data updates the n-1th column of data, the newly collected first thickness data is used as the nth thickness data and input into the data matrix to obtain the updated data matrix. Figure 6 .

[0045] Step 403, calculating the row scaling ratio and the column scaling ratio between the first interpolation matrix and the array matrix.

[0046] The purpose of interpolation transformation is to enlarge the image. At the same time, in order to take into account the image resolution, before the interpolation calculation, the row scaling ratio and column scaling ratio need to be determined according to the dimensional relationship between the interpolation matrix and the data matrix. The row scaling ratio a=M / m, the column scaling ratio b=N / n. The row scaling ratio and column scaling ratio are used to determine the data to be calculated in the interpolation matrix corresponding to the target position in the data matrix.

[0047] Step 404: Determine, based on the row scaling ratio and the column scaling ratio, the original position in the data matrix corresponding to the target interpolation position in the first interpolation matrix.

[0048] Indicatively, assume that the value at B(X,Y) in the first interpolation matrix is ​​calculated by row-column scaling to obtain the value at the corresponding position b(x,y)=(X*m / M,Y*n / N) in the data matrix. However, the calculation result may be a decimal, so it is further expressed as b(x,y)=([x]+u,[y]+v). [x] and [y] represent the integer parts of x and y, and u and v represent the decimal parts.

[0049] Step 405, determining 16 groups of original thickness data corresponding to the original position and the surrounding in the data matrix, and calculating the thickness value of the target interpolation position based on the quadratic cubic interpolation method of the BiCubic basis function.

[0050] like Figure 7 As shown, the target interpolation position B(3,3) in the first interpolation matrix calculates the corresponding point A(2.4,1.6) in the data matrix. And (2.4,1.6) belongs to the position (2,2), that is, the original position is the point (2,2).

[0051] In order to make the color of the enlarged image smoother, this solution uses the quadratic cubic interpolation method based on the BiCubic basis function to calculate the thickness value of the target interpolation position, that is, the thickness values ​​of 16 positions near the original position (2,2) are selected and substituted into the basis function calculation. In other words, the thickness values ​​of 16 points in total are selected, from (0,0) to (0,3), (1,0) to (1,3), (2,0) to (2,3) and (3,0) to (3,3).

[0052] Step 406: Update the thickness values ​​of all interpolation positions in the first interpolation matrix to obtain a second interpolation matrix.

[0053] According to the above calculation method, the thickness values ​​of all positions in the first interpolation matrix are interpolated and updated in sequence, and the second interpolation matrix is ​​formed after the entire M*N matrix is ​​updated. The second interpolation matrix is ​​an interpolation matrix obtained after interpolation and updating based on the most recently uploaded first thickness data.

[0054] Step 407, determining the target thickness level to which the target thickness value in the second interpolation matrix belongs; different thickness levels correspond to different thickness value intervals.

[0055] After the target thickness value of the second interpolation matrix is ​​obtained, the target thickness level to which the target thickness value at each position belongs is determined in sequence.

[0056] In a possible implementation, the thickness value of the cover glue can be divided into different levels. For example, if the thickness data is a value between 0-9, [0,2] can be divided into the first thickness interval; [2,4] can be divided into the second thickness interval; [4,6] can be divided into the third thickness interval, [6,8] can be divided into the fourth thickness interval; and [8,9] can be divided into the fifth thickness interval. The smaller the value, the more serious the wear. Therefore. Each thickness value in the second interpolation matrix corresponds to its own target thickness level.

[0057] Step 408 : determining the RGB primary colors and transparency of the target pixel position in the color value matrix based on the target thickness level and the target thickness value.

[0058] There is a one-to-one correspondence between the second interpolation matrix and the color value matrix, so the color value matrix and the second interpolation matrix have the same dimension, which is also a matrix of M*N dimensions. However, the second interpolation matrix contains thickness data, while the color value matrix should contain RGBA values, so it is necessary to convert the target thickness level and target thickness value of each position in the second interpolation matrix to obtain the RGB primary color and transparency of the corresponding target pixel position. Specifically, Figure 8 As shown, step 408 also includes the following steps:

[0059] Step 408a, determining the RGB primary color value of the target pixel position according to the thickness level.

[0060] In a possible implementation, different thickness levels are divided into different colors, for example, the highest thickness level is represented by blue, the lowest level is represented by red, and other levels are represented by colors such as yellow and green. Different levels are set with corresponding RGB primary color values.

[0061] Step 408b, determining the maximum thickness value of the thickness interval to which the thickness level belongs, and determining the ratio of the target thickness value to the maximum thickness value of the thickness interval as the transparency of the target pixel position.

[0062] Transparency A is set based on the RGB primary color and is used to set the color depth of the target pixel block to provide a more vivid visual effect. For example, the maximum thickness value of the first thickness interval [0,2] corresponding to the first thickness interval is 2, and the ratio of the target thickness value to the maximum thickness value is the value of transparency A. In this way, each determined target thickness value will calculate its own RGB primary color value and transparency.

[0063] In another possible implementation, in order to improve rendering efficiency and reduce the load of computer rendering, the base color and the calculated transparency can be selected by the user independently.

[0064] Step 408c, determining the target RGB primary color values ​​for image display based on the primary color adjustment instruction, and setting the RGB color values ​​of all pixel positions in the color value matrix to the target RGB primary color values.

[0065] Before or during rendering, the RGB primary color value is reset through the interface command control, and when the computer receives the primary color adjustment command, it selects the color according to the command. This method sets the RGB color values ​​of all pixel positions in the color value matrix to the target RGB primary color value, that is, the entire Bitmap image is displayed in blue, red and other colors.

[0066] Step 408d: Calculate the transparency of the corresponding target pixel position based on the target thickness level to which the target thickness value belongs and the total number of thickness levels.

[0067] Under the premise of fixed RGB base color, only transparency can be used to indicate the degree of wear of the covering rubber. At this time, it needs to be calculated based on the target thickness grade and the total number of thickness grades. The calculation formula A is expressed as:

[0068]

[0069] in, Indicates the target thickness level to which the target thickness value belongs, and L indicates the total number of thickness levels. For example, if the interpolated value is 4.6, it corresponds to the third thickness interval. , the total number of levels is fixed at L=5, and as a result of the calculation A=0.4.

[0070] Step 409: Update the color value matrix based on the RGBA color value composed of the RGB primary color and the transparency.

[0071] In RGBA (242,77,77,0.4), (242,77,77) represents the RGB setting, and 0.4 represents transparency. The corresponding color value matrix is ​​obtained by calculating and updating the settings of all pixel positions.

[0072] Step 410, performing bitwise operation on the RGBA color values ​​in the color value matrix to obtain image data for image rendering.

[0073] Step 411, determine the traveling direction and traveling speed of the conveyor belt, update the length information of the conveyor belt in the Bitmap image according to the frequency of receiving the first thickness data; update the width information of the conveyor belt based on the position information uploaded by the laser sensor array.

[0074] In addition, it should be noted that the computer not only needs to receive the first thickness data, but also needs to obtain the position information uploaded by the sensor. The position information is used for the width information of the conveyor belt, which corresponds to the vertical coordinate information in the image. The transmission direction and travel speed of the conveyor belt also need to be obtained in order to display and update the length information of the conveyor belt in the Bitmap image in real time and determine the direction of dynamic movement of the image. Figure 3 as shown in .

[0075] Step 412, performing image conversion based on the image data and the length and width information of the conveyor belt, generating a Bitmap image and displaying it.

[0076] In summary, this solution receives the first thickness value of a column of cover glue collected by the laser sensor array, then moves the data of each column of the data matrix forward based on the first thickness value, and adds the newly collected thickness data to the last column to obtain an updated data matrix. Then, interpolation calculation is performed based on the updated data matrix, with the purpose of updating the first interpolation matrix and obtaining a second interpolation matrix. The interpolation calculation is calculated using at least 16 adjacent thickness values, which can ensure that no blur points will be generated after the amplified interpolation matrix is ​​converted and rendered. When performing color value conversion, the thickness interval and level are defined according to the thickness value, and the RGB primary color value and transparency are determined according to the level and thickness value, so as to obtain the color value for image display, and realize the conversion from numerical value to color. This solution subverts the traditional method of judging the thickness of the cover glue based on the value monitored by the sensor, converts the rigid numerical value into an intuitive visual dynamic image that is continuously updated and displayed, and replaces the degree of wear of the cover glue with changes in image color and depth. The operation and maintenance personnel can clearly observe the wear distribution of the conveyor belt surface, and it is easy to focus on the key parts that need maintenance, so as to carry out targeted maintenance.

[0077] Fig. 9 : is a structural block diagram of a conveyor belt wear detection device provided in an embodiment of the present application, comprising:

[0078] The data matrix update module 901 is used to receive the first thickness data of the conveyor belt uploaded by the laser sensor array, and update the data matrix based on the first thickness data; the laser sensor array is installed above the cross section of the conveyor belt, and the detection width is not less than the width of the conveyor belt, and the data matrix contains n groups of original thickness data for representing the covering rubber;

[0079] The interpolation matrix updating module 902 is used to update the corresponding first interpolation matrix based on the updated data matrix; the first interpolation matrix contains N groups of cover glue thickness data after interpolation conversion; N and n are positive integers;

[0080] The image updating module 903 is used to determine the RGBA color values ​​used for rendering and display based on the thickness data in the first interpolation matrix after update, and to update and display the Bitmap image according to the color value matrix composed of the RGBA color values.

[0081] An embodiment of the present application also provides a computer device, which includes a processor and a memory; the memory stores at least one instruction, and the at least one instruction is used to be executed by the processor to implement the visual monitoring method of conveyor belt wear provided by the above-mentioned various method embodiments.

[0082] An embodiment of the present application also provides a computer-readable storage medium, in which at least one instruction, at least one program, a code set or an instruction set is stored. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the method for visually monitoring conveyor belt wear as described in the above aspect.

[0083] The embodiment of the present application also provides a computer program product or a computer program, which includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the conveyor belt wear detection device method described in any one of the above aspects.

[0084] The preferred embodiments of the present invention are described above; it should be understood that the present invention is not limited to the above-mentioned specific embodiments, and the devices and structures not described in detail should be understood to be implemented in a common manner in the art; any technician familiar with the art can make many possible changes and modifications without departing from the technical solution of the present invention, or modify them into equivalent embodiments with equivalent changes, which does not affect the essential content of the present invention; therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of protection of the technical solution of the present invention.

Claims

1. A visual method for monitoring conveyor belt wear, characterized in that: The method comprises: Receiving first thickness data of the conveyor belt uploaded by the laser sensor array, and updating the data matrix based on the first thickness data; the laser sensor array is installed above the cross section of the conveyor belt, and the detection width is not less than the width of the conveyor belt, and the data matrix contains n groups of original thickness data for representing the covering rubber; Based on the updated data matrix, the corresponding first interpolation matrix is ​​updated; the first interpolation matrix contains N groups of thickness data of the cover glue after interpolation conversion; N and n are positive integers; specifically calculating the row scaling ratio and column scaling ratio between the first interpolation matrix and the data matrix; Based on the row scaling ratio and the column scaling ratio, determining that a target interpolation position in the first interpolation matrix corresponds to an original position in the data matrix; Determine 16 groups of original thickness data corresponding to the original position and the surrounding in the data matrix, and calculate the thickness value of the target interpolation position based on the quadratic cubic interpolation method of the BiCubic basis function; updating the thickness values ​​of all interpolation positions in the first interpolation matrix to obtain a second interpolation matrix; Based on the thickness data in the second interpolation matrix, the RGBA color values ​​used for rendering and display are determined, and the Bitmap image is updated and displayed according to the color value matrix composed of the RGBA color values.

2. The method according to claim 1, characterized in that: The data matrix is ​​an m*n dimensional matrix; The updating of the data matrix based on the first thickness data comprises: Sequentially, based on the second column of thickness data of the data matrix, the first column of thickness data is updated, based on the third column of thickness data, the second column of thickness data is updated, and until the nth column of thickness data updates the n-1th column of thickness data; The first thickness data uploaded by the sensor array is used as the nth column data of the data matrix to update the updated data matrix.

3. The method according to claim 2, characterized in that The first interpolation matrix is ​​an M*N dimensional matrix.

4. The method according to claim 3, characterized in that: The method of determining RGBA color values ​​for rendering and display based on the thickness data in the second interpolation matrix, and updating and displaying the Bitmap image according to the color value matrix composed of the RGBA color values, includes: Determine a target thickness level to which the target thickness value in the second interpolation matrix belongs; different thickness levels correspond to different thickness value intervals; determining the RGB primary colors and transparency of the target pixel position in the color value matrix based on the target thickness level and the target thickness value; the color value matrix and the second interpolation matrix have the same dimension; Update the color value matrix based on the RGBA color value composed of the RGB primary color and the transparency; Performing bitwise operations on the RGBA color values ​​in the color value matrix to obtain image data for image rendering; The image data is converted into a Bitmap image and displayed.

5. The method according to claim 4, characterized in that The determining of the RGB primary colors and transparency of the target pixel position in the color value matrix based on the target thickness level and the target thickness value includes: Determine the RGB primary color value of the target pixel position according to the thickness level; different thickness levels correspond to different RGB primary color values; The maximum thickness value of the thickness interval to which the thickness grade belongs is determined, and the ratio of the target thickness value to the maximum thickness value of the thickness interval is determined as the transparency of the target pixel position.

6. The method according to claim 4, characterized in that When a primary color adjustment instruction is received, determining the RGB primary color and transparency of the target pixel position in the color value matrix based on the target thickness level and the target thickness value includes: When a primary color adjustment instruction is received, determining a target RGB primary color value for image display based on the primary color adjustment instruction, and setting the RGB color values ​​of all pixel positions in the color value matrix to the target RGB primary color value; Based on the target thickness level to which the target thickness value belongs and the total number of thickness levels, the transparency corresponding to the target pixel position is calculated and obtained.

7. The method according to claim 4, characterized in that The step of converting the image data into a Bitmap image and displaying the image includes: Determine the traveling direction and traveling speed of the conveyor belt, and update the length information of the conveyor belt in the Bitmap image according to the frequency of receiving the first thickness data; update the width information of the conveyor belt based on the position information uploaded by the laser sensor array; Image conversion is performed based on the image data and the length information and width information of the conveyor belt, and the Bitmap image is generated and displayed.

8. A conveyor belt wear detection device, characterized in that: The device comprises: A data matrix update module, used for receiving first thickness data of the conveyor belt uploaded by the laser sensor array, and updating the data matrix based on the first thickness data; the laser sensor array is installed above the cross section of the conveyor belt, and the detection width is not less than the width of the conveyor belt, and the data matrix contains n groups of original thickness data for representing the covering rubber; An interpolation matrix update module is used to update the corresponding first interpolation matrix based on the updated data matrix; the first interpolation matrix contains N groups of thickness data of the cover glue after interpolation conversion; N and n are positive integers; specifically calculate the row scaling ratio and column scaling ratio between the first interpolation matrix and the data matrix; Based on the row scaling ratio and the column scaling ratio, determining that a target interpolation position in the first interpolation matrix corresponds to an original position in the data matrix; Determine 16 groups of original thickness data corresponding to the original position and the surrounding in the data matrix, and calculate the thickness value of the target interpolation position based on the quadratic cubic interpolation method of the BiCubic basis function; updating the thickness values ​​of all interpolation positions in the first interpolation matrix to obtain a second interpolation matrix; The image update module is used to determine the RGBA color values ​​used for rendering and display based on the thickness data in the second interpolation matrix, and to update and display the Bitmap image according to the color value matrix composed of the RGBA color values.

9. A computer device, characterized in that: The computer device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement the method for visually monitoring conveyor belt wear as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The readable storage medium stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement the method for visually monitoring conveyor belt wear as described in any one of claims 1 to 7.

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