Steel plate detection system, steel plate detection method and electronic equipment

Abstract

The present invention provides a steel plate detection system, a steel plate detection method and an electronic device, which belong to the field of visual measurement technology. The system includes an image acquisition device, a camera calibration software and a data analysis software. The image acquisition device is used to acquire image data of the upper surface and the lower surface of the steel plate to be tested. The camera calibration software is connected to the image acquisition device and is used to perform data preprocessing on the acquired image data. The data analysis software is connected to the camera calibration software and is used to calculate the thickness standard deviation of the steel plate to be tested according to the preprocessed image data, and evaluate the thickness uniformity of the steel plate to be tested according to the thickness standard deviation. This can at least solve the problems existing in the related art, such as high labor intensity, easy to cause missed detection, inability to adapt to the production environment of high-speed units, low detection accuracy, etc., and is suitable for the scenes of visual measurement and steel plate detection.

Description

Technical Field

[0001] The present invention relates to the field of visual measurement technology, and in particular to a steel plate detection system, a steel plate detection method and electronic equipment. Background Art

[0002] Steel plate surface inspection is mainly used to detect discontinuity defects on the surface of steel plates (such as pits, scratches, etc.). The detection methods include manual experience detection method, non-destructive testing technology based on electromagnetic induction and ultrasound.

[0003] At present, the detection method of large steel plates mainly uses manual visual methods. Due to the requirements of production rhythm, the manual visual method cannot detect the bottom surface of the steel plate, so it cannot fully cover the upper and lower surfaces of the tested steel plate; and the manual visual detection method cannot perform numerical measurement of the discontinuity of the steel plate surface. It is necessary to increase the process and use special instruments to measure the numerical value before performing steel plate grading operations. Therefore, the current detection of large steel plates has problems such as high labor intensity, easy to cause missed detection, inability to adapt to the production environment of high-speed units, and low detection accuracy. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a steel plate detection system, a steel plate detection method and an electronic device in view of the above-mentioned deficiencies in the prior art, so as to at least solve the problems existing in the related technology such as high labor intensity, easy missed detection, inability to adapt to the production environment of high-speed units, and low detection accuracy of manual visual steel plate detection.

[0005] In a first aspect, the present invention provides a steel plate detection system, including an image acquisition device, camera calibration software and data analysis software.

[0006] The image acquisition device is used to acquire image data of the upper surface and the lower surface of the steel plate to be tested. The camera calibration software is connected to the image acquisition device and is used to perform data preprocessing on the acquired image data. The data analysis software is connected to the camera calibration software and is used to calculate the thickness standard deviation of the steel plate to be tested based on the preprocessed image data, and evaluate the thickness uniformity of the steel plate to be tested based on the thickness standard deviation.

[0007] Preferably, the image acquisition device includes an array camera and an acquisition signal controller. The array camera is connected to the acquisition signal controller and is used to acquire image data of the upper surface and the lower surface of the steel plate under test according to the acquisition signal sent by the acquisition signal controller, and output the first coordinate of the sampling point, wherein the first coordinate is in a coordinate system with the position of the array camera as the origin. The acquisition signal controller is provided with an acquisition signal cycle, and the acquisition signal controller is used to send an acquisition signal to the array camera according to the acquisition signal cycle, wherein the acquisition signal cycle is the ratio of the steel plate step length to the steel plate transmission rate.

[0008] Preferably, the array camera includes two groups of linear scan cameras. The two groups of linear scan cameras are respectively fixed at the upper part and the lower part of the detection gate, and respectively maintain a preset shooting distance between the corresponding surface of the steel plate to be tested, wherein the multiple linear scan cameras in the group jointly cover the wide side of the steel plate to be tested by means of a cascaded device.

[0009] Preferably, the image acquisition device further comprises a rate controller and a roller bed. The rate controller is connected to the roller bed, and the rate controller is provided with a steel plate transmission rate, and is used to control the rotation speed of the roller bed according to the steel plate transmission rate. The roller bed is used to place the steel plate to be measured and to transmit the steel plate to be measured by rotating.

[0010] Preferably, the camera calibration software includes a coordinate conversion module. The coordinate conversion module is used to convert the first coordinate of the sampling point output by each camera into the world coordinate system according to the relative position relationship of each camera in the array camera to obtain the converted acquisition data, wherein the origin O of the world coordinate system is a corner of the steel plate to be measured, its X-axis is parallel to the array camera composed of each camera, its Y-axis is parallel to the transmission direction of the steel plate to be measured, and its Z-axis is perpendicular to the XOY plane. The converted acquisition data is: Where p = u represents the upper surface of the steel plate under test, p = d represents the lower surface of the steel plate under test, t represents the sampling time, i = j·N+k, j is the camera index, i takes values ​​of 0, 1, 2, ... A, A = M·N+N M Represents the total number of sampling points on any surface of the steel plate at each sampling moment, N M ≤M represents the number of sampling points of the last camera that photographs any surface of the tested steel plate.

[0011] Preferably, the data analysis software includes a first calculation module and a second calculation module. The first calculation module is used to calculate the steel plate thickness of each sampling point of the measured steel plate according to the following formula:

[0012]

[0013] in, The data collected for the upper surface of the steel plate under test is The second calculation module is connected to the first calculation module and is used to calculate the thickness standard deviation of the steel plate under test according to the thickness of the steel plate and the following formula:

[0014]

[0015] in, Indicates the average thickness of the steel plate being tested.

[0016] Preferably, the data analysis software further comprises an evaluation module. The evaluation module is connected to the second calculation module and is used to evaluate the uniformity of the thickness of the steel plate under test in response to the thickness standard deviation being less than a preset threshold value, and to evaluate the non-uniformity of the thickness of the steel plate under test in response to the thickness standard deviation being greater than or equal to a preset threshold value.

[0017] In a second aspect, the present invention also provides a steel plate detection method, comprising: collecting image data of the upper surface and the lower surface of the steel plate to be tested; performing data preprocessing on the collected image data; calculating the thickness standard deviation of the steel plate to be tested based on the preprocessed image data, and evaluating the thickness uniformity of the steel plate to be tested based on the thickness standard deviation.

[0018] Preferably, the acquisition of image data of the upper surface and the lower surface of the steel plate under test specifically includes: using an array camera to acquire image data of the upper surface and the lower surface of the steel plate under test according to an acquisition signal period, and outputting a first coordinate of a sampling point, wherein the first coordinate is in a coordinate system with the position of the array camera as the origin. The array camera includes two groups of linear scanning cameras, which respectively acquire image data of the upper surface and the lower surface of the steel plate under test, and the multiple linear scanning cameras in the group jointly cover the wide side of the steel plate under test by means of a device cascade.

[0019] Preferably, the collected image data is preprocessed, specifically including: according to the relative position relationship of each camera in the array camera, the first coordinate of the sampling point output by each camera is converted into the world coordinate system to obtain the converted collected data, wherein the origin O of the world coordinate system is a corner of the steel plate to be measured, its X-axis is parallel to the array camera composed of each camera, its Y-axis is parallel to the transmission direction of the steel plate to be measured, and its Z-axis is perpendicular to the XOY plane. The converted collected data is: Where p = u represents the upper surface of the steel plate under test, p = d represents the lower surface of the steel plate under test, t represents the sampling time, i = j·N+k, j is the camera index, i takes values ​​of 0, 1, 2, ... A, A = M·N+N M Represents the total number of sampling points on any surface of the steel plate at each sampling moment, N M ≤M represents the number of sampling points of the last camera that photographs any surface of the tested steel plate.

[0020] Preferably, calculating the thickness standard deviation of the measured steel plate according to the preprocessed image data specifically includes: calculating the steel plate thickness of each sampling point of the measured steel plate according to the following formula:

[0021]

[0022] in, The data collected for the upper surface of the steel plate under test is The data collected from the lower surface of the steel plate under test is used to calculate the thickness standard deviation of the steel plate under test according to the thickness of the steel plate and the following formula:

[0023]

[0024] in, Indicates the average thickness of the steel plate being tested.

[0025] Preferably, the thickness uniformity of the measured steel plate is evaluated according to the thickness standard deviation, specifically including: in response to the thickness standard deviation being less than a preset threshold, evaluating the thickness of the measured steel plate as uniform; in response to the thickness standard deviation being greater than or equal to the preset threshold, evaluating the thickness of the measured steel plate as non-uniform.

[0026] In a third aspect, the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the steel plate detection method as described in the second aspect.

[0027] The present invention provides a steel plate detection system, a steel plate detection method and an electronic device. The image acquisition device in the steel plate detection system is used to respectively acquire image data of the upper and lower surfaces of the steel plate to be detected, the camera calibration software is used to preprocess the acquired data, and the data analysis software is used to calculate the thickness standard deviation of the steel plate according to the preprocessed data to evaluate the thickness uniformity of the steel plate. This detection system for flatness and defects of steel plates in industrial production based on machine vision detection has the characteristics of higher automation, comprehensive detection, adaptability to the production environment of high-speed units, and high detection accuracy compared to manual visual methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a structural schematic diagram of a steel plate detection system according to Embodiment 1 of the present invention;

[0029] Figure 2 A schematic diagram of camera coverage in accordance with Embodiment 1 of the present invention;

[0030] Figure 3 A schematic diagram of a world coordinate system according to Embodiment 1 of the present invention;

[0031] Figure 4 A schematic flow chart of a steel plate detection method according to Embodiment 2 of the present invention;

[0032] Figure 5 This is a schematic diagram of the structure of an electronic device according to Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the technical solution of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0034] It should be understood that the specific embodiments and drawings described herein are only used to explain the present invention rather than to limit the present invention.

[0035] It can be understood that, in the absence of conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other.

[0036] It can be understood that, for the convenience of description, the drawings of the present invention only show the parts related to the present invention, while the parts irrelevant to the present invention are not shown in the drawings.

[0037] It can be understood that each unit and module involved in the embodiments of the present invention may correspond to only one physical structure, or may be composed of multiple physical structures, or multiple units and modules may be integrated into one physical structure.

[0038] It can be understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of the present invention may occur in an order different from that marked in the drawings.

[0039] It is understood that the flowcharts and block diagrams of the present invention illustrate the possible architectures, functions, and operations of the systems, devices, equipment, and methods according to the various embodiments of the present invention. Each box in the flowchart or block diagram may represent a unit, module, program segment, or code, which contains executable instructions for implementing the specified functions. Moreover, each box or combination of boxes in the block diagram and flowchart may be implemented by a hardware-based system that implements the specified functions, or may be implemented by a combination of hardware and computer instructions.

[0040] It can be understood that the units and modules involved in the embodiments of the present invention can be implemented by software or hardware. For example, the units and modules can be located in a processor.

[0041] Embodiment 1:

[0042] like Figure 1 As shown, this embodiment provides a steel plate detection system, which can be applied to steel plate production scenarios of high-speed units or other steel plate detection scenarios. The steel plate detection system includes an image acquisition device 11, a camera calibration software 12 and a data analysis software 13.

[0043] The image acquisition device 11 is used to acquire image data of the upper surface and the lower surface of the steel plate under test.

[0044] The camera calibration software 12 is connected to the image acquisition device 11 and is used for performing data preprocessing on the acquired image data.

[0045] The data analysis software 13 is connected to the camera calibration software 12 and is used to calculate the thickness standard deviation of the measured steel plate according to the preprocessed image data, and evaluate the thickness uniformity of the measured steel plate according to the thickness standard deviation.

[0046] Optionally, the image acquisition device includes an array camera and an acquisition signal controller. The array camera is connected to the acquisition signal controller, and is used to acquire image data of the upper and lower surfaces of the steel plate under test according to the acquisition signal sent by the acquisition signal controller, and output the first coordinate of the sampling point, wherein the first coordinate is in a coordinate system with the position of the array camera as the origin. The acquisition signal controller is provided with an acquisition signal cycle, and the acquisition signal controller is used to send an acquisition signal to the array camera according to the acquisition signal cycle, wherein the acquisition signal cycle is the ratio of the steel plate step length L (unit: meter) to the steel plate transmission rate S (unit: meter / second), that is, the time interval for the acquisition signal controller to send the acquisition signal is: τ=LS (unit: second), that is, the array camera takes and acquires data once every time interval τ.

[0047] Specifically, the array camera includes two groups of linear scanning cameras. The two groups of linear scanning cameras are respectively fixed at the upper part and the lower part of the detection gate, and respectively maintain a preset shooting distance between the corresponding surface of the steel plate to be tested, wherein the multiple linear scanning cameras in the group jointly cover the wide side of the steel plate to be tested through a cascaded device mode.

[0048] In this embodiment, Figure 1 As shown in the figure, a set of three-dimensional (3D) linear scanning cameras are installed at the upper and lower parts of the detection gate (i.e., above and below the steel plate to be tested) to collect image data, and the upper (or lower) cameras are cascaded to cover the entire width of the steel plate to be tested. Figure 2 As shown, each camera covers a straight line range of a certain length, and the six cameras cover the wide side of the steel plate under test through a cascaded device. The number of cameras is determined by the width of the steel plate under test (or other object under test) and the scanning range of the camera (for example, when the image data acquisition coverage width of each 3D camera is 0.45 meters and the width of the steel plate under test is 4.2 meters, a total of 18 to 20 3D cameras are required to cover the width of the upper and lower surfaces of the entire steel plate under test through a cascaded device). When the resolutions of the cascaded cameras are different, according to the different resolutions of the cameras, each camera obtains a set of coordinates of the pixel points of the steel plate under test within the coverage range, and outputs the first coordinate of the steel plate under test as a coordinate system based on the position of each camera as the origin. The first coordinate is written as: Wherein p=u or p=d, u represents the camera above the upper surface of the steel plate under test, d represents the camera below the lower surface of the steel plate under test, t=0,1,2,...T represents the sampling time, j=0,1,2,...M represents the camera index ID, k=0,1,2,...N represents the index ID of each camera collecting N sampling points each time, all cameras are uniformly controlled by the acquisition signal controller, when the acquisition signal controller sends out the acquisition signal, all cameras start shooting at the same time and collect the image data of the steel plate under test.

[0049] Optionally, the image acquisition device further includes a rate controller and a roller bed. The rate controller is connected to the roller bed, and a steel plate transmission rate is set in the rate controller, which is used to control the rotation speed of the roller bed according to the steel plate transmission rate. The roller bed is used to place the steel plate to be tested and to transmit the steel plate to be tested by rotating. In this embodiment, the rate controller and the acquisition signal controller are coordinated by the rate matching software control.

[0050] Data preprocessing includes data cleaning, data integration, data transformation, and data reduction. In this embodiment, data transformation is used to illustrate the detailed process.

[0051] Specifically, the camera calibration software includes a coordinate conversion module.

[0052] A coordinate conversion module is used to convert the first coordinate of the sampling point output by each camera into the world coordinate system according to the relative position relationship of each camera in the array camera to obtain the converted acquisition data. Figure 3 As shown in the figure, the origin O of the world coordinate system is a corner of the steel plate to be measured (such as Figure 1 One corner of the object to be inspected is the unified coordinate origin O), its X-axis is parallel to the array camera composed of each camera, its Y-axis is parallel to the transmission direction of the steel plate to be inspected, and its Z-axis is perpendicular to the XOY plane. The converted collected data is: Where p = u represents the upper surface of the steel plate under test, p = d represents the lower surface of the steel plate under test, t represents the sampling time, i = j·N+k, j is the camera index, i takes values ​​of 0, 1, 2, ... A, A = M·N+N M Represents the total number of sampling points on any surface of the steel plate at each sampling moment, N M ≤M represents the number of sampling points of the last camera that photographs any surface of the steel plate under test. It should be noted that the origin of the world coordinate system is not limited to a corner of the steel plate under test in this embodiment. By converting the data collected by each camera into the collected data in the same coordinate system, the subsequent calculation of the thickness of the steel plate under test is facilitated and the accuracy of the calculation result is guaranteed.

[0053] Optionally, the data analysis software includes a first calculation module and a second calculation module.

[0054] The first calculation module is used to calculate the steel plate thickness of each sampling point of the tested steel plate according to the following formula:

[0055]

[0056] in, The data collected for the upper surface of the steel plate under test is The data collected are from the lower surface of the steel plate under test.

[0057] The second calculation module is connected to the first calculation module and is used to calculate the thickness standard deviation of the measured steel plate according to the thickness of the steel plate and the following formula:

[0058]

[0059] in, Indicates the average thickness of the steel plate being tested.

[0060] Optionally, the data analysis software further includes an evaluation module. The evaluation module is connected to the second calculation module and is used to evaluate the uniformity of the thickness of the steel plate being tested in response to the thickness standard deviation being less than a preset threshold, and to evaluate the unevenness of the thickness of the steel plate being tested in response to the thickness standard deviation being greater than or equal to a preset threshold. The standard deviation σ of the steel plate thickness characterizes the uniformity of the thickness of the steel plate being tested, and the smaller the value, the more uniform the thickness of the steel plate. Measuring the uniformity of thickness by the thickness standard deviation is reasonable and the evaluation is effective.

[0061] In the steel plate detection system of this embodiment, the image acquisition device (such as an array camera) is used to respectively acquire image data of the upper and lower surfaces of the steel plate to be tested, the camera calibration software is used to preprocess the acquired data, and the data analysis software is used to calculate the thickness standard deviation of the steel plate based on the preprocessed data to evaluate the thickness uniformity of the steel plate. And it is used to coordinate the acquisition signal controller to control the acquisition cycle and the rate controller to control the rotation speed of the roller bed to achieve automatic detection of the steel plate to be tested. This steel plate detection system based on machine vision detection of the flatness and defects of steel plates in industrial production has the characteristics of higher degree of automation, comprehensive detection, adaptability to the production environment of high-speed units, and high detection accuracy compared to the manual visual method. Further, the camera calibration software is used to convert the data acquired by each camera into the acquisition data in the same coordinate system, which is convenient for the subsequent calculation of the thickness of the steel plate to be tested and ensures the accuracy of the calculation results. In addition, the data analysis software is used to measure the uniformity of the thickness of the steel plate to be tested using the thickness standard deviation, which is reasonable and effective in evaluation.

[0062] Embodiment 2:

[0063] like Figure 4 As shown, this embodiment provides a steel plate detection method, comprising:

[0064] Step 401, collecting image data of the upper surface and the lower surface of the steel plate under test.

[0065] Step 402: preprocess the collected image data.

[0066] Step 403, calculating the thickness standard deviation of the measured steel plate according to the preprocessed image data, and evaluating the thickness uniformity of the measured steel plate according to the thickness standard deviation.

[0067] Optionally, the acquisition of image data of the upper and lower surfaces of the steel plate under test specifically includes: using an array camera to acquire image data of the upper and lower surfaces of the steel plate under test according to an acquisition signal period, and outputting the first coordinate of the sampling point, wherein the first coordinate is in a coordinate system with the position of the array camera as the origin, and the array camera includes two groups of linear scanning cameras, the two groups of linear scanning cameras respectively acquire image data of the upper and lower surfaces of the steel plate under test, and the multiple linear scanning cameras in the group jointly cover the wide side of the steel plate under test through a cascaded device. The acquisition signal period is the ratio of the steel plate step length to the steel plate transmission rate. Among them, the rate controller is provided with a steel plate transmission rate, which is used to control the rotation speed of the roller bed according to the steel plate transmission rate; the roller bed is used to place the steel plate under test, and to transmit the steel plate under test by rotating to obtain the steel plate step length.

[0068] Preferably, the collected image data is preprocessed, specifically including: according to the relative position relationship of each camera in the array camera, the first coordinate of the sampling point output by each camera is converted into the world coordinate system to obtain the converted collected data, wherein the origin O of the world coordinate system is a corner of the steel plate to be measured, its X-axis is parallel to the array camera composed of each camera, its Y-axis is parallel to the transmission direction of the steel plate to be measured, and its Z-axis is perpendicular to the XOY plane. The converted collected data is: Where p = u represents the upper surface of the steel plate under test, p = d represents the lower surface of the steel plate under test, t represents the sampling time, i = j·N+k, j is the camera index, i takes values ​​of 0, 1, 2, ... A, A = M·N+N M Represents the total number of sampling points on any surface of the steel plate at each sampling moment, N M ≤M represents the number of sampling points of the last camera that photographs any surface of the tested steel plate.

[0069] Optionally, calculating the thickness standard deviation of the measured steel plate according to the preprocessed image data specifically includes: calculating the steel plate thickness of each sampling point of the measured steel plate according to the following formula:

[0070]

[0071] in, The data collected for the upper surface of the steel plate under test is Collect data of the lower surface of the steel plate under test;

[0072] Calculate the thickness standard deviation of the steel plate according to the steel plate thickness and the following formula:

[0073]

[0074] in, Indicates the average thickness of the steel plate being tested.

[0075] Optionally, the thickness uniformity of the steel plate under test is evaluated according to the thickness standard deviation, specifically including: in response to the thickness standard deviation being less than a preset threshold, evaluating the thickness uniformity of the steel plate under test; in response to the thickness standard deviation being greater than or equal to the preset threshold, evaluating the thickness non-uniformity of the steel plate under test. The steel plate thickness standard deviation σ characterizes the uniformity of the thickness of the steel plate under test, and the smaller the value, the more uniform the thickness of the steel plate.

[0076] Embodiment 3:

[0077] like Figure 5 As shown, this embodiment provides an electronic device, including a memory 51 and a processor 52, wherein the memory 51 stores a computer program, and the processor 52 is configured to run the computer program to implement the steel plate detection method as described in Example 2.

[0078] The steel plate detection method of Example 2 and the electronic device of Example 3 respectively collect image data of the upper and lower surfaces of the steel plate to be tested, pre-process the collected data, and calculate the thickness standard deviation of the steel plate based on the pre-processed data to evaluate the thickness uniformity of the steel plate. And the acquisition cycle is automatically controlled by the acquisition signal controller, and the rotation speed of the roller bed is automatically controlled by the rate controller to realize automatic detection of the steel plate to be tested. This steel plate detection system based on machine vision detection of the flatness and defects of steel plates in industrial production has a higher degree of automation, comprehensive detection, adaptability to the production environment of high-speed units, and high detection accuracy compared to the manual visual method. Furthermore, by converting the data collected by each camera into the collected data in the same coordinate system, it is convenient to calculate the thickness of the steel plate to be tested and ensure the accuracy of the calculation results. In addition, the thickness standard deviation is used to measure the uniformity of the thickness of the steel plate to be tested, which is reasonable and effective in evaluation.

[0079] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present invention, but the present invention is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A steel plate detection system, characterized in that: Including image acquisition device, camera calibration software and data analysis software, The image acquisition device is used to acquire image data of the upper and lower surfaces of the steel plate being tested. The camera calibration software is connected to the image acquisition device and is used to perform data preprocessing on the acquired image data. Data analysis software, connected to the camera calibration software, for calculating the thickness standard deviation of the steel plate under test according to the preprocessed image data, and evaluating the thickness uniformity of the steel plate under test according to the thickness standard deviation; The image acquisition device includes an array camera and an acquisition signal controller. An array camera is connected to the acquisition signal controller, and is used to acquire image data of the upper surface and the lower surface of the steel plate under test according to the acquisition signal sent by the acquisition signal controller, and output the first coordinate of the sampling point, wherein the first coordinate is in a coordinate system with the position of the array camera as the origin, The acquisition signal controller is provided with an acquisition signal cycle, and the acquisition signal controller is used to send an acquisition signal to the array camera according to the acquisition signal cycle, wherein the acquisition signal cycle is a ratio of the steel plate step length to the steel plate transmission rate; The array camera includes two groups of linear scan cameras, Two groups of linear scanning cameras are respectively fixed at the upper and lower parts of the detection gate, and respectively maintain a preset shooting distance with the corresponding surface of the steel plate to be tested, wherein multiple linear scanning cameras in the group jointly cover the wide side of the steel plate to be tested through a cascaded device mode, and each camera obtains a set of coordinates of pixel points of the steel plate to be tested within the coverage range, and outputs the first coordinate of the steel plate to be tested as a coordinate system based on the position of each camera as the origin. The first coordinate is written as: Where p=u or p=d, u represents the camera above the surface of the steel plate under test, d represents the camera below the lower surface of the steel plate under test, t=0,1,2,...T represents the sampling time, j=0,1,2,...M represents the camera index, k=1,2,...N represents the index of each camera collecting N sampling points each time; The camera calibration software includes a coordinate conversion module, The coordinate conversion module is used to convert the first coordinate of the sampling point output by each camera into the world coordinate system according to the relative position relationship of each camera in the array camera to obtain the converted acquisition data. Among them, the origin O of the world coordinate system is a corner of the steel plate to be measured, its X-axis is parallel to the array camera composed of each camera, its Y-axis is parallel to the transmission direction of the steel plate to be measured, and its Z-axis is perpendicular to the XOY plane. The converted collected data is: Where p = u represents the upper surface of the steel plate under test, p = d represents the lower surface of the steel plate under test, t represents the sampling time, i = j·N+k, j is the camera index, i takes values ​​of 1, 2, ... A, A = M·N+N M Represents the total number of sampling points on any surface of the steel plate at each sampling moment, N M ≤M represents the number of sampling points of the last camera that photographs any surface of the tested steel plate; The data analysis software includes a first calculation module and a second calculation module. The first calculation module is used to calculate the steel plate thickness of each sampling point of the tested steel plate according to the following formula: in, The data collected for the upper surface of the steel plate under test is The data collected for the lower surface of the steel plate under test is The second calculation module is connected to the first calculation module and is used to calculate the thickness standard deviation of the measured steel plate according to the thickness of the steel plate and the following formula: in, Indicates the average thickness of the steel plate being tested.

2. The steel plate detection system according to claim 1, characterized in that: The image acquisition device also includes a rate controller and a rolling bed, A rate controller is connected to the roller bed, and the rate controller is provided with a steel plate transmission rate, and is used to control the rotation speed of the roller bed according to the steel plate transmission rate. The roller bed is used to place the steel plate to be tested and to convey the steel plate to be tested by rotating.

3. The steel plate detection system according to claim 1, characterized in that: The data analysis software also includes an evaluation module. The evaluation module is connected to the second calculation module and is used to evaluate the uniformity of the thickness of the tested steel plate in response to the thickness standard deviation being less than a preset threshold, and to evaluate the non-uniformity of the thickness of the tested steel plate in response to the thickness standard deviation being greater than or equal to the preset threshold.

4. A steel plate detection method, characterized in that: include: Collect image data of the upper and lower surfaces of the steel plate under test; Performing data preprocessing on the collected image data; Calculate the thickness standard deviation of the measured steel plate according to the preprocessed image data, and evaluate the thickness uniformity of the measured steel plate according to the thickness standard deviation; The collecting of image data of the upper surface and the lower surface of the steel plate under test specifically includes: An array camera is used to collect image data of the upper surface and the lower surface of the steel plate under test according to the acquisition signal cycle, and a first coordinate of the sampling point is output, wherein the first coordinate is in a coordinate system with the position of the array camera as the origin; The array camera includes two groups of linear scan cameras, which respectively collect image data of the upper and lower surfaces of the steel plate under test, and multiple linear scan cameras in the group jointly cover the wide side of the steel plate under test through a cascaded device. Each camera obtains a set of coordinates of pixel points of the steel plate under test within the coverage range, and outputs the first coordinate of the steel plate under test as a coordinate system based on the position of each camera as the origin. The first coordinate is written as: Where p=u or p=d, u represents the camera above the surface of the steel plate under test, d represents the camera below the lower surface of the steel plate under test, t=0,1,2,...T represents the sampling time, j=0,1,2,...M represents the camera index, k=1,2,...N represents the index of each group of cameras collecting N sampling points each time; The collected image data is preprocessed, specifically including: According to the relative position relationship of each camera in the array camera, the first coordinate of the sampling point output by each camera is converted to the world coordinate system to obtain the converted acquisition data. Among them, the origin O of the world coordinate system is a corner of the steel plate to be measured, its X-axis is parallel to the array camera composed of each camera, its Y-axis is parallel to the transmission direction of the steel plate to be measured, and its Z-axis is perpendicular to the XOY plane. The converted collected data is: Where p = u represents the upper surface of the steel plate under test, p = d represents the lower surface of the steel plate under test, t represents the sampling time, i = j·N+k, j is the camera index, i takes values ​​of 1, 2, ... A, A = M·N+N M Represents the total number of sampling points on any surface of the steel plate at each sampling moment, N M ≤M represents the number of sampling points of the last camera that photographs any surface of the tested steel plate; The thickness standard deviation of the steel plate under test is calculated based on the preprocessed image data, including: The steel plate thickness at each sampling point of the tested steel plate is calculated according to the following formula: in, The data collected for the upper surface of the steel plate under test is Collect data of the lower surface of the steel plate under test; Calculate the thickness standard deviation of the steel plate according to the steel plate thickness and the following formula: in, Indicates the average thickness of the steel plate being tested.

5. The steel plate detection method according to claim 4, characterized in that: The thickness uniformity of the steel plate under test is evaluated according to the thickness standard deviation, including: In response to the thickness standard deviation being less than a preset threshold, evaluating the thickness uniformity of the tested steel plate; In response to the thickness standard deviation being greater than or equal to a preset threshold, the thickness of the tested steel plate is evaluated to be non-uniform.

6. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the steel plate detection method according to claim 4 or 5.

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