CN115791830B - Steel plate detection system, steel plate detection method and electronic equipment - Google Patents
Steel plate detection system, steel plate detection method and electronic equipment Download PDFInfo
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- G—PHYSICS
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- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
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- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/01—Arrangements or apparatus for facilitating the optical investigation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
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Abstract
本发明提供一种钢板检测系统、钢板检测方法及电子设备，属于视觉测量技术领域。所述系统包括图像采集装置、相机标定软件和数据分析软件。图像采集装置，用于采集被测钢板的上表面和下表面的图像数据，相机标定软件，与所述图像采集装置连接，用于对所采集的图像数据进行数据预处理，数据分析软件，与所述相机标定软件连接，用于根据预处理后的图像数据计算被测钢板的厚度标准差，并根据厚度标准差评价被测钢板的厚度均匀性。以至少解决相关技术中存在的人工目视钢板检测人工劳动强度大、易造成漏检、无法适应高速机组的生产环境、检测精度低等问题，适应于视觉测量、钢板检测的场景。
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
The invention relates to the technical field of vision measurement, in particular to a steel plate detection system, a steel plate detection method and electronic equipment.
Background
The detection method of the surface of the steel plate is mainly used for detecting discontinuous defects (such as pits, scratches and the like) on the surface of the steel plate, and comprises a manual experience detection method and a nondestructive detection technology based on electromagnetic induction and ultrasound.
At present, the detection means of the large steel plate mainly adopts an artificial visual method, is limited by the requirement of production beats, and cannot detect the bottom surface of the steel plate, so that the upper surface and the lower surface of the detected steel plate cannot be fully covered, and the artificial visual detection method cannot carry out numerical measurement on the surface discontinuity of the steel plate, and needs to increase working procedures and carry out steel plate grading operation after measuring the numerical values by using a special instrument.
Disclosure of Invention
The invention aims to solve the technical problems of the prior art, and provides a steel plate detection system, a steel plate detection method and electronic equipment, so as to at least solve the problems of high labor intensity, easy missed detection, incapability of adapting to the production environment of a high-speed unit, low detection precision and the like of manual visual steel plate detection in the related art.
In a first aspect, the invention provides a steel plate detection system, which comprises an image acquisition device, camera calibration software and data analysis software.
And the image acquisition device is used for acquiring image data of the upper surface and the lower surface of the detected steel plate. And the camera calibration software is connected with the image acquisition device and is used for carrying out data preprocessing on the acquired image data. The data analysis software is connected with the camera calibration software and is used for 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.
Preferably, the image acquisition device comprises an array camera and an acquisition signal controller. The array camera is connected with the acquisition signal controller and is used for acquiring image data of the upper surface and the lower surface of the detected steel plate according to the acquisition signal sent by the acquisition signal controller and outputting first coordinates of sampling points, wherein the first coordinates are in a coordinate system taking the position of the array camera as an origin. The acquisition signal controller is provided with an acquisition signal period, and is used for sending an acquisition signal to the array camera according to the acquisition signal period, wherein the acquisition signal period is the ratio of the stepping length of the steel plate to the transmission rate of the steel plate.
Preferably, the array camera comprises two sets of linear scanning cameras. The two groups of linear scanning cameras are used for being respectively and fixedly arranged on the upper part and the lower part of the detection gate, and keeping a preset shooting distance with the corresponding surface of the detected steel plate, wherein the plurality of linear scanning cameras in the groups jointly cover the broadside of the detected steel plate in a device cascading mode.
Preferably, the image acquisition device further comprises a rate controller and a roller bed. And the speed controller is connected with the rolling machine, is provided with a steel plate transmission speed and is used for controlling the rotating speed of the rolling machine according to the steel plate transmission speed. And the rolling machine is used for placing the steel plate to be tested and conveying the steel plate to be tested through rotation.
Preferably, the camera calibration software includes a coordinate conversion module. The coordinate conversion module is used for converting a first coordinate of a sampling point output by each camera into a world coordinate system according to the relative position relation of each camera in the array camera to obtain converted acquisition data, wherein an origin O of the world coordinate system is one corner of a detected steel plate, an X axis of the origin O is parallel to the array camera formed by each camera, a Y axis of the origin O is parallel to the conveying direction of the detected steel plate, a Z axis of the origin O is perpendicular to an XOY plane, and the converted acquisition data are: Where p=u denotes the upper surface of the measured steel sheet, p=d denotes the lower surface of the measured steel sheet, t denotes the sampling time, i=j·n+k, j is the camera index, i takes values of 0,1,2,.. a=m·n+n M represents the total number of sampling points of any surface of the measured steel sheet at each sampling time, and N M +.m represents the number of sampling points of the last camera that photographed any surface of the measured steel sheet.
Preferably, the data analysis software includes a first computing module and a second computing module. The first calculation module is used for calculating the thickness of the steel plate at each sampling point of the measured steel plate according to the following formula:
Wherein, For the acquisition data of the upper surface of the steel plate to be tested,The data are collected for the lower surface of the steel plate to be tested. The second calculation module is connected with the first calculation module and is used for calculating the thickness standard deviation of the measured steel plate according to the thickness of the steel plate and the following formula:
Wherein, The average thickness of the steel sheet to be measured is shown.
Preferably, the data analysis software further comprises an evaluation module. The evaluation module is connected with the second calculation module and is used for evaluating the uniformity of the thickness of the measured steel plate in response to the thickness standard deviation being smaller than a preset threshold value and evaluating the non-uniformity of the thickness of the measured steel plate in response to the thickness standard deviation being larger than or equal to the preset threshold value.
The invention further provides a steel plate detection method, which comprises the steps of collecting image data of the upper surface and the lower surface of the steel plate to be detected, carrying out data preprocessing on the collected image data, calculating the thickness standard deviation of the steel plate to be detected according to the preprocessed image data, and evaluating the thickness uniformity of the steel plate to be detected according to the thickness standard deviation.
Preferably, the method for acquiring the image data of the upper surface and the lower surface of the steel plate to be measured specifically comprises the steps of acquiring the image data of the upper surface and the lower surface of the steel plate to be measured by adopting an array camera according to a signal acquisition period, and outputting first coordinates of sampling points, wherein the first coordinates are in a coordinate system taking the position of the array camera as an origin. The array camera comprises two groups of linear scanning cameras, the two groups of linear scanning cameras respectively collect image data of the upper surface and the lower surface of the steel plate to be tested, and the plurality of linear scanning cameras in the groups jointly cover the wide edge of the steel plate to be tested in a cascade mode of equipment.
The method specifically comprises the steps of converting a first coordinate of a sampling point output by each camera into a world coordinate system according to the relative position relation of each camera in the array camera to obtain converted acquisition data, wherein an origin O of the world coordinate system is one corner of a detected steel plate, an X axis of the origin O is parallel to the array camera formed by each camera, a Y axis of the origin O is parallel to the conveying direction of the detected steel plate, a Z axis of the origin O is perpendicular to an XOY plane, and the converted acquisition data are: Where p=u denotes the upper surface of the measured steel sheet, p=d denotes the lower surface of the measured steel sheet, t denotes the sampling time, i=j·n+k, j is the camera index, i takes values of 0,1,2,.. a=m·n+n M represents the total number of sampling points of any surface of the measured steel sheet at each sampling time, and N M +.m represents the number of sampling points of the last camera that photographed any surface of the measured steel sheet.
Preferably, the thickness standard deviation of the measured steel plate is calculated according to the preprocessed image data, and specifically comprises the steps of calculating the thickness of the steel plate at each sampling point of the measured steel plate according to the following formula:
Wherein, For the acquisition data of the upper surface of the steel plate to be tested,For the collected data of the lower surface of the steel plate to be tested, calculating the thickness standard deviation of the steel plate to be tested according to the thickness of the steel plate and the following formula:
Wherein, The average thickness of the steel sheet to be measured is shown.
Preferably, the thickness uniformity of the steel plate to be measured is evaluated according to the thickness standard deviation, and specifically comprises the steps of evaluating the thickness uniformity of the steel plate to be measured in response to the thickness standard deviation being smaller than a preset threshold value and evaluating the thickness non-uniformity of the steel plate to be measured in response to the thickness standard deviation being greater than or equal to the preset threshold value.
In a third aspect, the present invention also provides an electronic device comprising a memory in which a computer program is stored and a processor arranged to run the computer program to implement the method of detecting a steel sheet as described in the second aspect.
The invention provides a steel plate detection system, a steel plate detection method and electronic equipment, wherein an image acquisition device in the steel plate detection system is used for respectively acquiring image data of the upper surface and the lower surface of a detected steel plate, camera calibration software is used for preprocessing the acquired data, and data analysis software is used for calculating the thickness standard deviation of the steel plate according to the preprocessed data so as to evaluate the thickness uniformity of the steel plate. Compared with an artificial visual method, the detection system for detecting the flatness and flaws of the steel plate in industrial production based on machine vision has the characteristics of higher automation degree, comprehensive detection, suitability for the production environment of a high-speed unit and high detection precision.
Drawings
Fig. 1 is a schematic structural diagram of a steel plate detection system according to embodiment 1 of the present invention;
Fig. 2 is a schematic view of a camera coverage area according to embodiment 1 of the present invention;
FIG. 3 is a diagram of a world coordinate system according to embodiment 1 of the present invention;
FIG. 4 is a flow chart of a steel plate detection method according to embodiment 2 of the present invention;
Fig. 5 is a schematic structural diagram of an electronic device according to embodiment 3 of the present invention.
Detailed Description
In order to make the technical scheme of the present invention better understood by those skilled in the art, the following detailed description of the embodiments of the present invention will be given with reference to the accompanying drawings.
It is to be understood that the specific embodiments and figures described herein are merely illustrative of the invention, and are not limiting of the invention.
It is to be understood that the various embodiments of the invention and the features of the embodiments may be combined with each other without conflict.
It is to be understood that only the portions relevant to the present invention are shown in the drawings for convenience of description, and the portions irrelevant to the present invention are not shown in the drawings.
It should be understood that each unit and module in the embodiments of the present invention may correspond to only one physical structure, may be formed by a plurality of physical structures, or may be integrated into one physical structure.
It will be appreciated that, without conflict, the functions and steps noted in the flowcharts and block diagrams of the present invention may occur out of the order noted in the figures.
It is to be understood that the flowcharts and block diagrams of the present invention illustrate the architecture, functionality, and operation of possible implementations of systems, apparatuses, devices, methods according to various embodiments of the present invention. Where each block in the flowchart or block diagrams may represent a unit, module, segment, code, or the like, which comprises executable instructions for implementing the specified functions. Moreover, each block or combination of blocks in the block diagrams and flowchart illustrations can be implemented by hardware-based systems that perform the specified functions, or by combinations of hardware and computer instructions.
It should be understood that the units and modules related in the embodiments of the present invention may be implemented by software, or may be implemented by hardware, for example, the units and modules may be located in a processor.
Example 1:
As shown in fig. 1, the present embodiment provides a steel plate detection system, which can be applied to a steel plate production scene of a high-speed unit or other steel plate detection scenes. The steel plate detection system comprises an image acquisition device 11, camera calibration software 12 and data analysis software 13.
And the image acquisition device 11 is used for acquiring image data of the upper surface and the lower surface of the steel plate to be tested.
The camera calibration software 12 is connected with the image acquisition device 11 and is used for carrying out data preprocessing on the acquired image data.
The data analysis software 13 is connected with the camera calibration software 12 and is used for 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.
Optionally, the image acquisition device comprises an array camera and an acquisition signal controller. The array camera is connected with the acquisition signal controller and is used for acquiring image data of the upper surface and the lower surface of the detected steel plate according to the acquisition signal sent by the acquisition signal controller and outputting first coordinates of the sampling points, wherein the first coordinates are in a coordinate system taking the position of the array camera as an origin. The acquisition signal controller is internally provided with an acquisition signal period, and the acquisition signal controller is used for sending an acquisition signal to the array camera according to the acquisition signal period, wherein the acquisition signal period is the ratio of the step length L (unit: m) of the steel plate to the transmission rate S (unit: m/S) of the steel plate, namely the time interval of sending the acquisition signal by the acquisition signal controller is tau=LS (unit: S), that is, the array camera shoots and acquires data once every interval time tau.
Specifically, the array camera includes two sets of linear scanning cameras. The two groups of linear scanning cameras are used for being respectively and fixedly arranged on the upper part and the lower part of the detection gate, and keeping a preset shooting distance with the corresponding surface of the detected steel plate, wherein the plurality of linear scanning cameras in the groups jointly cover the broadside of the detected steel plate in a device cascading mode.
In this embodiment, as shown in fig. 1, a group of three-dimensional (3D) linear scanning cameras are respectively installed at the upper and lower parts of the detection gate (i.e., above and below the steel plate to be detected) to collect image data, and the upper (or lower) cameras are cascade-connected through equipment to cover the whole width of the steel plate to be detected. As shown in fig. 2, each camera covers a certain length of linear range, and 6 cameras jointly cover the wide edge of the steel plate to be tested in a cascading mode of equipment. The number of cameras is determined by the width of the steel plate (or other objects to be measured) to be measured and the scanning range of the cameras (for example, when the acquisition coverage width of the image data of each 3D camera is 0.45 meter and the width of the steel plate to be measured is 4.2 meters, 18-20 3D cameras are required to cover the widths of the upper and lower surfaces of the whole steel plate to be measured in a cascading manner of the equipment). When the resolutions of the cameras in cascade are different, according to the different resolutions of the cameras, each camera obtains a group of coordinates of pixel points of the measured steel plate in a coverage area, and outputs a first coordinate of the measured steel plate as a coordinate system based on the position of each camera as an origin, and the first sitting mark is made: Where p=u or p=d, u denotes a camera above the upper surface of the measured steel sheet, d denotes a camera below the lower surface of the measured steel sheet, t=0, 1,2,..t denotes a sampling time, j=0, 1,2,..m denotes a camera index ID, k=0, 1,2,..n denotes an index ID of each camera for collecting N sampling points at a time, all cameras are uniformly controlled by the collection signal controller, and when the collection signal controller sends out a collection signal, all cameras are simultaneously started to shoot and collect image data of the measured steel sheet.
Optionally, the image acquisition device further comprises a rate controller and a roller bed. And the speed controller is connected with the rolling machine, and is internally provided with a steel plate transmission speed for controlling the rotating speed of the rolling machine according to the steel plate transmission speed. And the rolling machine is used for placing the steel plate to be tested and conveying the steel plate to be tested through rotation. In this embodiment, the rate controller and the acquisition signal controller are controlled in coordination by rate matching software.
The data preprocessing comprises data cleaning, data integration, data transformation and data protocol. The detailed process is described in terms of data transformation in this embodiment.
Specifically, the camera calibration software includes a coordinate conversion module.
The coordinate conversion module is used for converting the first coordinates of the sampling points output by each camera into a world coordinate system according to the relative position relation of each camera in the array camera to obtain converted acquisition data. Preferably, as shown in fig. 3, the origin O of the world coordinate system is a corner of the measured steel plate (a corner of the measured object shown in fig. 1 is a uniform origin O of coordinates), the X axis of the origin O is parallel to the array camera formed by each camera, the Y axis of the origin O is parallel to the conveying direction of the measured steel plate, the Z axis of the origin O is perpendicular to the XOY plane, and the converted collected data are: where p=u denotes the upper surface of the measured steel sheet, p=d denotes the lower surface of the measured steel sheet, t denotes the sampling time, i=j·n+k, j is the camera index, i takes values of 0,1,2,.. a=m·n+n M represents the total number of sampling points of any surface of the measured steel sheet at each sampling time, and N M +.m represents the number of sampling points of the last camera that photographed any surface of the measured steel sheet. It should be noted that, the origin of the world coordinate system is not limited to one corner of the steel sheet to be measured in the present embodiment. The data acquired by each camera are converted into the acquired data in the same coordinate system, so that the thickness of the measured steel plate can be calculated conveniently, and the accuracy of a calculation result can be ensured.
Optionally, the data analysis software includes a first computing module and a second computing module.
The first calculation module is used for calculating the thickness of the steel plate at each sampling point of the measured steel plate according to the following formula:
Wherein, For the acquisition data of the upper surface of the steel plate to be tested,The data are collected for the lower surface of the steel plate to be tested.
The second calculation module is connected with the first calculation module and is used for calculating the thickness standard deviation of the measured steel plate according to the thickness of the steel plate and the following formula:
Wherein, The average thickness of the steel sheet to be measured is shown.
Optionally, the data analysis software further comprises an evaluation module. The evaluation module is connected with the second calculation module and is used for evaluating the uniformity of the thickness of the measured steel plate in response to the thickness standard deviation being smaller than a preset threshold value and evaluating the non-uniformity of the thickness of the measured steel plate in response to the thickness standard deviation being larger than or equal to the preset threshold value. The standard deviation sigma of the thickness of the steel plate represents the uniformity of the thickness of the detected steel plate, and the smaller the value is, the more uniform the thickness of the steel plate is. The uniformity of thickness is measured by standard deviation of thickness, and is reasonable and evaluated effectively.
In the steel plate detection system of this embodiment, the image acquisition device (such as an array camera) is used for respectively acquiring image data of the upper surface and the lower surface of the detected steel plate, the camera calibration software is used for preprocessing the acquired data, and the data analysis software is used for calculating the thickness standard deviation of the steel plate according to the preprocessed data so as to evaluate the thickness uniformity of the steel plate. The steel plate detection system based on the machine vision detection of flatness and flaws of the steel plate in industrial production has the characteristics of higher automation degree, comprehensive detection, suitability for the production environment of a high-speed unit and high detection precision compared with an artificial visual method. Furthermore, the camera calibration software is used for converting the data acquired by each camera into the acquired data in the same coordinate system, so that the thickness of the measured steel plate can be calculated conveniently and the accuracy of a calculation result can be ensured. In addition, the data analysis software is used for measuring the uniformity of the thickness of the measured steel plate by adopting the thickness standard deviation, so that the evaluation is reasonable and effective.
Example 2:
as shown in fig. 4, the present embodiment provides a steel plate detection method, including:
And step 401, acquiring image data of the upper surface and the lower surface of the steel plate to be tested.
Step 402, data preprocessing is performed on the acquired image data.
And 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.
The method comprises the steps of acquiring image data of the upper surface and the lower surface of a steel plate to be measured by adopting an array camera according to a signal acquisition period, acquiring the image data of the upper surface and the lower surface of the steel plate to be measured, and outputting first coordinates of sampling points, wherein the first coordinates are in a coordinate system taking the position of the array camera as an origin, the array camera comprises two groups of linear scanning cameras, the two groups of linear scanning cameras respectively acquire the image data of the upper surface and the lower surface of the steel plate to be measured, and a plurality of linear scanning cameras in the groups jointly cover the wide edge of the steel plate to be measured in a device cascading mode. The period of the acquired signal is the ratio of the stepping length of the steel plate to the transmission rate of the steel plate. The speed controller is internally provided with a steel plate transmission speed for controlling the rotating speed of the rolling machine according to the steel plate transmission speed, and the rolling machine is used for placing the steel plate to be tested and transmitting the steel plate to be tested through rotation to obtain the stepping length of the steel plate.
The method specifically comprises the steps of converting a first coordinate of a sampling point output by each camera into a world coordinate system according to the relative position relation of each camera in the array camera to obtain converted acquisition data, wherein an origin O of the world coordinate system is one corner of a detected steel plate, an X axis of the origin O is parallel to the array camera formed by each camera, a Y axis of the origin O is parallel to the conveying direction of the detected steel plate, a Z axis of the origin O is perpendicular to an XOY plane, and the converted acquisition data are: Where p=u denotes the upper surface of the measured steel sheet, p=d denotes the lower surface of the measured steel sheet, t denotes the sampling time, i=j·n+k, j is the camera index, i takes values of 0,1,2,.. a=m·n+n M represents the total number of sampling points of any surface of the measured steel sheet at each sampling time, and N M +.m represents the number of sampling points of the last camera that photographed any surface of the measured steel sheet.
Optionally, calculating the thickness standard deviation of the measured steel plate according to the preprocessed image data specifically comprises calculating the steel plate thickness of each sampling point of the measured steel plate according to the following formula:
Wherein, For the acquisition data of the upper surface of the steel plate to be tested,Collecting data of the lower surface of the steel plate to be tested;
Calculating the thickness standard deviation of the measured steel plate according to the thickness of the steel plate and the following formula:
Wherein, The average thickness of the steel sheet to be measured is shown.
Optionally, the thickness uniformity of the measured steel plate is evaluated according to the thickness standard deviation, and specifically comprises the steps of evaluating the thickness uniformity of the measured steel plate in response to the thickness standard deviation being smaller than a preset threshold value and evaluating the thickness non-uniformity of the measured steel plate in response to the thickness standard deviation being greater than or equal to the preset threshold value. Wherein the standard deviation sigma of the thickness of the steel plate represents the uniformity of the thickness of the detected steel plate, and the smaller the value is, the more uniform the thickness of the steel plate is.
Example 3:
As shown in fig. 5, the present embodiment provides an electronic apparatus including a memory 51 and a processor 52, the memory 51 storing a computer program therein, the processor 52 being configured to run the computer program to implement the steel plate detection method as described in embodiment 2.
The steel sheet inspection method of example 2 and the electronic apparatus of example 3 evaluate the thickness uniformity of the steel sheet by collecting image data of the upper surface and the lower surface of the steel sheet to be inspected, respectively, and preprocessing the collected data, and calculating the thickness standard deviation of the steel sheet from the preprocessed data. The steel plate detection system based on the flatness and flaws of the steel plate in the machine vision detection industrial production has the characteristics of higher automation degree, comprehensive detection, suitability for the production environment of a high-speed unit and high detection precision compared with an artificial visual method. Further, through converting the data collected by each camera into the collected data in the same coordinate system, the thickness of the measured steel plate is convenient to calculate subsequently, and the accuracy of a calculation result is ensured. In addition, the number adopts the standard deviation of the thickness to measure the uniformity of the thickness of the measured steel plate, so that the evaluation is reasonable and effective.
It is to be understood that the above embodiments are merely illustrative of the application of the principles of the present invention, but not in limitation thereof. Various modifications and improvements may be made by those skilled in the art without departing from the spirit and substance of the invention, and are also considered to be within the scope of the invention.
Claims (6)
1. A steel plate detection system is characterized by comprising an image acquisition device, camera calibration software and data analysis software,
An image acquisition device for acquiring image data of the upper surface and the lower surface of the steel plate to be tested,
Camera calibration software connected with the image acquisition device for data preprocessing of the acquired image data,
The data analysis software is connected with the camera calibration software and is used for 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;
the image acquisition device comprises an array camera and an acquisition signal controller,
The array camera is connected with the acquisition signal controller and is used for acquiring image data of the upper surface and the lower surface of the detected steel plate according to the acquisition signal sent by the acquisition signal controller and outputting the first coordinate of the sampling point, wherein the first coordinate is positioned in a coordinate system taking the position of the array camera as an origin,
The acquisition signal controller is provided with an acquisition signal period, and is used for sending an acquisition signal to the array camera according to the acquisition signal period, wherein the acquisition signal period is the ratio of the stepping length of the steel plate to the transmission rate of the steel plate;
The array camera includes two sets of linear scanning cameras,
The two groups of linear scanning cameras are respectively and fixedly arranged at the upper part and the lower part of the detection gate, and respectively keep a preset shooting distance with the corresponding surface of the detected steel plate, wherein the plurality of linear scanning cameras in the groups cover the broadside of the detected steel plate together in a device cascading mode, each camera obtains a group of coordinates of pixel points of the detected steel plate in the coverage range, the first coordinates of the detected steel plate are output as a coordinate system based on the position of each camera, and the first sitting marks are made: Where p=u or p=d, u denotes a camera above the upper surface of the measured steel sheet, d denotes a camera below the lower surface of the measured steel sheet, t=0, 1,2,..t denotes a sampling time, j=0, 1,2,..m denotes a camera index, k=1, 2,..n denotes an index where each camera captures N sampling points at a time;
the camera calibration software includes a coordinate conversion module,
The coordinate conversion module is used for converting the first coordinates of the sampling points output by each camera into a world coordinate system according to the relative position relation of each camera in the array camera to obtain converted acquisition data,
The origin O of the world coordinate system is a corner of the measured steel plate, the X axis of the origin O is parallel to an array camera formed by each camera, the Y axis of the origin O is parallel to the conveying direction of the measured steel plate, the Z axis of the origin O is perpendicular to the XOY plane, and the converted acquired data are: Where p=u denotes the upper surface of the measured steel sheet, p=d denotes the lower surface of the measured steel sheet, t denotes the sampling time, i=j·n+k, j is the camera index, i takes a value of 1, 2. A=m·n+n M represents the total number of sampling points of any surface of the measured steel plate at each sampling time, N M is less than or equal to M represents the number of sampling points of the last camera that photographs any surface of the measured steel plate;
the data analysis software includes a first computing module and a second computing module,
The first calculation module is used for calculating the thickness of the steel plate at each sampling point of the measured steel plate according to the following formula:
Wherein, For the acquisition data of the upper surface of the steel plate to be tested,For the acquisition data of the lower surface of the steel plate to be tested,
The second calculation module is connected with the first calculation module and is used for calculating the thickness standard deviation of the measured steel plate according to the thickness of the steel plate and the following formula:
Wherein, The average thickness of the steel sheet to be measured is shown.
2. The steel plate detection system of claim 1, wherein the image acquisition device further comprises a rate controller and a roller bed,
The speed controller is connected with the rolling machine, is provided with a steel plate transmission speed and is used for controlling the rotating speed of the rolling machine according to the steel plate transmission speed,
And the rolling machine is used for placing the steel plate to be tested and conveying the steel plate to be tested through rotation.
3. The steel plate inspection system of claim 1, wherein the data analysis software further comprises an evaluation module,
The evaluation module is connected with the second calculation module and is used for evaluating the uniformity of the thickness of the measured steel plate in response to the thickness standard deviation being smaller than a preset threshold value and evaluating the non-uniformity of the thickness of the measured steel plate in response to the thickness standard deviation being larger than or equal to the preset threshold value.
4. A steel sheet detection method, comprising:
Collecting image data of the upper surface and the lower surface of a detected steel plate;
performing data preprocessing on the acquired image data;
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;
the method for acquiring the image data of the upper surface and the lower surface of the measured steel plate specifically comprises the following steps:
Acquiring image data of the upper surface and the lower surface of the steel plate to be tested by adopting an array camera according to the acquisition signal period, and outputting first coordinates of sampling points, wherein the first coordinates are in a coordinate system taking the position of the array camera as an origin;
The array camera comprises two groups of linear scanning cameras, the two groups of linear scanning cameras respectively collect image data of the upper surface and the lower surface of the steel plate to be tested, the plurality of linear scanning cameras in the groups cover the broadside of the steel plate to be tested together in a device cascading mode, each camera obtains a group of coordinates of pixel points of the steel plate to be tested in the coverage range, the first coordinates of the steel plate to be tested are output to be a coordinate system based on the position of each camera as an origin, and the first sitting marks are made: Where p=u or p=d, u denotes a camera above the upper surface of the measured steel sheet, d denotes a camera below the lower surface of the measured steel sheet, t=0, 1,2,..t denotes a sampling time, j=0, 1,2,..m denotes a camera index, k=1, 2,..n denotes an index for each group of cameras to collect N sampling points at a time;
The data preprocessing of the collected image data specifically comprises the following steps:
converting the first coordinates of the sampling points output by each camera into a world coordinate system according to the relative position relation of each camera in the array camera to obtain converted acquisition data,
The origin O of the world coordinate system is a corner of the measured steel plate, the X axis of the origin O is parallel to an array camera formed by each camera, the Y axis of the origin O is parallel to the conveying direction of the measured steel plate, the Z axis of the origin O is perpendicular to the XOY plane, and the converted acquired data are: Where p=u denotes the upper surface of the measured steel sheet, p=d denotes the lower surface of the measured steel sheet, t denotes the sampling time, i=j·n+k, j is the camera index, i takes a value of 1, 2. A=m·n+n M represents the total number of sampling points of any surface of the measured steel plate at each sampling time, N M is less than or equal to M represents the number of sampling points of the last camera that photographs any surface of the measured steel plate;
Calculating the thickness standard deviation of the measured steel plate according to the preprocessed image data, wherein the method specifically comprises the following steps:
the thickness of the steel plate at each sampling point of the steel plate to be measured is calculated according to the following formula:
Wherein, For the acquisition data of the upper surface of the steel plate to be tested,Collecting data of the lower surface of the steel plate to be tested;
Calculating the thickness standard deviation of the measured steel plate according to the thickness of the steel plate and the following formula:
Wherein, The average thickness of the steel sheet to be measured is shown.
5. The method for inspecting a steel sheet according to claim 4, wherein the thickness uniformity of the inspected steel sheet is evaluated based on a thickness standard deviation, specifically comprising:
in response to the thickness standard deviation being smaller than a preset threshold value, evaluating that the thickness of the measured steel plate is uniform;
and in response to the thickness standard deviation being greater than or equal to a preset threshold value, evaluating the thickness unevenness of the measured steel plate.
6. An electronic device comprising a memory and a processor, the memory having stored therein a computer program, the processor being arranged to run the computer program to implement the steel plate detection method according to claim 4 or 5.
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| CN202211564477.3A CN115791830B (en) | 2022-12-07 | 2022-12-07 | Steel plate detection system, steel plate detection method and electronic equipment |
| PCT/CN2023/136094 WO2024120333A1 (en) | 2022-12-07 | 2023-12-04 | Steel plate inspection system, steel plate inspection method, electronic device, and storage medium |
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| CN202211564477.3A CN115791830B (en) | 2022-12-07 | 2022-12-07 | Steel plate detection system, steel plate detection method and electronic equipment |
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| CN115791830B (en) * | 2022-12-07 | 2025-03-18 | 中国联合网络通信集团有限公司 | Steel plate detection system, steel plate detection method and electronic equipment |
| CN117190887B (en) * | 2023-11-06 | 2024-01-30 | 深圳市磐锋精密技术有限公司 | Aerogel thickness automatic detection system for mobile phone production |
| CN118293852B (en) * | 2024-06-05 | 2024-08-06 | 乐山京隆石英玻璃制品有限公司 | Crucible thickness measuring method and measuring device |
| CN118777562B (en) * | 2024-09-12 | 2024-12-13 | 安徽首矿大昌金属材料有限公司 | A steel quality analysis and feedback system |
| CN118882507B (en) * | 2024-09-30 | 2025-01-03 | 中南大学 | Method for measuring thickness of cladding of composite metal wire, method for evaluating thickness of cladding of composite metal wire, terminal and medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108955608A (en) * | 2018-05-18 | 2018-12-07 | 云南电网有限责任公司电力科学研究院 | Insulator surface RTV coating coats effect evaluation method, apparatus and system |
| CN113624458A (en) * | 2021-08-19 | 2021-11-09 | 中国科学院合肥物质科学研究院 | Thin film uniformity inspection system based on two-channel full projection light |
| CN216593225U (en) * | 2021-12-24 | 2022-05-24 | 凯多智能科技(上海)有限公司 | Line laser thickness measuring equipment |
| WO2024120333A1 (en) * | 2022-12-07 | 2024-06-13 | 中国联合网络通信集团有限公司 | Steel plate inspection system, steel plate inspection method, electronic device, and storage medium |
Family Cites Families (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6473186B2 (en) * | 2000-05-22 | 2002-10-29 | Mitutoyo Corporation | Scanning wide-area surface shape analyzer |
| CA2327894A1 (en) * | 2000-12-07 | 2002-06-07 | Clearview Geophysics Inc. | Method and system for complete 3d object and area digitizing |
| KR100652948B1 (en) * | 2000-12-08 | 2006-12-01 | 삼성코닝 주식회사 | Thickness Measurement System and Method of Glass Substrate for LCD |
| KR20100020671A (en) * | 2008-08-13 | 2010-02-23 | 에스티엑스조선해양 주식회사 | Equipment to measure thickness and distinguish shape of steel materials using vision camera, and method to measure thickness and distinguish shape of steel materials using the same |
| US8502180B2 (en) * | 2009-01-26 | 2013-08-06 | Centre De Recherche Industrielle Du Quebec | Apparatus and method having dual sensor unit with first and second sensing fields crossed one another for scanning the surface of a moving article |
| JP5942494B2 (en) * | 2012-03-12 | 2016-06-29 | コニカミノルタ株式会社 | Thickness measuring apparatus and thickness measuring method |
| EP2913631A1 (en) * | 2014-02-27 | 2015-09-02 | Ricoh Company, Ltd. | Test apparatus and method |
| KR102402386B1 (en) * | 2014-05-30 | 2022-05-26 | (주)에디슨이브이 | Method, apparatus and the system for detecting thickness of an object |
| US9638642B2 (en) * | 2014-11-28 | 2017-05-02 | Centre De Recherce Industrielle Du Quebec | Apparatus and method for optically scanning a surface of an object under adverse external condition |
| CN104677314A (en) * | 2015-03-02 | 2015-06-03 | 合肥京东方光电科技有限公司 | Device and method for detecting surface flatness of display panel |
| CN206920353U (en) * | 2017-07-12 | 2018-01-23 | 江苏阿瑞斯智能设备有限公司 | Honeycomb substrate defect automatic detection system |
| CN109029233B (en) * | 2018-08-31 | 2020-06-26 | 中国联合网络通信集团有限公司 | Brake block thickness detection system and vehicle |
| CN111609801B (en) * | 2020-05-31 | 2021-03-23 | 南京工业大学 | A method and system for measuring the thickness of multi-size workpieces based on machine vision |
| CN111795657B (en) * | 2020-07-16 | 2022-02-15 | 南京大量数控科技有限公司 | A kind of equipment and method for quickly measuring the flatness of flexible sheet |
| CN114234804B (en) * | 2021-12-14 | 2024-07-12 | 复旦大学 | Refraction and reflection mixed type shape and position integrated deflection measurement method |
-
2022
- 2022-12-07 CN CN202211564477.3A patent/CN115791830B/en active Active
-
2023
- 2023-12-04 WO PCT/CN2023/136094 patent/WO2024120333A1/en unknown
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108955608A (en) * | 2018-05-18 | 2018-12-07 | 云南电网有限责任公司电力科学研究院 | Insulator surface RTV coating coats effect evaluation method, apparatus and system |
| CN113624458A (en) * | 2021-08-19 | 2021-11-09 | 中国科学院合肥物质科学研究院 | Thin film uniformity inspection system based on two-channel full projection light |
| CN216593225U (en) * | 2021-12-24 | 2022-05-24 | 凯多智能科技(上海)有限公司 | Line laser thickness measuring equipment |
| WO2024120333A1 (en) * | 2022-12-07 | 2024-06-13 | 中国联合网络通信集团有限公司 | Steel plate inspection system, steel plate inspection method, electronic device, and storage medium |
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