WO2024120333A1 - 一种钢板检测系统、钢板检测方法、电子设备及存储介质 - Google Patents
一种钢板检测系统、钢板检测方法、电子设备及存储介质 Download PDFInfo
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- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 256
- 239000010959 steel Substances 0.000 title claims abstract description 256
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- 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, an electronic device and a computer-readable storage medium.
- 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.
- 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.
- the present invention provides a steel plate detection system, a steel plate detection method, an electronic device and a computer-readable storage medium, so as to at least solve the problems existing in the related art of manual visual steel plate detection, 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.
- the present invention provides a steel plate detection system, including an image acquisition device, camera calibration software and data analysis software.
- An image acquisition device is used to acquire image data of the upper and lower surfaces of the steel plate under test.
- a camera calibration software is connected to the image acquisition device and is used to perform data preprocessing on the acquired image data.
- a data analysis software is connected to the camera calibration software and is used to calculate the thickness standard deviation of the steel plate under test based on the preprocessed image data, and to evaluate the thickness standard deviation based on the thickness standard deviation. Thickness uniformity of the steel plate being tested.
- 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.
- 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 by means of a cascaded device.
- 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.
- 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 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:
- the data collected for the upper surface of the steel plate under test is The following table is for the steel plate under test
- 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:
- 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.
- 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.
- 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, the two groups of linear scanning cameras 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.
- 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 thickness standard deviation of the steel plate to be measured is calculated based on the preprocessed image data.
- the method includes: calculating the steel plate thickness at each sampling point of the steel plate under test according to the following formula:
- 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:
- 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.
- 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.
- the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steel plate detection method as described in the second aspect is implemented.
- the present invention provides a steel plate detection system, a steel plate detection method, an electronic device and a computer-readable storage medium.
- 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.
- FIG1 is a schematic structural diagram of a steel plate detection system according to Embodiment 1 of the present invention.
- FIG2 is a schematic diagram of a camera coverage range according to Embodiment 1 of the present invention.
- FIG3 is a schematic diagram of a world coordinate system according to Embodiment 1 of the present invention.
- FIG4 is a schematic flow chart of a steel plate detection method according to Embodiment 2 of the present invention.
- FIG. 5 is a schematic diagram of the structure of an electronic device according to Embodiment 3 of the present invention.
- 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.
- 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.
- 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 by a combination of hardware and computer instructions.
- the units and modules involved in the embodiments of the present invention can be implemented by software or hardware.
- the units and modules can be located in a processor.
- Embodiment 1 is a diagrammatic representation of Embodiment 1:
- 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 .
- 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.
- 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.
- 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.
- 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 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.
- a group 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 (i.e., the wide side of the steel plate to be tested).
- each camera covers a straight line range of a certain length, and 6 cameras are cascaded to cover the wide side of the steel plate to be tested.
- the number of cameras is determined by the width of the steel plate to be tested (or other objects to be tested) and the scanning range of the camera (for example, when the image data collection coverage width of each 3D camera is 0.45 meters and the width of the steel plate to be tested is 4.2 meters, a total of 18 to 20 3D cameras are required to cover the wide side of the upper and lower surfaces of the entire steel plate to be tested through the cascade of equipment).
- each camera obtains a set of coordinates of the 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 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.
- the rate controller and the acquisition signal controller are coordinated by the rate matching software control.
- Data preprocessing includes data cleaning, data integration, data transformation, and data reduction.
- data transformation is used to illustrate the detailed process.
- 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.
- the origin O of the world coordinate system is a corner of the steel plate to be tested (a corner of the object to be tested as shown in FIG1 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 tested
- its Z axis is perpendicular to the XOY plane.
- 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:
- 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.
- 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:
- 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 tested steel plate in response to the thickness standard deviation being less than a preset threshold, and to evaluate the unevenness of the thickness of the tested steel plate in response to the thickness standard deviation being greater than or equal to a preset threshold.
- the standard deviation ⁇ of the steel plate thickness characterizes the uniformity of the thickness of the tested steel plate, 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.
- 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 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.
- 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.
- 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.
- Embodiment 2 is a diagrammatic representation of Embodiment 1:
- this embodiment provides a steel plate detection method, comprising:
- Step 401 collecting image data of the upper surface and the lower surface of the steel plate under test.
- Step 402 preprocess the collected image data.
- Step 403 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 collecting of image data of the upper surface and the lower surface of the steel plate under test specifically includes: using an array camera to collect image data of the upper surface and the lower surface of the steel plate under test according to a collection signal cycle, and outputting a first coordinate of a sampling point, wherein the first coordinate is in 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 collect image data of the upper and lower surfaces of the steel plate under test, and 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.
- 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.
- 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 a 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.
- 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:
- 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 ⁇ 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.
- Embodiment 3 is a diagrammatic representation of Embodiment 3
- 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.
- 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.
- 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.
- Embodiment 4 is a diagrammatic representation of Embodiment 4:
- This embodiment provides a computer-readable storage medium on which a computer program is stored.
- the computer program is executed by a processor, the steel plate detection method described in Example 2 is implemented.
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Abstract
本发明提供一种钢板检测系统、钢板检测方法、电子设备及计算机可读存储介质，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。
Description
本发明要求申请日为2022年12月7日、申请号为CN202211564477.3、名称为“一种钢板检测系统、钢板检测方法及电子设备”的中国专利申请的优先权。
本发明涉及视觉测量技术领域，尤其涉及一种钢板检测系统、钢板检测方法、电子设备及计算机可读存储介质。
钢板表面检测主要用于检测钢板表面的不连续性缺陷(如坑陷、划痕等)，检测方法有人工经验检测法、基于电磁感应及超声的无损检测技术。
目前，大型钢板的检测手段主要使用人工目视的方法，受限于生产节拍的要求，人工目视的方法无法检测钢板底面，故无法全覆盖被测钢板的上下表面；且人工目视检测方法无法对钢板表面不连续性进行数值测量，需要增加工序并使用专用仪器测量数值后进行钢板分级操作，因此，目前大型钢板的检测存在人工劳动强度大、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。
发明内容
本发明提供一种钢板检测系统、钢板检测方法、电子设备及计算机可读存储介质，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。
第一方面，本发明提供一种钢板检测系统，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。
优选地，所述图像采集装置包括阵列相机和采集信号控制器。阵列相机，与所述采集信号控制器连接，用于根据所述采集信号控制器发送的采集信号对被测钢板的上表面和下表面进行图像数据的采集，并输出采样点的第一坐标，其中，第一坐标处于以阵列相机的位置为原点的坐标系中。所述采集信号控制器设有采集信号周期，所述采集信号控制器用于根据采集信号周期向所述阵列相机发送采集信号，其中，采集信号周期为钢板步进长度与钢板传输速率的比值。
优选地，所述阵列相机包括两组线性扫描相机。两组线性扫描相机，用于分别固设在检测闸口的上部和下部，且分别与被测钢板的对应表面之间保持预设的拍摄距离，其中，组内的多个线性扫描相机通过设备级联方式共同覆盖被测钢板的宽边。
优选地，所述图像采集装置还包括速率控制器和滚床。速率控制器，与所述滚床连接，速率控制器设有钢板传输速率，用于根据钢板传输速率控制所述滚床的转速。所述滚床，用于放置被测钢板，并通过转动以传送被测钢板。
优选地，所述相机标定软件包括坐标转换模块。坐标转换模块，用于根据阵列相机中各相机的相对位置关系，将各相机输出的采样点的第一坐标转换至世界坐标系中，得到转换后的采集数据，其中，世界坐标系的原点O为被测钢板的一角，其X轴与各相机组成的阵列相机平行，其Y轴与被测钢板的传送方向平行，其Z轴垂直于XOY平面，转换后的采集数据为：其中p＝u表示被测钢板的上表面，p＝d表示被测钢板的下表面，t表示采样时刻，i＝j·N+k，j为相机索引，i取值为0,1,2,...A，A＝M·N+NM表示每个采样时刻被测钢板任一表面的采样点的总数量，NM≤M表示拍摄被测钢板任一表面的最后一个相机的采样点的数量。
优选地，数据分析软件包括第一计算模块和第二计算模块。第一计算模块，用于根据以下公式计算被测钢板的各采样点的钢板厚度：
其中，为被测钢板的上表面的采集数据，为被测钢板的下表
面的采集数据。第二计算模块，与第一计算模块连接，用于根据钢板厚度及以下公式计算被测钢板的厚度标准差：
其中，表示被测钢板的平均厚度。
优选地，数据分析软件还包括评价模块。评价模块，与第二计算模块连接，用于响应于厚度标准差小于预设阈值，评价被测钢板的厚度均匀，以及，用于响应于厚度标准差大于或等于预设阈值，评价被测钢板的厚度不均匀。
第二方面，本发明还提供一种钢板检测方法，包括：采集被测钢板的上表面和下表面的图像数据；对所采集的图像数据进行数据预处理；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。
优选地，所述采集被测钢板的上表面和下表面的图像数据，具体包括：采用阵列相机根据采集信号周期对被测钢板的上表面和下表面进行图像数据的采集，并输出采样点的第一坐标，其中，第一坐标处于以阵列相机的位置为原点的坐标系中。阵列相机包括两组线性扫描相机，两组线性扫描相机分别采集被测钢板的上表面和下表面的图像数据，且组内的多个线性扫描相机通过设备级联方式共同覆盖被测钢板的宽边。
优选地，对所采集的图像数据进行数据预处理，具体包括：根据阵列相机中各相机的相对位置关系，将各相机输出的采样点的第一坐标转换至世界坐标系中，得到转换后的采集数据，其中，世界坐标系的原点O为被测钢板的一角，其X轴与各相机组成的阵列相机平行，其Y轴与被测钢板的传送方向平行，其Z轴垂直于XOY平面，转换后的采集数据为：其中p＝u表示被测钢板的上表面，p＝d表示被测钢板的下表面，t表示采样时刻，i＝j·N+k，j为相机索引，i取值为0,1,2,...A，A＝M·N+NM表示每个采样时刻被测钢板任一表面的采样点的总数量，NM≤M表示拍摄被测钢板任一表面的最后一个相机的采样点的数量。
优选地，根据预处理后的图像数据计算被测钢板的厚度标准差，具
体包括：根据以下公式计算被测钢板的各采样点的钢板厚度：
其中，为被测钢板的上表面的采集数据，为被测钢板的下表面的采集数据，根据钢板厚度及以下公式计算被测钢板的厚度标准差：
其中，表示被测钢板的平均厚度。
优选地，根据厚度标准差评价被测钢板的厚度均匀性，具体包括：响应于厚度标准差小于预设阈值，评价被测钢板的厚度均匀；响应于厚度标准差大于或等于预设阈值，评价被测钢板的厚度不均匀。
第三方面，本发明还提供一种电子设备，包括存储器和处理器，所述存储器中存储有计算机程序，所述处理器被设置为运行所述计算机程序以实现如第二方面中所述的钢板检测方法。
第四方面，本发明还提供一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时，实现如第二方面中所述的钢板检测方法。
本发明提供的一种钢板检测系统、钢板检测方法、电子设备及计算机可读存储介质，钢板检测系统中的图像采集装置用于分别采集被测钢板上表面和下表面的图像数据，相机标定软件用于对所采集的数据进行预处理，数据分析软件用于根据预处理后的数据计算钢板的厚度标准差，以评价钢板的厚度均匀性。这种基于机器视觉检测工业生产中钢板的平整度和瑕疵的检测系统，相比于人工目视方法具有较高的自动化程度、检测全面、适应于高速机组的生产环境、且检测精度高的特点。
图1为本发明实施例1的一种钢板检测系统的结构示意图；
图2为本发明实施例1的一种相机覆盖范围示意图；
图3为本发明实施例1的一种世界坐标系的示意图；
图4为本发明实施例2的一种钢板检测方法的流程示意图；
图5为本发明实施例3的一种电子设备的结构示意图。
为使本领域技术人员更好地理解本发明的技术方案，下面将结合附图对本发明实施方式作进一步地详细描述。
可以理解的是，此处描述的具体实施例和附图仅仅用于解释本发明，而非对本发明的限定。
可以理解的是，在不冲突的情况下，本发明中的各实施例及实施例中的各特征可相互组合。
可以理解的是，为便于描述，本发明的附图中仅示出了与本发明相关的部分，而与本发明无关的部分未在附图中示出。
可以理解的是，本发明的实施例中所涉及的每个单元、模块可仅对应一个实体结构，也可由多个实体结构组成，或者，多个单元、模块也可集成为一个实体结构。
可以理解的是，在不冲突的情况下，本发明的流程图和框图中所标注的功能、步骤可按照不同于附图中所标注的顺序发生。
可以理解的是，本发明的流程图和框图中，示出了按照本发明各实施例的系统、装置、设备、方法的可能实现的体系架构、功能和操作。其中，流程图或框图中的每个方框可代表一个单元、模块、程序段、代码，其包含用于实现规定的功能的可执行指令。而且，框图和流程图中的每个方框或方框的组合，可用实现规定的功能的基于硬件的系统实现，也可用硬件与计算机指令的组合来实现。
可以理解的是，本发明实施例中所涉及的单元、模块可通过软件的方式实现，也可通过硬件的方式来实现，例如单元、模块可位于处理器中。
实施例1：
如图1所示，本实施例提供一种钢板检测系统，可应用于高速机组的钢板生产场景或其他钢板检测场景。钢板检测系统包括图像采集装置11、相机标定软件12和数据分析软件13。
图像采集装置11，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12，与图像采集装置11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13，与相机标定软件12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。
可选地，图像采集装置包括阵列相机和采集信号控制器。阵列相机，与采集信号控制器连接，用于根据采集信号控制器发送的采集信号对被测钢板的上表面和下表面进行图像数据的采集，并输出采样点的第一坐标，其中，第一坐标处于以阵列相机的位置为原点的坐标系中。采集信号控制器内设有采集信号周期，采集信号控制器用于根据采集信号周期向阵列相机发送采集信号，其中，采集信号周期为钢板步进长度L(单位：米)与钢板传输速率S(单位：米/秒)的比值，即采集信号控制器发送采集信号的时间间隔为：τ＝L/S(单位：秒)，也就是说，阵列相机每间隔时间τ，拍摄并采集一次数据。
具体地，阵列相机包括两组线性扫描相机。两组线性扫描相机，用于分别固设在检测闸口的上部和下部，且分别与被测钢板的对应表面之间保持预设的拍摄距离，其中，组内的多个线性扫描相机通过设备级联方式共同覆盖被测钢板的宽边。
本实施例中，如图1所示，在检测闸口上下部(即待测钢板的上方和下方)各安装一组三维(3D)线性扫描相机进行图像数据的采集，上方(或下方)相机之间通过设备级联共同覆盖整个被测钢板宽度(即被测钢板的宽边)。如图2所示，每个相机覆盖一定长度的直线范围，6个相机通过设备级联方式共同覆盖被测钢板的宽边。相机的个数由被测钢板(或其他被测物体)的宽度以及相机的扫描范围确定(例如，当每个3D相机的图像数据的采集覆盖宽度为0.45米，被测钢板宽度为4.2米时，共计需要18～20个3D相机通过设备级联方式覆盖整个被测钢板的上下表面的宽边)。当级联的相机的分辨率不同，根据相机不同的分辨率，每个相机在覆盖范围内获得一组关于被测钢板的像素点的坐标，并输出被测钢板的第一坐标为基于各自相机位置为原点的坐标系，第一坐标记作：其中p＝u或p＝d，u表示被测钢板的上表面，d表示被测钢板的下表面，t＝0,1,2,...T表示采样时刻，j＝0,1,2,...M表示相机索引ID，k＝0,1,2,...N表示每个相机每次采集N个采样点的索引ID，所有
的相机由采集信号控制器统一控制，当采集信号控制器发出采集信号时，所有相机同时启动拍摄并采集被测钢板的图像数据。
可选地，图像采集装置还包括速率控制器和滚床。速率控制器，与滚床连接，速率控制器内设有钢板传输速率，用于根据钢板传输速率控制滚床的转速。滚床，用于放置被测钢板，并通过转动以传送被测钢板。本实施例中，速率控制器和采集信号控制器由速率匹配软件控制协同。
数据预处理包括数据清理、数据集成、数据变换、数据规约。本实施例中以数据变换说明详细过程。
具体地，相机标定软件包括坐标转换模块。
坐标转换模块，用于根据阵列相机中各相机的相对位置关系，将各相机输出的采样点的第一坐标转换至世界坐标系中，得到转换后的采集数据。优选地，如图3所示，世界坐标系的原点O为被测钢板的一角(如图1所示的被检测物体的一角为统一坐标原点O)，其X轴与各相机组成的阵列相机平行，其Y轴与被测钢板的传送方向平行，其Z轴垂直于XOY平面，转换后的采集数据为：其中p＝u表示被测钢板的上表面，p＝d表示被测钢板的下表面，t表示采样时刻，i＝j·N+k，j为相机索引，i取值为0,1,2,...A，A＝M·N+NM表示每个采样时刻被测钢板任一表面的采样点的总数量，NM≤M表示拍摄被测钢板任一表面的最后一个相机的采样点的数量。需要说明的是，世界坐标系的原点并不局限于本实施例中被测钢板的一角。通过将各相机采集的数据转换为同一坐标系中的采集数据，便于后续对被测钢板厚度的计算并保证计算结果的精确度。
可选地，数据分析软件包括第一计算模块和第二计算模块。
第一计算模块，用于根据以下公式计算被测钢板的各采样点的钢板厚度：
其中，为被测钢板的上表面的采集数据，为被测钢板的下表面的采集数据。
第二计算模块，与第一计算模块连接，用于根据钢板厚度及以下公式计算被测钢板的厚度标准差：
其中，表示被测钢板的平均厚度。
可选地，数据分析软件还包括评价模块。评价模块，与第二计算模块连接，用于响应于厚度标准差小于预设阈值，评价被测钢板的厚度均匀，以及，用于响应于厚度标准差大于或等于预设阈值，评价被测钢板的厚度不均匀。钢板厚度标准差σ表征了被检测钢板厚度的均匀性，该值越小则表示钢板厚度越均匀。通过厚度标准差衡量厚度的均匀性，合理且评价有效。
本实施例的钢板检测系统，图像采集装置(如阵列相机)用于分别采集被测钢板上表面和下表面的图像数据，相机标定软件用于对所采集的数据进行预处理，数据分析软件用于根据预处理后的数据计算钢板的厚度标准差，以评价钢板的厚度均匀性。并且用于协同采集信号控制器控制采集周期和速率控制器控制滚床的转速，以实现对被测钢板的自动检测，这种基于机器视觉检测工业生产中钢板的平整度和瑕疵的钢板检测系统，相比于人工目视方法具有较高的自动化程度、检测全面、适应于高速机组的生产环境、且检测精度高的特点。进一步地，相机标定软件用于将各相机采集的数据转换为同一坐标系中的采集数据，便于后续计算被测钢板的厚度并保证计算结果的精确度。此外，数据分析软件用于采用厚度标准差衡量被测钢板厚度的均匀性，合理且评价有效。
实施例2：
如图4所示，本实施例提供一种钢板检测方法，包括：
步骤401，采集被测钢板的上表面和下表面的图像数据。
步骤402，对所采集的图像数据进行数据预处理。
步骤403，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。
可选地，所述采集被测钢板的上表面和下表面的图像数据，具体包括：采用阵列相机根据采集信号周期对被测钢板的上表面和下表面进行图像数据的采集，并输出采样点的第一坐标，其中，所述第一坐标处于
以阵列相机的位置为原点的坐标系中，阵列相机包括两组线性扫描相机，两组线性扫描相机分别采集被测钢板的上表面和下表面的图像数据，且组内的多个线性扫描相机通过设备级联方式共同覆盖被测钢板的宽边。采集信号周期为钢板步进长度与钢板传输速率的比值。其中，速率控制器内设有钢板传输速率，用于根据钢板传输速率控制滚床的转速；滚床，用于放置被测钢板，并通过转动以传送被测钢板，得到钢板步进长度。
可选地，对所采集的图像数据进行数据预处理，具体包括：根据阵列相机中各相机的相对位置关系，将各相机输出的采样点的第一坐标转换至世界坐标系中，得到转换后的采集数据，其中，世界坐标系的原点O为被测钢板的一角，其X轴与各相机组成的阵列相机平行，其Y轴与被测钢板的传送方向平行，其Z轴垂直于XOY平面，转换后的采集数据为：其中p＝u表示被测钢板的上表面，p＝d表示被测钢板的下表面，t表示采样时刻，i＝j·N+k，j为相机索引，i取值为0,1,2,...A，A＝M·N+NM表示每个采样时刻被测钢板任一表面的采样点的总数量，NM≤M表示拍摄被测钢板任一表面的最后一个相机的采样点的数量。
可选地，根据预处理后的图像数据计算被测钢板的厚度标准差，具体包括：根据以下公式计算被测钢板的各采样点的钢板厚度：
其中，为被测钢板的上表面的采集数据，为被测钢板的下表面的采集数据；
根据钢板厚度及以下公式计算被测钢板的厚度标准差：
其中，表示被测钢板的平均厚度。
可选地，根据厚度标准差评价被测钢板的厚度均匀性，具体包括：响应于厚度标准差小于预设阈值，评价被测钢板的厚度均匀；响应于厚度标准差大于或等于预设阈值，评价被测钢板的厚度不均匀。其中，钢板厚度标准差σ表征了被检测钢板厚度的均匀性，该值越小则表示钢板厚度越均匀。
实施例3：
如图5所示，本实施例提供一种电子设备，包括存储器51和处理器52，所述存储器51中存储有计算机程序，所述处理器52被设置为运行所述计算机程序以实现如实施例2所述的钢板检测方法。
实施例2的钢板检测方法和实施例3的电子设备，通过分别采集被测钢板上表面和下表面的图像数据，并对所采集的数据进行预处理，以及根据预处理后的数据计算钢板的厚度标准差，以评价钢板的厚度均匀性。并且通过采集信号控制器自动控制采集周期、通过速率控制器自动控制滚床的转速，以实现对被测钢板的自动检测，这种基于机器视觉检测工业生产中钢板的平整度和瑕疵的钢板检测系统，相比于人工目视方法具有较高的自动化程度、检测全面、适应于高速机组的生产环境、且检测精度高的特点。进一步地，通过将各相机采集的数据转换为同一坐标系中的采集数据，便于后续计算被测钢板的厚度并保证计算结果的精确度。此外，采用厚度标准差衡量被测钢板厚度的均匀性，合理且评价有效。
实施例4：
本实施例提供一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时，实现如实施例2所述的钢板检测方法。
可以理解的是，以上实施方式仅仅是为了说明本发明的原理而采用的示例性实施方式，然而本发明并不局限于此。对于本领域内的普通技术人员而言，在不脱离本发明的精神和实质的情况下，可以做出各种变型和改进，这些变型和改进也视为本发明的保护范围。
Claims (14)
- 一种钢板检测系统，其特征在于，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。
- 根据权利要求1所述的钢板检测系统，其特征在于，所述图像采集装置包括阵列相机和采集信号控制器，阵列相机，与所述采集信号控制器连接，用于根据所述采集信号控制器发送的采集信号对被测钢板的上表面和下表面进行图像数据的采集，并输出采样点的第一坐标，其中，第一坐标处于以阵列相机的位置为原点的坐标系中，所述采集信号控制器设有采集信号周期，所述采集信号控制器用于根据采集信号周期向所述阵列相机发送采集信号，其中，采集信号周期为钢板步进长度与钢板传输速率的比值。
- 根据权利要求2所述的钢板检测系统，其特征在于，所述阵列相机包括两组线性扫描相机，两组线性扫描相机，用于分别固设在检测闸口的上部和下部，且分别与被测钢板的对应表面之间保持预设的拍摄距离，其中，组内的多个线性扫描相机通过设备级联方式共同覆盖被测钢板的宽边。
- 根据权利要求1所述的钢板检测系统，其特征在于，所述图像采集装置还包括速率控制器和滚床，速率控制器，与所述滚床连接，速率控制器设有钢板传输速率，用 于根据钢板传输速率控制所述滚床的转速，所述滚床，用于放置被测钢板，并通过转动以传送被测钢板。
- 根据权利要求2所述的钢板检测系统，其特征在于，所述相机标定软件包括坐标转换模块，坐标转换模块，用于根据阵列相机中各相机的相对位置关系，将各相机输出的采样点的第一坐标转换至世界坐标系中，得到转换后的采集数据，其中，世界坐标系的原点O为被测钢板的一角，其X轴与各相机组成的阵列相机平行，其Y轴与被测钢板的传送方向平行，其Z轴垂直于XOY平面，转换后的采集数据为：其中p＝u表示被测钢板的上表面，p＝d表示被测钢板的下表面，t表示采样时刻，i＝j·N+k，j为相机索引，i取值为0,1,2,...A，A＝M·N+NM表示每个采样时刻被测钢板任一表面的采样点的总数量，NM≤M表示拍摄被测钢板任一表面的最后一个相机的采样点的数量。
- 根据权利要求1所述的钢板检测系统，其特征在于，数据分析软件包括第一计算模块和第二计算模块，第一计算模块，用于根据以下公式计算被测钢板的各采样点的钢板厚度：
其中，为被测钢板的上表面的采集数据，为被测钢板的下表面的采集数据，第二计算模块，与第一计算模块连接，用于根据钢板厚度及以下公式计算被测钢板的厚度标准差：
其中，表示被测钢板的平均厚度。 - 根据权利要求6所述的钢板检测系统，其特征在于，数据分析软件还包括评价模块，评价模块，与第二计算模块连接，用于响应于厚度标准差小于预设阈值，评价被测钢板的厚度均匀，以及，用于响应于厚度标准差大于或等于预设阈值，评价被测钢板的厚度不均匀。
- 一种钢板检测方法，其特征在于，包括：采集被测钢板的上表面和下表面的图像数据；对所采集的图像数据进行数据预处理；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。
- 根据权利要求8所述的钢板检测方法，其特征在于，所述采集被测钢板的上表面和下表面的图像数据，具体包括：采用阵列相机根据采集信号周期对被测钢板的上表面和下表面进行图像数据的采集，并输出采样点的第一坐标，其中，第一坐标处于以阵列相机的位置为原点的坐标系中；阵列相机包括两组线性扫描相机，两组线性扫描相机分别采集被测钢板的上表面和下表面的图像数据，且组内的多个线性扫描相机通过设备级联方式共同覆盖被测钢板的宽边。
- 根据权利要求8所述的钢板检测方法，其特征在于，对所采集的图像数据进行数据预处理，具体包括：根据阵列相机中各相机的相对位置关系，将各相机输出的采样点的第一坐标转换至世界坐标系中，得到转换后的采集数据，其中，世界坐标系的原点O为被测钢板的一角，其X轴与各相机组成的阵列相机平行，其Y轴与被测钢板的传送方向平行，其Z轴垂直于XOY平面，转换后的采集数据为：其中p＝u表示被测钢板的上表面，p＝d表示被测钢板的下表面，t表示采样时刻，i＝j·N+k，j为相机索引，i取值为0,1,2,...A，A＝M·N+NM表示每个采样时刻被测钢板 任一表面的采样点的总数量，NM≤M表示拍摄被测钢板任一表面的最后一个相机的采样点的数量。
- 根据权利要求8所述的钢板检测方法，其特征在于，根据预处理后的图像数据计算被测钢板的厚度标准差，具体包括：根据以下公式计算被测钢板的各采样点的钢板厚度：
其中，为被测钢板的上表面的采集数据，为被测钢板的下表面的采集数据；根据钢板厚度及以下公式计算被测钢板的厚度标准差：
其中，表示被测钢板的平均厚度。 - 根据权利要求8所述的钢板检测方法，其特征在于，根据厚度标准差评价被测钢板的厚度均匀性，具体包括：响应于厚度标准差小于预设阈值，评价被测钢板的厚度均匀；响应于厚度标准差大于或等于预设阈值，评价被测钢板的厚度不均匀。
- 一种电子设备，其特征在于，包括存储器和处理器，所述存储器中存储有计算机程序，所述处理器被设置为运行所述计算机程序以实现如权利要求8-12中任一项所述的钢板检测方法。
- 一种计算机可读存储介质，其上存储有计算机程序，其特征在于，所述计算机程序被处理器执行时，实现如权利要求8-12中任一项所述的钢板检测方法。
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