阅读说明：本技术 基于机器视觉的钢板表面缺陷检测系统及方法 (Steel plate surface defect detection system and method based on machine vision ) 是由 陈文建 陈瑞 李武森 王小卓 裘俊哲 于 2019-11-15 设计创作，主要内容包括：本发明公开了一种基于机器视觉的钢板表面缺陷检测系统及方法,系统包括传动模块,用于带动被测钢板运动；激光测速模块,用于产生控制采集控制模块工作的信号；采集控制模块,用于控制图像采集模块工作；图像采集模块,用于采集被测钢板表面图像；图像处理模块,用于对被测钢板表面图像进行预处理和缺陷检测；图像分割存储模块,用于对被测钢板表面图像进行分割；图像显示模块,用于对被测钢板图像、被测钢板对应的缺陷信息进行显示。方法基于上述系统实现缺陷检测。本发明能实现非接触式钢板缺陷检测,并对高分辨率钢板表面图像和缺陷信息进行显示,具有采集速度快、分辨率高、显示速度快且流畅、检测精度高等特点,具有广阔的应用前景。(The invention discloses a steel plate surface defect detection system and method based on machine vision, wherein the system comprises a transmission module, a detection module and a control module, wherein the transmission module is used for driving a detected steel plate to move; the laser speed measuring module is used for generating a signal for controlling the acquisition control module to work; the acquisition control module is used for controlling the image acquisition module to work; the image acquisition module is used for acquiring the surface image of the steel plate to be detected; the image processing module is used for preprocessing the surface image of the detected steel plate and detecting defects; the image segmentation storage module is used for segmenting the surface image of the measured steel plate; and the image display module is used for displaying the image of the measured steel plate and the defect information corresponding to the measured steel plate. The method realizes defect detection based on the system. The invention can realize non-contact steel plate defect detection, displays the high-resolution steel plate surface image and defect information, has the characteristics of high acquisition speed, high resolution, high display speed, smoothness, high detection precision and the like, and has wide application prospect.)

1. A steel plate surface defect detection system based on machine vision is characterized by comprising: the device comprises a transmission module, a laser speed measuring module, an acquisition control module, an image acquisition module, an image processing module, a display module and a segmentation storage module;

the transmission module is used for driving the steel plate to be measured to move along a horizontal plane;

the laser speed measuring module is used for measuring the movement speed of the steel plate to be measured and converting the movement speed into a signal for controlling the acquisition control module to work;

the acquisition control module is used for controlling the image acquisition module to work;

the image acquisition module is used for acquiring the surface image of the steel plate to be detected and transmitting the acquired image to the image processing module;

the image processing module is used for preprocessing the surface image of the detected steel plate acquired by the image acquisition module and detecting the defects, and acquiring the position and area information of the defects;

the image segmentation and storage module is used for segmenting the surface image of the measured steel plate acquired by the image acquisition module according to the pyramid multi-level resolution model and storing the segmented surface image as a tile data set;

and the image display module is used for displaying the image of the measured steel plate acquired by the image acquisition module based on the tile data set and displaying the defect position and area information corresponding to the measured steel plate.

2. The steel plate surface defect detection system based on machine vision of claim 1, wherein the laser speed measurement module comprises a laser, the relative position between the laser and the steel plate to be detected is fixed, and the emergent light beam of the laser is vertically incident to the side surface of the steel plate to be detected.

3. The machine vision-based steel plate surface defect detection system as claimed in claim 1, wherein said acquisition control module is implemented using FPGA.

4. The machine vision-based steel plate surface defect detection system as claimed in claim 1, wherein said image acquisition module comprises an industrial linear array CCD camera, an optical lens and an image acquisition card, and is disposed right above the steel plate to be detected.

5. The steel plate surface defect detection system based on machine vision according to claim 1, wherein the image processing module preprocesses the measured steel plate surface image acquired by the image acquisition module, and specifically comprises: correcting uneven illumination, filtering and denoising; the defect detection comprises the following steps: and carrying out edge detection and morphological processing on the preprocessed image.

6. The steel plate surface defect detection system based on machine vision as claimed in claim 1, wherein said image display module displays the measured steel plate image collected by the image collection module based on said tile data set, and displays the defect position and area information corresponding to the measured steel plate, specifically through the web page constructed by openlayers3 framework, CSS, Javascript.

7. The detection method of the steel plate surface defect detection system based on the machine vision according to any one of the claims 1 to 6, characterized by comprising the following steps:

step 1, calibrating an industrial linear array CCD camera in an image acquisition module to obtain an internal reference matrix I of the industrial linear array CCD camera₁And distortion parameter matrix I₂；

Step 2, measuring the movement speed of the steel plate to be measured by using a laser speed measuring module, and converting the movement speed into a signal for controlling the work of an acquisition control module;

step 3, the acquisition control module controls the image acquisition module to acquire an image A of the surface of the steel plate to be detected;

step 4, utilizing the internal reference matrix I obtained in the step 1₁And distortion parameter matrix I₂Carrying out distortion correction on the surface image A of the measured steel plate collected in the step 3 to obtain a surface image B of the measured steel plate after the distortion correction;

step 5, preprocessing the surface image B of the detected steel plate and detecting the defects, and acquiring the position and area information of the defects;

step 6, segmenting the surface image B of the measured steel plate according to the pyramid multi-level resolution model, and storing the segmented image B as a tile data set;

and 7, displaying the image B on the surface of the measured steel plate by the image display module based on the tile data set, and displaying the defect position and area information corresponding to the measured steel plate.

8. The method for detecting the surface defects of the steel plate based on the machine vision as claimed in claim 7, wherein the step 5 of preprocessing the surface image B of the detected steel plate specifically comprises: correcting uneven illumination, filtering and denoising;

the method for detecting the defects of the surface image B of the detected steel plate specifically comprises the following steps: and carrying out edge detection and morphological processing on the preprocessed image.

9. The method for detecting surface defects of a steel plate based on machine vision according to claim 7, wherein the step 6 of segmenting the surface image B of the detected steel plate according to the pyramid multi-level resolution model and storing the segmented image B as a tile data set specifically comprises:

and dividing the surface image B of the steel plate to be detected into N layers of tile maps with the resolutions of r0, r1, r2 … and rN according to the pyramid multi-resolution model, and constructing and storing a tile data set according to the rule of the number of layers N-the number of rows Rn-the number of columns Cn.

10. The steel plate surface defect detection method based on machine vision as claimed in claim 7, wherein said image display module in step 7 displays a measured steel plate surface image B based on said tile data set, and displays defect position and area information corresponding to the measured steel plate, specifically through a web page constructed by openlayers3 framework, CSS, Javascript.

Technical Field

The invention belongs to the field of defect detection, and particularly relates to a steel plate surface defect detection system and method based on machine vision.

Background

The machine vision technology is to realize human vision function by a computer, namely to realize the recognition of an objective three-dimensional world by the computer, and mainly comprises the research on the aspects of image acquisition, processing, analysis, output, display and the like. Machine vision technology has been rapidly developed in recent 30 years as an important branch of computer science, and its application fields are spread throughout industry, agriculture, military affairs, etc. Through the crossover and penetration of computer technology to nondestructive testing technology, machine vision has become a very vital branch in the nondestructive testing technology, and a brand-new application field of the nondestructive testing technology is developed. Currently, industrial vision inspection systems are mainly used to improve production efficiency, control product quality during production, collect product data, and classify and select products.

In the production of steel products, the traditional detection methods, such as manual detection, eddy current detection, infrared detection and the like, have great disadvantages. The manual detection is simple and repetitive, high in speed and high in concentration, not only brings great pressure to detection personnel, but also reduces the moving speed of the steel plate in the visual detection process of the detection personnel, the corresponding rolling speed of the steel plate is reduced, the production efficiency is reduced inevitably, meanwhile, the detection personnel are inevitably subjected to the objective influences of fatigue, mood, feeling and technical level, the accuracy and quantification are difficult to achieve, and in addition, the memory storage and analysis of flaws are also difficult to compare; the eddy current detection is based on the principle of electromagnetic induction, although non-contact measurement can be realized and the speed is high, the penetration depth is limited, the eddy current detection needs to be close to the detected surface, the detection result is influenced when the roughness of the detected surface is high, and the detection precision is reduced; the infrared detection has more using limit conditions, and detection is generally carried out only in an off-line small range; therefore, the detection precision of the method is not high.

Disclosure of Invention

The invention aims to provide an online steel plate defect detection system and method with the advantages of non-contact, high detection efficiency, high detection precision and the like.

The technical solution for realizing the purpose of the invention is as follows: a steel plate surface defect detection system based on machine vision comprises: the device comprises a transmission module, a laser speed measuring module, an acquisition control module, an image acquisition module, an image processing module, a display module and a segmentation storage module;

the transmission module is used for driving the steel plate to be measured to move along a horizontal plane;

the laser speed measuring module is used for measuring the movement speed of the steel plate to be measured and converting the movement speed into a signal for controlling the acquisition control module to work;

the acquisition control module is used for controlling the image acquisition module to work;

the image acquisition module is used for acquiring the surface image of the steel plate to be detected and transmitting the acquired image to the image processing module;

the image processing module is used for preprocessing the surface image of the detected steel plate acquired by the image acquisition module and detecting the defects, and acquiring the position and area information of the defects;

the image segmentation and storage module is used for segmenting the surface image of the measured steel plate acquired by the image acquisition module according to the pyramid multi-level resolution model and storing the segmented surface image as a tile data set;

and the image display module is used for displaying the image of the measured steel plate acquired by the image acquisition module based on the tile data set and displaying the defect position and area information corresponding to the measured steel plate.

The detection method of the steel plate surface defect detection system based on the machine vision comprises the following steps:

step 1, calibrating an industrial linear array CCD camera in an image acquisition module to obtain an internal reference matrix I of the industrial linear array CCD camera₁And distortion parameter matrix I₂；

Step 2, measuring the movement speed of the steel plate to be measured by using a laser speed measuring module, and converting the movement speed into a signal for controlling the work of an acquisition control module;

step 3, the acquisition control module controls the image acquisition module to acquire an image A of the surface of the steel plate to be detected;

step 4, utilizing the internal reference matrix I obtained in the step 1₁And distortion parameter matrix I₂Carrying out distortion correction on the surface image A of the measured steel plate collected in the step 3 to obtain a surface image B of the measured steel plate after the distortion correction;

step 5, preprocessing the surface image B of the detected steel plate and detecting the defects, and acquiring the position and area information of the defects;

step 6, segmenting the surface image B of the measured steel plate according to the pyramid multi-level resolution model, and storing the segmented image B as a tile data set;

and 7, displaying the image B on the surface of the measured steel plate by the image display module based on the tile data set, and displaying the defect position and area information corresponding to the measured steel plate.

Compared with the prior art, the invention has the following remarkable advantages: 1) the laser speed measurement method is adopted to generate image acquisition signals, so that the images acquired by the linear array camera can be effectively corrected for geometric distortion, and the precision of subsequent defect detection is improved; 2) the high-speed linear array camera is matched with the acquisition card to acquire the surface image of the steel plate, so that the image acquisition efficiency is greatly improved, and the high-speed and accurate acquisition of the surface image of the steel plate is realized; 3) the pyramid multi-level resolution model is used for displaying the high-resolution large-size picture, so that the problems of slow response, unsmooth response and the like existing in the direct display of the high-resolution large-size picture are solved; 4) the invention realizes non-contact, automatic and intelligent defect detection of the steel plate on the production line.

The present invention is described in further detail below with reference to the attached drawing figures.

Drawings

FIG. 1 is a schematic structural diagram of a steel plate surface defect detection system based on machine vision according to the present invention.

FIG. 2 is a flow chart of the steel plate surface defect detection method based on machine vision according to the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

With reference to fig. 1, the present invention provides a steel plate surface defect detection system based on machine vision, comprising: the device comprises a transmission module, a laser speed measuring module, an acquisition control module, an image acquisition module, an image processing module, a display module and a segmentation storage module;

the transmission module is used for driving the measured steel plate to move along a horizontal plane;

the laser speed measuring module is used for measuring the movement speed of the steel plate to be measured and converting the movement speed into a signal for controlling the acquisition control module to work;

the acquisition control module is used for controlling the image acquisition module to work;

the image acquisition module is used for acquiring the surface image of the steel plate to be detected and transmitting the acquired image to the image processing module;

the image processing module is used for preprocessing the surface image of the detected steel plate acquired by the image acquisition module and detecting the defects, and acquiring the position and area information of the defects;

the image segmentation and storage module is used for segmenting the surface image of the steel plate to be detected, which is acquired by the image acquisition module, according to the pyramid multi-level resolution model and storing the segmented surface image as a tile data set;

and the image display module is used for displaying the image of the measured steel plate acquired by the image acquisition module based on the tile data set and displaying the defect position and area information corresponding to the measured steel plate.

Further, in one embodiment, the laser speed measuring module includes a laser, the relative position between the laser and the measured steel plate is fixed, and the outgoing beam of the laser is vertically incident to the side surface of the measured steel plate.

Further, in one embodiment, the acquisition control module is specifically implemented by an FPGA.

Further, in one embodiment, the image acquisition module comprises an industrial linear array CCD camera, an optical lens and an image acquisition card, and is disposed right above the measured steel plate.

Further, in one embodiment, the image processing module performs preprocessing on the surface image of the measured steel plate acquired by the image acquisition module, and specifically includes: correcting uneven illumination, filtering and denoising; the defect detection comprises the following steps: and carrying out edge detection and morphological processing on the preprocessed image.

Further, in one embodiment, the image display module displays the detected steel plate image acquired by the image acquisition module based on the tile data set, and displays the defect position and area information corresponding to the detected steel plate, specifically, displays the defect position and area information through a webpage constructed by the openlayers3 framework, the CSS, and the Javascript.

With reference to fig. 2, the invention provides a steel plate surface defect detection method based on machine vision, which comprises the following steps:

step 1, calibrating an industrial linear array CCD camera in an image acquisition module to obtain an internal reference matrix I of the industrial linear array CCD camera₁And distortion parameter matrix I₂；

Step 2, measuring the movement speed of the steel plate to be measured by using a laser speed measuring module, and converting the movement speed into a signal for controlling the work of an acquisition control module;

step 3, the acquisition control module controls the image acquisition module to acquire an image A of the surface of the steel plate to be detected;

step 4, utilizing the internal reference matrix I obtained in the step 1₁And distortion parameter matrix I₂Carrying out distortion correction on the surface image A of the measured steel plate collected in the step 3 to obtain a surface image B of the measured steel plate after the distortion correction;

step 5, preprocessing the surface image B of the detected steel plate and detecting the defects, and acquiring the position and area information of the defects;

step 6, segmenting the surface image B of the measured steel plate according to the pyramid multi-level resolution model, and storing the segmented image B as a tile data set;

and 7, displaying the image B on the surface of the measured steel plate by the image display module based on the tile data set, and displaying the defect position and area information corresponding to the measured steel plate.

Further, in one embodiment, the preprocessing the surface image B of the measured steel plate in the step 5 specifically includes: correcting uneven illumination, filtering and denoising;

the method for detecting the defects of the surface image B of the detected steel plate specifically comprises the following steps: and carrying out edge detection and morphological processing on the preprocessed image.

Further, in one embodiment, in step 6, the segmenting is performed on the measured steel plate surface image B according to the pyramid multi-level resolution model, and the segmented image B is stored as a tile data set, which specifically includes:

and dividing the surface image B of the steel plate to be detected into N layers of tile maps with the resolutions of r0, r1, r2 … and rN according to the pyramid multi-resolution model, and constructing and storing a tile data set according to the rule of the number of layers N-the number of rows Rn-the number of columns Cn.

Further, in one embodiment, in step 7, the image display module displays the image B of the surface of the measured steel plate based on the tile data set, and displays the defect position and area information corresponding to the measured steel plate, specifically, the defect position and area information is displayed through a web page constructed by openlayers3 framework, CSS, and Javascript.

The steel plate surface defect detection system and method based on the machine vision are realized based on the technology combining the machine vision and the image processing, the linear array CCD camera is adopted to match with the laser speed measurement to generate an external line trigger signal to acquire the steel plate image, then the image is preprocessed and the defect detection is carried out, and the detection result is displayed based on the pyramid multi-level resolution model.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.