Research Of Key Technology On On-line Surface Defects Detection System For Steel Plate Based On Computer Vision

The technique of on-line surface defects detection for steel plate has become the restriction of the Steel and Iron production enterprises developing to the modernized manufacturing industry with high efficiency, intellectualization and automation, so it's been a hot field researched by foreign and domestic scholars. Sponsored by scientific research academe specific fund of NSTS, the project is developed to detect surface defects for steel plate based on computer vision. In view of systematic specifications, such as broad width, simplicity, modularization, advancement etc, and combining with the latest development of relevant theory and technology, the scheme of linear CCD scanning method based on computer vision is brought forward to realize on-line non-destructive surface inspection for steel plate, and key technology of system is discussed. The main work included in the dissertation is shown as follows:1. In order to satisfy the requirements of high speed, broad width and high resolution, the linear CCD scanning scheme is put forward to detect the surface defects of steel plate based on width division using on-line computer vision. Taking the characteristics of surface defects into account, optimal configuration of receiving mode containing bright-field and dark-field is analyzed to make defects effectively detected;2. The slit-type high-frequency fluorescent lamp is designed, solving the problem of luminance under high speed movement, and this light source has some excellent characteristics, such as high brightness, good uniformity, high stability and low cost and so on;3. With a view to the characteristics of surface defects for steel plate and the demand of system performance, the algorithm flow of image-processing applied to the surface defect of steel plate is fully discussed, and feasible algorithm is presented at each processing step in the paper, Main surface defects such as hole, inclusion, rolling skin, scratch and roll-mark can be detected. Under the condition of meeting the precision, the application is realized using the optimized algorithm and multi-thread procedure structure, so its processing speed could satisfy the 2m/s running rate of steel plate.4. The dissertation not only defines spatial distribution of surface defects based on its speciality, but also discusses some pattern recognition methods, such as decision tree, Bayes classifier, nervous network means, and it also makes a specific exposition about BPNN that the rate of classifying defects is more than 90%. Because of the limitation of each classifier, compositive classifier is mainly discussed in the paper, making use of each others' advantages to effectively classify defects.5. Adopted multi-process scheme including real-time gathering system + near-real time processing system, and based on pipe-line theory, software structure is proposed in this paper. The optimized multi-thread procedure structure is introduced to the capturing application to realize the high speed acquiring, and the rate of capturing data reaches to 100Mbps, so it meets the requirement of system. In order to reduce the load of image-processing application, the real-time application not only captures image data, but also simultaneously detects ROI (Region of Interest) data. Near-real time processing system processes ROI file, and extracts special data of defects to distinguish the type of defect.7. Two kinds of prototype, including low speed translational prototype and high speed rotary prototype simulation systems, are developed. The highest speed is 1.5m/s in the experiment. Feasibility and validation is verified through experiments.This project was checked and accepted smoothly by Ministry of Science and Technology at January 2007.