Surface defects inspection method in hot slab continuous casting process

Zhao, Li; Ouyang, Qi; Chen, D F; Wen, Liang

doi:10.1179/1743281211y.0000000025

Cited by 12 publications

(9 citation statements)

References 6 publications

(10 reference statements)

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“…The laser point, camera, and laser transmitter formed a triangle, so as to carry out the damage assessment of the aircraft panel. The laser scanner is one of the more common measurement tools in the application field of 3D surface detection of metal planar materials [ 149 , 150 , 151 , 152 , 153 ]. Landstorm and Thurley [ 150 ] developed a crack detection strategy for steel plates with 3D surface contour data collected by laser triangulation.…”

Section: Taxonomy Of Three-dimension Defect Detection Methodsmentioning

confidence: 99%

“…The system first uses mathematical morphology to segment the data and then assigns a crack probability to the structural connectivity area by the logistic regression model, which detects 70% of the total length of the manually labeled cracks in the connectivity area. Zhao et al [ 151 ] established a 3D quantitative detection method for surface defects of continuous casting slab using an optimized laser fringe imaging algorithm by using a laser beam and two-beam array charge-coupled cameras (CCD). By comparing CCD camera and image data fusion technology, the optimal imaging method of laser fringe projection on the hot plates surface was studied, and the detection accuracy of 3D shape defects was improved.…”

Section: Taxonomy Of Three-dimension Defect Detection Methodsmentioning

confidence: 99%

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Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

Fang

Luo

Zhou

et al. 2020

Sensors

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The computer-vision-based surface defect detection of metal planar materials is a research hotspot in the field of metallurgical industry. The high standard of planar surface quality in the metal manufacturing industry requires that the performance of an automated visual inspection system and its algorithms are constantly improved. This paper attempts to present a comprehensive survey on both two-dimensional and three-dimensional surface defect detection technologies based on reviewing over 160 publications for some typical metal planar material products of steel, aluminum, copper plates and strips. According to the algorithm properties as well as the image features, the existing two-dimensional methodologies are categorized into four groups: statistical, spectral, model, and machine learning-based methods. On the basis of three-dimensional data acquisition, the three-dimensional technologies are divided into stereoscopic vision, photometric stereo, laser scanner, and structured light measurement methods. These classical algorithms and emerging methods are introduced, analyzed, and compared in this review. Finally, the remaining challenges and future research trends of visual defect detection are discussed and forecasted at an abstract level.

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Section: Taxonomy Of Three-dimension Defect Detection Methodsmentioning

confidence: 99%

Section: Taxonomy Of Three-dimension Defect Detection Methodsmentioning

confidence: 99%

Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

Fang

Luo

Zhou

et al. 2020

Sensors

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“…To measure the height or depth of the surface cracks, there must be an unwrapping phase according to equations (2) and (4). An automated analysis of the fringe patterns is normally carried out by phase stepping of the fringe patterns.…”

Section: Measurement Principlesmentioning

confidence: 99%

Continuous casting slab surface crack depth measurement using sinusoidal phase grating method

Zhang

Ouyang

Sun

et al. 2013

Ironmaking & Steelmaking

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With the development of hot charging and direct rolling technology in continuous slab casting, there are increasing demands for the surface quality of hot continuously cast slab evoked by modern metal material fabrication. In order to reduce noise, which is caused by scale, water film and oscillation marks, during on-line detection of surface defects, a sinusoidal phase grating projection method is presented to detect the depth and surface profile of surface cracks in continuous slab casting. This technology, based on a deformed projected grating pattern, which carries three-dimensional information of the measured surface of the slab, can provide an absolute measurement of the depth of the surface defect by using a temporal phase unwrapping algorithm. The main advantage is that objects containing depth discontinuities of the crack are profiled as easily as smooth ones. The experimental results show the method has a high signal to noise ratio, and good applicability for automatic crack depth testing in continuous casting.

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“…Although the technical objectives to be improved have been identified, no manufacturer in the world has reported one-hundred percent defect-free CC semi-products manufacturing technology in such a complex and systematic setting [6]. Therefore, complementary technologies such as automatic nondestructive examination (NDE) for CC products surface quality evaluation have become essential in the promotion of HC-DR [7,8]. This is an advisable method to eliminate flaw segments according to accurate NDE evaluation results [9].…”

Section: Introductionmentioning

confidence: 99%

A Deep-Learning-based 3D Defect Quantitative Inspection System in CC Products Surface

Zhao

Zhang

et al. 2020

Sensors

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To create an intelligent surface region of interests (ROI) 3D quantitative inspection strategy a reality in the continuous casting (CC) production line, an improved 3D laser image scanning system (3D-LDS) was established based on binocular imaging and deep-learning techniques. In 3D-LDS, firstly, to meet the requirements of the industrial application, the CCD laser image scanning method was optimized in high-temperature experiments and secondly, we proposed a novel region proposal method based on 3D ROI initial depth location for effectively suppressing redundant candidate bounding boxes generated by pseudo-defects in a real-time inspection process. Thirdly, a novel two-step defects inspection strategy was presented by devising a fusion deep CNN model which combined fully connected networks (for defects classification/recognition) and fully convolutional networks (for defects delineation). The 3D-LDS’ dichotomous inspection method of defects classification and delineation processes are helpful in understanding and addressing challenges for defects inspection in CC product surfaces. The applicability of the presented methods is mainly tied to the surface quality inspection for slab, strip and billet products.

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Surface defects inspection method in hot slab continuous casting process

Cited by 12 publications

References 6 publications

Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

Continuous casting slab surface crack depth measurement using sinusoidal phase grating method

A Deep-Learning-based 3D Defect Quantitative Inspection System in CC Products Surface

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