Abstract
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.
Highlights
In recent years, with the advent of the industrial 4.0 enterprises undergoing transformation and upgrading manufacturing processes, continuous casting (CC) as a main solidification process for molten steel has been widely popularized to produce metal semi-finished products [1]
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]. Complementary technologies such as automatic nondestructive examination (NDE) for CC products surface quality evaluation have become essential in the promotion of hot charging and direct rolling (HC-DR) [7,8]
Machine vision (MV) in NDE combined with AI algorithms is becoming a burgeoning method which can perform with a fast response, a high signal-to-noise ratio and a strong anti-jamming capability [10,11] compared with ultrasonic, eddy current and other contact methods
Summary
With the advent of the industrial 4.0 enterprises undergoing transformation and upgrading manufacturing processes, continuous casting (CC) as a main solidification process for molten steel has been widely popularized to produce metal semi-finished products [1]. 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]. 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]. The MV merits make it more competitive in harsh environment application like
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
