Iron Scrap Imaging for Hidden Incompatible Object Detection
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Solution Overview
Problem
Existing methods for detecting incompatible objects in iron scraps, such as those using deep learning models, struggle to accurately identify objects present slightly beneath the surface or during transportation due to limited viewpoints and timing, leading to potential undetection and safety risks in electric furnaces.
Innovation Solution
A monitoring system that photographs iron scraps multiple times from different viewpoints or at different timings, using a learning model to identify the type and position of incompatible objects and calculate their probability, with adjustable camera settings and region extraction to enhance detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single photograph is taken of iron scraps in a stationary state, then the photographing process is simple and quick, but incompatible objects present slightly inside from the surface are difficult to detect
Solution Approach 1:
The system performs photographing operations in advance at multiple different timings during the transportation process, capturing images before the final inspection point. This preliminary multi-timing photographing ensures that incompatible objects are detected earlier, improving detection accuracy without requiring complex post-processing equipment.
Solution Approach 2:
The system transitions from single-point stationary photographing to multi-dimensional photographing by capturing images at multiple different viewpoints and timings during transportation. This dimensional expansion of the photographing process allows detection of objects that would be hidden in a single static view, significantly improving detection accuracy.
2Reliability
If iron scraps are photographed only when stationary on the truck bed, then the photographing setup is simple, but the lift magnet interferes with photographing and incompatible objects may be missed
Solution Approach 1:
The system transitions from static photographing (when the truck is stationary) to dynamic photographing during the transportation process. By capturing images while the lift magnet is moving and transporting iron scraps, the system eliminates interference from the lift magnet's position and achieves more reliable detection without complicating the operation.
Solution Approach 2:
The system performs photographing operations in advance during the transportation process, before the iron scraps reach the inspection point. This timing strategy captures images when the lift magnet is not interfering with the camera's angle of view, improving detection reliability while maintaining operational simplicity.
3Measurement precision
If multiple photographs are taken from different viewpoints and timings, then detection accuracy of hidden objects improves, but the time and resources required for processing increase
Solution Approach 1:
The system performs continuous photographing during the entire transportation process, capturing images at multiple timings without interrupting the workflow. This continuous action approach ensures that incompatible objects are detected reliably while utilizing the existing transportation time efficiently, minimizing additional time loss.
Solution Approach 2:
The system performs photographing operations in advance during transportation, rather than after loading is complete. This preliminary action utilizes the existing transportation time for detection purposes, reducing the need for separate inspection time and resources while maintaining high detection accuracy.
Data Source
AI summary
A monitoring system that is a system for monitoring an iron scrap, includes a photographing unit that photographs the iron scrap a plurality of times at different viewpoints or at different timings, an incompatible object identifying unit that inputs a plurality of images obtained by photographing with the photographing unit into a learning model to identify each of a type and a position of an incompatible object that is a target to be removed from the iron scrap and a probability of being an incompatible object, and an output unit that outputs each of the type and position of the incompatible object when the probability identified with the incompatible object identifying unit has exceeded a predetermined threshold value.