Crack Detection in Metallurgical Vessel Linings
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Solution Overview
Problem
Current technologies lack the capability to detect and measure cracks in the refractory material of metallurgical vessels, which are critical for preventing catastrophic failures and extending the life of these vessels.
Innovation Solution
A scanning device generates a cloud of data points, and a controller fits a polygonal mesh through these points to detect cracks by identifying portions that extend beyond a threshold distance, allowing for the calculation of crack dimensions such as depth, location, orientation, length, and width.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional laser scanning is used to measure refractory thickness, then thickness measurement capability is provided, but crack detection capability is lacking
Solution Approach 1:
The patent segments the crack detection process into distinct computational steps: generating a point cloud from laser scans, creating a polygonal mesh representation, fitting a minimum surface to the mesh, and identifying polygons that extend beyond the minimum surface by a threshold distance. This segmentation transforms a complex crack detection problem into manageable computational stages, enabling crack detection without requiring fundamentally new scanning hardware.
2Reliability
If visual inspection by experienced operators is used, then crack detection is possible, but the approach requires long downtime and is not scalable
Solution Approach 1:
The patent replaces the mechanical/visual inspection system with an automated optical-mechanical system. Instead of relying on human operators to visually inspect refractory surfaces, the system uses laser scanning to capture geometric data and automated algorithms to detect cracks. This substitution eliminates the need for prolonged manual inspection while maintaining or improving detection reliability through consistent, repeatable measurements.
3Reliability
If frequent inspection is performed to detect cracks early, then vessel safety is improved, but inspection time and operational disruption increase
Solution Approach 1:
The patent enables efficient periodic inspection by rapidly capturing the entire refractory lining geometry through laser scanning. The system can quickly acquire point cloud data and process it through mesh generation and minimum surface fitting to identify cracks. This periodic scanning approach allows frequent safety checks with minimal operational disruption, as the automated process completes inspections much faster than manual methods.
4Loss of information
If detailed crack characterization is performed to determine severity, then maintenance decisions are improved, but measurement and analysis complexity increases
Solution Approach 1:
The patent characterizes cracks in multiple dimensions by analyzing the three-dimensional spatial relationships of polygons extending beyond the minimum surface. The system determines crack depth by measuring the distance from the minimum surface to the outer surface at crack locations, identifies crack orientation through the spatial arrangement of affected polygons, and calculates crack length and width from the mesh geometry. This multi-dimensional characterization provides comprehensive crack information without requiring additional physical measurement devices.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables the detection and characterization of cracks, providing critical information for determining the severity of damage and the need for maintenance or re-lining, thereby enhancing safety and extending the operational life of metallurgical vessels.
Implementation Method 1
A widely used conventional method for measuring the remaining lining thickness of metallurgical vessels is laser scanning.
Implementation Method 2
A sensor on the instrument measures the amount of time it takes for each pulse to bounce back from the target surface to the scanner through a given field of view
Data Source
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AI summary
Apparatuses, methods, and systems are disclosed to detect and measure cracks in the lining of a container. A typical apparatus includes a scanning device to acquire a cloud of data points by measuring distances from the scanning device to a plurality of points on the surface of lining material and a controller to fit a polygonal mesh and a minimum surface through the cloud of data points, a crack being detected by a portion of the polygonal mesh containing a connected group of polygons that extends past the minimum surface beyond a threshold distance.