Magnetic Dipole Density Calculation for Material Defect Detection
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Solution Overview
Problem
Existing material defect detection systems in metallic equipment, such as those in petroleum and petrochemical plants, struggle to accurately estimate shape information of defects like local corrosion, as they require numerous patterns for varying defect shapes and distances, making them impractical due to the large variety of possible defects.
Innovation Solution
A material defect detection device using a magnetic sensor array to calculate magnetic dipole density distribution and depth distribution based on measured magnetic field distribution, employing optimization problems and regularization terms to estimate defect shape information without relying on pattern matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pattern matching is used to detect material defects, then detection capability is achieved, but the system requires a great number of material defect patterns for various shapes and standoffs, making it impractical
Solution Approach 1:
The patent transforms the detection approach from pattern matching to physics-based magnetic field analysis. By measuring magnetic field strength at multiple positions and calculating depth information through mathematical relationships between magnetic field strength and depth, the system eliminates the need for extensive pattern libraries while maintaining detection capability across various defect shapes and standoffs.
2Measurement precision
If multiple material defect patterns are prepared for various shapes and standoffs, then shape information estimation accuracy is improved, but the system complexity and data requirements increase significantly
Solution Approach 1:
The patent replaces the mechanical approach of storing and comparing numerous pre-defined patterns with a mathematical calculation system. By using the relationship between magnetic field strength and depth (B = μ0*M/2, where B is magnetic field strength, μ0 is permeability of free space, and M is magnetization), the system calculates depth information directly from measurements, eliminating the need for extensive pattern libraries while maintaining or improving estimation accuracy.
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
Enables accurate and efficient estimation of material defect shape information in metallic equipment, reducing the need for extensive pattern preparation and improving detection precision across various defect shapes and distances.
Implementation Method 1
a magnetic field distribution in a predetermined region measured by a magnetic sensor array including a plurality of magnetic sensors
Data Source
AI summary
A material defect detection device that detects a material defect in a predetermined region of metallic equipment using a magnetic field distribution in the predetermined region measured by a magnetic sensor array including a plurality of magnetic sensors, the material defect detection device including: a processor that calculates a density distribution of magnetic dipoles in the predetermined region based on the magnetic field distribution and calculates a depth distribution of material defect in the predetermined region based on the density distribution of the magnetic dipoles.