Wire Rope Defect Detection Using Magnetic Flux and MFL Signal Fusion
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Solution Overview
Problem
Current nondestructive testing methods for wire ropes fail to accurately distinguish between internal and external defects, nor can they quantify defect depth, leading to low detection accuracy and safety concerns due to incomplete fracture detection.
Innovation Solution
A nondestructive testing method and device that acquires and preprocesses magnetic flux and magnetic flux leakage signals from wire ropes, using trained higher-degree equations or multi-layer neural networks to differentiate between internal and external defects and calculate defect depth by analyzing signal thresholds and peak-to-peak values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If magnetic flux detection is used, then both external defect and internal defect can be detected, but the detection accuracy is poor when axial width of defect is small and quantitative detection cannot be performed
Solution Approach 1:
The patent combines magnetic flux detection and MFL detection into a unified detection system that uses both detection methods simultaneously. The magnetic flux detection provides broad coverage for detecting both internal and external defects, while MFL detection enhances precision for small axial width defects. The results from both methods are fused to achieve accurate quantitative detection and classification.
Solution Approach 2:
The patent introduces a defect classification model as an intermediary that processes detection results from both magnetic flux and MFL methods. This model classifies defects into types (external, internal, or both) based on the combined detection data, enabling accurate quantitative analysis and resolving the limitation of individual methods.
2Measurement precision
If MFL detection is used, then defect width can be detected accurately, but defect depth cannot be quantitatively detected
Solution Approach 1:
The patent segments the defect characterization into multiple independent parameters: defect width (from MFL detection), defect depth (from magnetic flux detection and classification model), and defect type (from classification model). By dividing the detection task into these segments, each parameter can be optimized independently, allowing MFL to handle width detection while the classification model recovers depth information.
Solution Approach 2:
The patent transitions from one-dimensional MFL surface detection to three-dimensional defect characterization by integrating magnetic flux detection data and using a classification model. This adds depth and type dimensions to the detection, transforming the limited surface width measurement into comprehensive 3D defect information including width, depth, and classification.
3Ease of operation
If prior detection methods are used, then detection can be performed, but internal defect and external defect cannot be distinguished
Solution Approach 1:
The patent implements a feedback mechanism where the classification model continuously refines defect type identification based on detection results. The model receives raw detection data from magnetic flux and MFL methods, processes this information, and provides feedback classification results that distinguish between external defects, internal defects, and combined defects. This feedback loop enables accurate defect type differentiation while maintaining operational simplicity.
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 approach enables accurate and quantitative detection of all defects, distinguishing between internal and external defects and calculating defect depth, thereby enhancing safety and reducing economic losses by preventing complete wire rope fracture.
Implementation Method 1
a wire rope to be magnetized to a saturation state or an approximately saturation state
Implementation Method 2
both the external defect and the internal defect can be detected through nondestructive magnetic flux detection
Data Source
AI summary
A nondestructive testing method for detecting and distinguishing internal and external defects of a wire rope includes: acquiring a magnetic flux signal and a MFL signal of a detected wire rope; preprocessing the magnetic flux signal and the MFL signal of the detected wire rope; comparing a preprocessed magnetic flux signal and a preprocessed MFL signal with a preset magnetic flux signal threshold and a preset MFL signal threshold respectively, and calculating a defect position; extracting a magnetic flux signal of a defect and an MFL signal of the defect based on the defect position; calculating a defect width of the detected wire rope based on the magnetic flux signal of the defect and the MFL signal of the defect; calculating a defect cross-sectional area loss of the detected wire rope based on the defect width; and determining whether the defect is the internal defect or the external defect.