Cable Magnetic Leakage Graph Analysis for Broken-Wire Detection
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Solution Overview
Problem
Manual evaluation of multi-channel magnetic flux leakage testing for bridge cables is inefficient and prone to false determinations due to large data volumes and lift-off fluctuations, leading to reduced accuracy and increased difficulty in interpreting cable health status.
Innovation Solution
Abstract testing channels as a graph structure, where units are nodes and adjacency relationships are edges, and apply graph Fourier transform to determine low-frequency signal energy characteristics for automated cable damage detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual evaluation of multi-channel magnetic flux leakage testing is used, then cable damage detection can be performed, but evaluation efficiency is low and false determinations increase due to large data volumes
Solution Approach 1:
The patent extracts only the essential information from the multi-channel detection signals by computing graph Fourier transforms and analyzing low-frequency signal energy characteristics. This extraction process filters out redundant data while retaining the critical damage indicators, thereby reducing the effective data volume for manual evaluation and improving efficiency.
Solution Approach 2:
The patent introduces an intermediary processing layer using graph theory and signal processing algorithms. The graph structure represents the spatial relationships between testing units, and the graph Fourier transform serves as an intermediary that converts raw detection signals into processed graph signals with enhanced damage detection capabilities, reducing the complexity of manual data interpretation.
2Measurement precision
If manual evaluation of multi-channel detection signals is used, then cable damage can be detected, but interpretation difficulty increases due to lift-off fluctuations and background interference
Solution Approach 1:
The patent converts the harmful lift-off fluctuations and background interference signals into beneficial information by using graph Fourier transforms. The transform process highlights the frequency characteristics of genuine damage signals while suppressing the harmful fluctuations, turning what was previously noise into a filtering mechanism that improves detection accuracy.
Solution Approach 2:
The patent changes the parameter domain from the time/space domain of raw detection signals to the frequency domain through graph Fourier transforms. This parameter transformation converts the difficult-to-interpret time-domain signals with lift-off fluctuations into frequency-domain representations where damage characteristics are more distinct and easier to identify, reducing interpretation difficulty.
3Reliability
If multi-channel magnetic flux leakage testing with circumferential coverage is used, then comprehensive cable damage detection is achieved, but device complexity and data processing requirements increase
Solution Approach 1:
The patent merges the data from multiple testing channels into a unified graph structure that represents the circumferential arrangement of testing units. By combining the information from all channels through graph signal processing, the system maintains comprehensive damage detection coverage while reducing the complexity of individual channel analysis through integrated processing.
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
Improves accuracy and efficiency of cable damage detection by automating the process, effectively identifying even deeper-layer broken wires.
Implementation Method 1
Magnetic flux leakage testing methods have been widely used in non-destructive testing for cable damage
Implementation Method 2
determining a frequency spectrum of a graph signal in each sliced graph by means of a graph Fourier transform
Data Source
AI summary
A leakage magnetic field graph testing method for in-service cable damage includes: acquiring multi-channel detection signals corresponding to respective testing units in a testing probe; slicing the multi-channel detection signals acquired at different detection positions to acquire sliced detection data at a plurality of detection positions in an axial direction of a cable under test; mapping the sliced detection data to a pre-constructed graph structure to acquire sliced graphs, wherein the graph structure is established on the basis of spatial distribution of the testing units in the testing probe, the testing units serving as nodes, and adjacency relationships between the testing units in the testing probe serving as edges; and determining a frequency spectrum of a graph signal in each sliced graph by means of a graph Fourier transform.