Magnetic Object Recognition via Dipole Parameter Extraction
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Solution Overview
Problem
Existing methods for recognizing moving magnetic objects are unreliable due to position and orientation dependencies, often requiring RFID tags or predetermined trajectories, which limit flexibility and accuracy.
Innovation Solution
A method using an array of magnetometers to calculate distinctive characteristics independent of object position and orientation, combined with systems of equations to determine magnetic dipoles' positions, orientations, and amplitudes, and an algorithm to minimize errors, enabling reliable recognition regardless of object movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If magnetometer measurements are used to recognize magnetic objects, then recognition capability is provided, but reliability deteriorates due to position and orientation dependencies
Solution Approach 1:
The patent transforms the raw magnetometer measurements (which depend on position and orientation) into derived parameters called distinctive features. These features are calculated by solving systems of equations that relate the magnetic field measurements to the physical characteristics of the object (number of dipoles, their positions, orientations, and magnetic moments). The transformation converts position-dependent measurements into position-independent distinctive features, resolving the contradiction between recognition capability and reliability.
2Reliability
If RFID tags are attached to magnetic objects for recognition, then recognition reliability is improved, but device complexity increases
Solution Approach 1:
The patent enables magnetic objects to be recognized through their inherent magnetic properties without requiring additional identification devices. The magnetic dipoles naturally present in the object (from magnetic materials like permanent magnets or magnetizable components) serve as the recognition feature. The system extracts distinctive features directly from the magnetic field generated by these inherent dipoles, eliminating the need for RFID tags or other active identification components.
3Measurement precision
If predetermined paths are required for magnetic object movement, then recognition accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The patent moves the problem from the spatial domain to the parameter space domain. Instead of controlling or restricting the object's movement in physical space (predetermined paths), the system transforms the position-dependent magnetic field measurements into position-independent distinctive features through mathematical processing. This dimensional transformation allows objects to move freely in space while maintaining recognition accuracy, as the distinctive features remain invariant to position and orientation changes.
4Measurement precision
If systems of equations are used to determine magnetic dipoles parameters, then recognition precision is improved, but computational complexity increases
Solution Approach 1:
The patent segments the complex problem of recognizing arbitrary magnetic objects into a standardized framework based on magnetic dipole models. By representing objects as collections of magnetic dipoles with specific parameters (positions, orientations, magnetic moments), the system breaks down the recognition task into solving systems of equations that relate measurements to these parameters. This segmentation enables precise parameter determination while maintaining computational tractability through the structured mathematical approach.
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 allows for accurate recognition of multiple magnetic objects with increased reliability and precision, even when they are moving, by using an array of magnetometers and solving non-linear systems of equations to determine the magnetic dipoles' parameters.
Implementation Method 1
a network of magnetometers arranged in a predetermined geometry... each magnetometer in the network measuring a magnetic field
Data Source
Figure 1~2
Figure 3~5
AI summary
This automatic recognition method comprises: a) calculating (80) an error representing the deviation between an estimate of the values of magnetometer measurements when the positions, orientations and amplitudes of the magnetic moments of P dipoles are equal to those determined, and the values of the magnetometer measurements taken; b) selecting another system of equations relating each measurement of a three-axis magnetometer to the position, orientation and amplitude of the magnetic moment of P' magnetic dipoles; c) calculating (90) at least one distinctive characteristic of the object presented from the position or the orientation or the amplitude of the magnetic moment of each dipole determined in step a) with the system of equations that minimises the error calculated in step b); and d) recognising (108) the magnetic object presented if the calculated distinctive characteristics correspond to those of a known object, and otherwise not recognising this object.