Linear Position Sensor Calibration via Magnetic Field Distortion Compensation
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Solution Overview
Problem
Position sensors employing magnetic sensing techniques face inaccuracies when used within enclosures that attenuate or distort magnetic fields, leading to incorrect position measurements.
Innovation Solution
A method and device for calibrating position sensors by generating an expected output signal from magnetic field sensors, superimposing it over actual output signals, iteratively shifting to minimize error, and determining the object's position within the enclosure, effectively compensating for magnetic field alterations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If magnetic field sensors are used to sense position within an enclosure, then contactless sensing and durability are improved, but measurement precision deteriorates due to magnetic field attenuation and distortion
Solution Approach 1:
The system performs preliminary calibration by moving the magnetic target through known reference positions and recording the actual sensor outputs. These reference measurements are stored and used to generate expected output signals for any given position, enabling the system to compensate for enclosure-induced magnetic field distortions during normal operation.
Solution Approach 2:
The system compares actual sensor outputs with expected outputs derived from calibration data. By calculating the difference between measured and expected values, the system generates correction signals that compensate for magnetic field distortions, continuously refining position measurements despite enclosure attenuation and distortion effects.
2Measurement precision
If calibration procedures are implemented to compensate for magnetic field distortion, then measurement precision is improved, but device complexity increases due to additional signal processing
Solution Approach 1:
The system creates a digital copy of the magnetic field characteristics during calibration by recording actual sensor outputs at known positions. This calibration data model is then used to predict expected sensor outputs for any position, allowing the system to compensate for distortions through software-based comparison rather than complex hardware modifications.
Solution Approach 2:
The system transforms the calibration data into lookup tables or mathematical models that map positions to expected sensor outputs. During operation, the system changes parameters by comparing actual versus expected outputs and applying correction factors, simplifying the compensation process through parameter transformation rather than complex real-time calculations.
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 position sensing of objects within enclosures that attenuate or distort magnetic fields, with minimal additional hardware and signal processing resources, improving measurement precision.
Implementation Method 1
the linear position sensor may sense a position of a magnetic target that is coupled to the object relative to one or more magnetic field sensors disposed along a base of the linear position sensor
Implementation Method 2
the one or more magnetic field sensors may include magnetoresistive (MR) sensors, including anisotropic magnetoresistive (AMR) sensors, Hall effect sensors, or other magnetic sensors
Implementation Method 3
the one or more magnetic field sensors may include magnetoresistive (MR) sensors, including anisotropic magnetoresistive (AMR) sensors, Hall effect sensors
Data Source
AI summary
Techniques are described for sensing a position of an object located within an enclosure over a position range. The techniques include generating an expected output signal of each of a plurality of magnetic field sensors disposed along an outer surface of the enclosure, receiving actual output signals from the sensors, wherein each actual output signal indicates a relative proximity of a magnetic target coupled to the object to the corresponding sensor. The techniques further include superimposing the expected output signal over the actual output signals, and iteratively shifting the expected output signal over position relative to the actual output signals and comparing the shifted expected output signal to the actual output signals, until the expected output signal compared to the actual output signals corresponds to a substantially minimized error parameter. The position of the object may then be determined based at least in part on the shifted expected output signal.