Proximity Sensor Gap Estimation With Nonlinear Inductance Modeling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing proximity sensing systems introduce substantial errors in gap estimation when relying on linear relationships, especially outside a small range, and fail to account for the non-negligible relationship between sensor resistance and gap, leading to inaccurate measurements and false alarms.
Innovation Solution
A non-linear model is incorporated to estimate the gap parameter, accounting for the relationship between inductance and resistance, and compensating for the influence of sensor temperature and cable length, thereby increasing the range of accurate gap estimation and reducing errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If linear relationships are used to estimate gap from sensor inductance, then the system is simple to operate, but substantial error is introduced outside a small gap range
Solution Approach 1:
The patent transforms the linear parameter relationship into a non-linear model that accounts for the actual physical relationship between inductance and gap. The system measures sensor resistance to determine temperature, then uses temperature-compensated inductance measurements with non-linear equations to calculate gap, thereby maintaining accuracy across extended gap ranges while preserving operational simplicity through automated compensation.
2Device complexity
If sensor resistance is assumed constant, then calculations are simplified, but additional error is introduced into gap estimation
Solution Approach 1:
The system implements feedback by measuring sensor resistance to determine temperature, then using the temperature information to compensate inductance measurements. The measured resistance value feeds back into the calculation process to adjust the gap estimation, creating a closed-loop system that eliminates the error introduced by assuming constant resistance while adding only minimal computational complexity.
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
The solution provides a more accurate and robust gap estimation over a larger range, reducing false alarms and enhancing confidence in notifications, while tolerating variations due to vibrations, turbulence, and rigging changes.
Implementation Method 1
the effective inductance of the sensor, when measured, varies with the gap between the sensor and its target. An inductance proximity sensing system measures the inductance of the proximity sensor, and uses the measured inductance to estimate the gap between the sensor and its target.
Implementation Method 2
Gap calculations made by existing proximity sensing systems compensate for certain factors using estimates of cable-induced inductance as well as estimates of temperature using sensor resistance measurements.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method is provided for sensing proximity of a target. The method includes sensing inductance associated with a magnetic field, wherein the inductance is affected by the target when the target is proximate the magnetic field. The method further includes providing the sensed inductance for processing. The processing includes determining an inductance value from at least the sensed inductance and estimating a parameter of a gap between a location of sensing the inductance and the target as a function of the inductance value and application of a nonlinear model of a relationship between the gap and inductance.