Magneto-Resistive Sensor Vehicle Detection Noise Filtering
Solution Overview
Problem
Existing magnetic sensor technologies, particularly magneto-resistive sensors, face challenges in reliably detecting the start and end times of a vehicle's passage due to high noise levels in the signals they produce, making it difficult to accurately determine these times.
Innovation Solution
A method that uses the recent variance of the raw signal from a magneto-resistive sensor to capture the start and end times by setting thresholds for variance detection and undetection, reducing noise sensitivity and improving reliability, which involves amplifying and digitizing the signal, and utilizing a processor with controllers like finite state machines or neural networks to generate start and end enable conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If magneto-resistive sensor is used to detect vehicle passage, then detection capability is provided, but noise in the signal makes determining start and end times erratic
Solution Approach 1:
The patent introduces an intermediary processing system that includes variance calculation and threshold comparison mechanisms. This intermediary layer processes the raw magnetic sensor signal before determining vehicle passage times, filtering out noise through statistical analysis (variance calculation) and conditional logic (threshold comparisons), thereby resolving the contradiction between maintaining detection capability and eliminating noise interference.
Solution Approach 2:
The patent changes the parameter analysis approach by transitioning from direct signal level analysis to variance-based analysis. By calculating the variance of signal levels over time windows and comparing against thresholds, the system transforms the noisy raw signal into reliable passage time determinations, effectively addressing the noise problem while preserving detection accuracy.
2Productivity
If rate of change analysis is used to analyze magnetic sensor signals, then signal processing is performed, but the effect of noise is worsened
Solution Approach 1:
The patent converts the harmful noise effect into a beneficial signal characteristic by analyzing variance. Instead of trying to eliminate noise directly, the system uses the statistical properties of noise (its variance) as part of the detection mechanism, comparing variance against thresholds to reliably determine passage times. This approach transforms the noise problem into a solution, improving both processing efficiency and noise resistance.
3Device complexity
If simple threshold detection is used without variance analysis, then device complexity is reduced, but detection reliability deteriorates due to noise sensitivity
Solution Approach 1:
The patent applies preliminary action by calculating variance and establishing threshold conditions before making the final passage time determination. This preparatory processing step involves computing statistical properties of the signal over time windows and setting up multiple conditional checks (variance thresholds, signal level thresholds) that must be satisfied before confirming a passage event, thereby ensuring reliable detection without excessive 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
This method significantly improves the reliability of detecting vehicle passage times by reducing noise sensitivity, allowing for more accurate determination of start and end times using the processed and raw signals from the magneto-resistive sensor.
Implementation Method 1
uses a magneto-resistive sensor, whose internal resistance changes due to fluctuations in the magnetic field it experiences
Data Source
AI summary
Method using raw signal from magneto-resistive sensor through the use of recent variance (RV) of raw signal (RS) for first-capture of first time RV crosses variance detect, second-capture start enable for first time when RS crosses above raw detect and RV above variance detect, third-capture ending time when RS crosses below raw undetect and RV below variance undetect. Starting and ending times are products of the process, often used for traffic flow counts. Apparatus supporting this method as a processor and/or a vehicular sensor node.


