Adaptive Proximity Sensor Thresholds for Noise-Robust Kick Detection
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Solution Overview
Problem
Existing sensor systems for motorized vehicle doors face challenges in reliably detecting operator-intended events in noisy environments, leading to either excessive power consumption or delayed reactions due to fixed threshold settings.
Innovation Solution
An adaptive method that dynamically adjusts the threshold value based on sampled sensor signals, excluding previous signals to prevent false triggers and optimize sensitivity according to noise levels, using statistical measures and sampling techniques to generate a trigger signal effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a low fixed threshold value is used to detect events quickly, then response speed is improved, but false triggers due to noise increase and power consumption rises
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed threshold to a dynamically adaptive threshold that automatically adjusts based on the measured noise level in the environment. The threshold is no longer static but changes over time to match the actual noise conditions, allowing the system to maintain high sensitivity when noise is low and reduce false triggers when noise is high.
Solution Approach 2:
The patent implements parameter changes by modifying the threshold value based on the measured noise characteristics. The system measures the noise level in the environment and uses this information to adjust the threshold parameter accordingly, changing it from a fixed value to a variable that adapts to environmental conditions.
2Reliability
If a high fixed threshold value is used to avoid false triggers, then reliability is improved, but response speed decreases
Solution Approach 1:
The system dynamically adjusts the threshold based on real-time noise measurements, allowing it to be high when noise is present (avoiding false triggers) and low when noise is absent (maintaining fast response). This dynamic adaptation resolves the contradiction by making the threshold flexible rather than fixed.
Solution Approach 2:
The threshold parameter is changed from a fixed high value to a variable that adapts to environmental noise levels, enabling the system to maintain reliability while preserving fast response capability when conditions permit.
3Productivity
If a low threshold is used to detect events quickly, then productivity is improved, but energy consumption increases due to frequent advanced measurements
Solution Approach 1:
The system changes the threshold parameter dynamically based on noise measurements, allowing it to operate at low thresholds (high productivity) when noise is low and automatically raise the threshold when noise is detected, thereby reducing unnecessary advanced measurements and saving energy.
Solution Approach 2:
The system uses feedback from noise level measurements to adjust the threshold parameter. By continuously monitoring the environment and feeding this information back to the threshold adjustment mechanism, the system can optimize its detection sensitivity and avoid unnecessary power consumption from false triggers.
Data Source
AI summary
A method of operating a sensor system having at least one proximity sensor, with regard to generating a trigger signal indicative of an occurrence of an operator-intended event in the presence of noise. The method includes repetitive steps of: acquiring the sensor signal at specified sampling times, comparing a value obtained as a presently sampled sensor signal with a presently valid first threshold value, generating a trigger signal if the value obtained as the presently sampled sensor signal is as large as or exceeds the presently valid first threshold value, omitting to generate a trigger signal if the value obtained as the presently sampled sensor signal is less than or equal to the presently valid first threshold value, forming a subset out of the sampled sensor signals, determining an update value for the first threshold value, and replacing the presently valid first threshold value by the update value.