Chemo-Resistive Gas Sensor with Time-Variant Weighting for Accuracy
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Solution Overview
Problem
Existing gas sensing technologies face challenges in accurately estimating gas concentrations in mixtures due to the intrinsic instability of chemo-resistive gas sensors, calibration inaccuracies, and cross-sensitivities, particularly in complex real-world scenarios with varying gas concentrations and noisy data sets.
Innovation Solution
A gas sensing device utilizing chemo-resistive gas sensors with temperature modulation and a decision-making block comprising a weighting block and a trained model-based algorithm stage, which applies time-variant weighting functions to feature samples to enhance accuracy and stability, and includes feature extraction stages for dynamic characteristic analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If chemo-resistive gas sensors are used for gas concentration sensing, then the device can detect gas concentrations, but the sensors exhibit intrinsic instability and calibration inaccuracies
Solution Approach 1:
The patent applies parameter changes by modulating the temperature of the gas sensors dynamically during operation. The temperature is varied between a first temperature (for recovery) and a second temperature (for sensing), which changes the sensor characteristics and allows differentiation between stable and unstable signal components. This temperature modulation enables the system to compensate for sensor instability and calibration drift without requiring frequent recalibration.
Solution Approach 2:
The patent implements feedback through an information extraction block that continuously analyzes sensor signals and a decision-making block that uses trained models to interpret the extracted features. The system processes signal samples, extracts features related to sensor stability, and uses machine learning models to compensate for instability in real-time. This feedback mechanism allows the system to adapt to sensor drift and maintain measurement accuracy.
2Measurement precision
If geographically distributed sensor systems are used, then gas concentration estimation can be improved, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent segments the gas sensing system into multiple functional blocks: gas sensors for signal generation, an information extraction block for feature analysis, and a decision-making block with trained models for final interpretation. This segmentation allows each component to perform a specific function efficiently, reducing overall system complexity while maintaining high measurement precision through specialized processing at each stage.
Solution Approach 2:
The patent introduces an information extraction block as an intermediary between the raw sensor signals and the decision-making block. This intermediary processes the raw signals, extracts relevant features, and prepares them for analysis by the trained models. This intermediate processing step simplifies the overall system architecture by preprocessing data before it reaches the complex decision-making algorithms.
3Measurement precision
If temperature modulation is applied to gas sensors, then sensor stability and measurement accuracy improve, but energy consumption increases
Solution Approach 1:
The patent applies periodic action by modulating the sensor temperature in cycles between a first temperature (recovery phase) and a second temperature (sensing phase). Rather than maintaining a constantly high temperature, the system periodically switches between two temperature states, reducing average power consumption while still achieving the stability and accuracy benefits of temperature modulation during the sensing phases.
Solution Approach 2:
The patent implements dynamic temperature control where the sensor temperature is actively adjusted based on operational requirements. The system dynamically switches between recovery and sensing modes, optimizing the temperature at each phase to balance measurement accuracy with energy consumption. This dynamic approach allows the system to use higher temperatures only when necessary for accurate sensing rather than maintaining high temperature continuously.
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 robust and accurate gas concentration estimation, capable of handling calibration inaccuracies and cross-sensitivities, with low material costs and suitable for integration into consumer electronics, effectively addressing the challenges of complex gas mixtures and real-world scenarios.
Implementation Method 1
one or more heating elements for heating the gas sensors according to one or more first temperature profiles during the recovery phases and according to one or more second temperature profiles during the sense phases
Implementation Method 2
one or more chemo-resistive gas sensors, wherein each of the gas sensors is configured for generating signal samples corresponding to a concentration of one of the one or more gases
Data Source
AI summary
A gas sensing device includes chemo-resistive gas sensors; heating elements for heating each of the gas sensors; an information extraction block for receiving signal samples and for generating representations for the received signal samples; and a decision making block configured for receiving the representations, wherein the decision making block comprises a weighting block and a trained model based algorithm stage, wherein the weighting block receives feature samples of the representations and applies time-variant weighting functions to the feature samples of the respective representation in order to calculate a weighted representation including weighted feature samples.