Gas Identification System with Humidity-Corrected Sensor Features
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Solution Overview
Problem
Conventional gas identification methods experience reduced accuracy due to moisture in sample gases, which affects the reliability of gas identification processes.
Innovation Solution
A gas identification method and system that utilize a sensor to output signals based on gas adsorption concentration, incorporating humidity data correction to enhance feature extraction and identification accuracy, employing a trained model to correct features based on humidity data and generate pseudo datasets for improved identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional gas identification methods are used without humidity correction, then the identification process is simple, but the identification accuracy is reduced due to moisture in the sample gas
Solution Approach 1:
The patent applies preliminary action by obtaining humidity data and correcting signal features before gas identification is performed. The humidity data is acquired from humidity sensors, and correction coefficients are calculated in advance based on the relationship between humidity and sensor signals. This preliminary correction process eliminates the adverse effect of moisture on identification accuracy while maintaining a relatively simple system structure.
Solution Approach 2:
The patent introduces humidity data and correction coefficients as intermediary elements between the raw sensor signal and the final gas identification result. The correction coefficient acts as a mediator that adjusts the signal features based on humidity levels, allowing the identification system to compensate for moisture effects without requiring complex hardware modifications.
2Measurement precision
If humidity correction is applied using trained models, then the identification accuracy is improved, but the processing time and computational complexity increase
Solution Approach 1:
The patent performs preliminary actions by pre-calculating correction coefficients based on humidity data before the actual gas identification process. The trained model is used in advance to establish the relationship between humidity and signal features, creating a lookup table or set of correction parameters that can be quickly applied during real-time measurement, thereby reducing processing time during actual operation.
Solution Approach 2:
The patent applies partial correction by focusing only on the most significant humidity-related features that need adjustment. Instead of completely reprocessing all signal data through the trained model, the system applies targeted corrections to specific signal features using pre-computed correction coefficients, reducing the computational burden while maintaining identification accuracy.
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 method significantly improves gas identification accuracy by reducing the influence of moisture, allowing for precise identification even with varying humidity levels, thereby enhancing the reliability of gas identification processes.
Implementation Method 1
a sensor that outputs a signal according to an adsorption concentration of a gas
Data Source
AI summary
A gas identification method includes: (a) obtaining a signal outputted from an odor sensor exposed to a sample gas during a predetermined measurement period; (b) extracting a feature of the signal obtained in (a); (c) obtaining humidity data indicating a humidity of the sample gas; (d) correcting the feature extracted in (b), based on the humidity data obtained in (c); and (e) identifying the sample gas by using a trained model for identifying the sample gas, based on the feature corrected in (d), and outputting an identification result.