一种基于等效电路模型的混合气体响应预测与浓度检测方法
By constructing an equivalent circuit model of a gas sensor array and combining parameter correlation iteration and Kalman filtering, the problems of large sample data volume and high computational complexity in mixed gas concentration detection are solved, achieving accurate mixed gas concentration detection and response prediction, reducing computational complexity and adapting to sensor array expansion.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- UNIV OF ELECTRONICS SCI & TECH OF CHINA
- Filing Date
- 2025-01-22
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies for detecting mixed gas concentrations suffer from problems such as large sample data volume and high computational complexity, which prevent electronic noses from accurately detecting the concentration of mixed gas components.
An equivalent circuit model-based approach is adopted. By constructing an equivalent circuit model of the gas sensor array and combining parameter correlation iteration and Kalman filtering, a gas sensor response and concentration detection model is established, and linear prediction and detection are achieved using small sample data.
It achieves accurate detection and response prediction of mixed gas concentration, reduces computational complexity, and can scale linearly with the increase of sensor array size, making it suitable for applications with large datasets.
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Figure CN119905167B_ABST