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Abstract
The temperature modulation method is used to improve the selectivity of sensor, but there are still some deficiencies in the gas mixture recognition. The dynamic response law is insufficient understood because the dynamic response process itself is a complex change and there are some factors such as competition or suppression among multi-gases. This paper solves this problem by decomposing dynamic response and mapping static response. Based on the grain boundary barrier model, dynamic response is divided into dynamic temperature response and dynamic gas-sensing response. The dynamic temperature response is unaffected by the target gas and can be detected directly. Dynamic gas-sensing response cannot be detected directly but can be mapped through static responses. Therefore, this paper uses static response to grasp the dynamic response law to directionally optimize the experimental scheme. Dynamic transient response and dynamic steady-state response are analyzed one by one to discuss the role of dynamic response law in gas mixture recognition. High recognition rate is achieved in KNN recognition due to the selection of PCA dimensionality reduction results of the second dynamic transient response and dynamic steady-state response value. The study of the dynamic response law provides a new avenue for the recognition of gas mixture.
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