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Electronic nose sampling data pre-calibration method based on response curve differential characteristic

A technology of sampling data and electronic nose, which is applied in the direction of analyzing materials, material inspection products, and analyzing gas mixtures, etc., which can solve the problems of inability to verify sampling data, achieve the effects of accurate classifiers, wide application ranges, and improved reliability

Active Publication Date: 2017-01-04
TIANJIN UNIV
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  • Abstract
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Problems solved by technology

[0008] (1) The current electronic nose data preprocessing method only performs some filtering, smoothing and transformation processing on the sampled data, and cannot verify the sampled data as a whole
[0009] (2) At present, there is no effective method for real-time verification of the overall accuracy of electronic nose sampling data

Method used

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  • Electronic nose sampling data pre-calibration method based on response curve differential characteristic
  • Electronic nose sampling data pre-calibration method based on response curve differential characteristic
  • Electronic nose sampling data pre-calibration method based on response curve differential characteristic

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Embodiment Construction

[0029] The present invention will be described below in conjunction with the accompanying drawings and embodiments.

[0030] The electronic nose structure that the present invention relates to is as figure 1 As shown, the electronic nose can not only directly detect gas samples, but also be used to detect liquid samples such as liquor. The electronic nose mainly includes three parts: evaporation and sampling device, sensor air chamber reaction device, and control and data acquisition preprocessing system.

[0031] The electronic nose device of the present invention includes an adjustable-speed air pump, a solenoid valve, an evaporation air chamber, a sensor air chamber, an AD acquisition chip and a main controller. The sampling method involved in the present invention takes the detection of liquor samples as an example, and the main workflow of the electronic nose is as follows: figure 1 As shown, firstly, the liquor sample in the evaporating gas chamber is fully evaporated ...

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Abstract

The invention relates to an electronic nose sampling data pre-calibration method based on a response curve differential characteristic. The method is suitable for adopting an electronic nose bionic sampling mode with a complete cycle in three cycles. The method comprises the steps that array sampling data acquired in an electronic nose bionic sampling manner are preprocessed in turn, and St is set as normalized relative conductivity change rate; St is differentiated through a sampling gradient method; the maximum of three ascending differential curves and the maximum of three descending differential curves of each sensor curve are extracted; the absolute value of three mean differentials of each sensor differential curve in a time period above a coordinate axis and the absolute value of three mean differentials in a time period above the coordinate axis are respectively calculated; the acquired maximum of the differential curve of each sensor is compared and judged; the acquired average differential of each sensor is compared and judged; and when the differential extremum and the mean differential meet the differential characteristic of bionic breath sampling, the sampling data of a sensor is accurately pre-calibrated.

Description

technical field [0001] The invention belongs to the field of instruments and measurements, and in particular relates to a method for pre-checking sampling data of an electronic nose based on the differential characteristics of response curves. Background technique [0002] Electronic nose, also known as artificial olfactory system, is a modern bionic detection instrument, which can simulate the structure and function of the human and mammalian olfactory system, and realize the detection and recognition of simple or complex odors. Electronic nose usually includes three parts: gas sensor array, information preprocessing and pattern recognition. When an electronic nose detects a sample, the volatile odor needs to react with an array composed of multiple gas sensors to convert the chemical signal of the sample into an electrical signal, and then undergo a series of preprocessing processes such as signal conditioning and normalization to obtain the sample The corresponding compr...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G01N33/14G01N33/00
CPCG01N33/0004G01N33/146G06F2218/02G06F18/24
Inventor 孟庆浩亓培锋曾明
Owner TIANJIN UNIV
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