Method for detecting an air discharge decomposed product based on a virtual sensor array

Patent metadata

Field	Value
Publication number	US-11525797-B2
Application number	US-201916261768-A
Country	US
Kind code	B2
Filing date	Jan 30, 2019
Priority date	Jan 30, 2019
Publication date	Dec 13, 2022
Grant date	Dec 13, 2022

Abstract

Embodiments of the present disclosure relate to a method for detecting an air discharge decomposed product based on a virtual sensor array, comprising: fabricating a virtual sensor array; disposing the virtual sensor array in a hermetically sealed gas chamber, energizing, and initializing; performing gas-sensitive testing to the virtual sensor array and storing a testing result as samples to store; and building a convolutional neural network model diagram for identifying contents of gas components, and identifying an atmosphere. The virtual sensor array fabricated by the present disclosure may reduce the array size and the overall volume of a device to an extreme content; the built convolutional neural network may dig other feature information besides a response value from a response curve of a sensor, thereby effectively improving identification efficiency and identification accuracy.

First claim

What is claimed is:

1. A method for detecting an air discharge decomposed product based on a virtual sensor array, comprising:
Step S 100 : fabricating a virtual sensor array;
Step S 200 : disposing the virtual sensor array in a hermetically sealed gas chamber, energizing, and initializing;
Step S 300 : performing gas-sensitive testing to the virtual sensor array and storing a testing result as samples to store; and
Step S 400 : building a convolutional neural network model diagram for identifying contents of gas components and identifying an atmosphere
wherein the step S 100 comprises:
Step S 101 : fabricating a sensor base: fabricating a devised electrode pattern on a sensor substrate, and leading out a corresponding electrode lead; wherein the electrode pattern is formed on a surface of the sensor substrate by an electronic beam evaporation process and a photolithographic process, and respective electrode pairs are crossed like a brush, but do not intersect;
Step S 102 : applying nanometer gas-sensitive materials: uniformly applying different nanometer gas-sensitive materials on the surface of the sensor base to form an entity array; further, sufficiently dispersing the nanometer gas-sensitive materials into ethanol, and coating a surface of a front-side testing electrode with the materials by spraying, spin-coating, or drop-coating to form a gas-sensitive film;
Step S 103 : forming a virtual sensor array: applying a pulse heating voltage to the entire sensor array to form the virtual sensor array.

2. The method according to claim 1 , wherein the virtual sensor array comprises: a sensor substrate, electrodes, and nanometer gas-sensitive materials, the sensor substrate and the electrodes forming a sensor base, the electrodes including a front-side testing electrode and a back-side heating electrode, the nanometer gas-sensitive material being applied on the front-side testing electrode.

3. The method according to claim 2 , wherein the front-side testing electrode is configured for testing a gas-sensitive resistance, and a fabricating material includes any one of gold-nickel, platinum, and silver-palladium.

4. The method according to claim 3 , wherein a thickness of the front-side testing electrode is 50˜300 nm.

5. The method according to claim 2 , wherein the back-side heating electrode is configured for applying different pulse heating voltages to perform thermal processing to the sensor array, and a fabricating material thereof includes any one of gold-nickel and platinum.

6. The method according to claim 5 , wherein a thickness of the back-side heating electrode is 50˜300 nm.

7. The method according to claim 2 , wherein the nanometer gas-sensitive material includes any one of tin oxide, titanium oxide, zinc oxide, indium oxide, cerium oxide, tungsten oxide, nickel oxide and cobalt oxide, and an application thickness is 100 nm˜1 μm.

8. The method according to claim 1 , wherein the pulse includes: a square wave, a sine wave, and a triangular wave.

9. The method according to claim 1 , wherein the step S 400 comprises:
Step S 401 : creating an input matrix and an output vector, where a two-dimensional measurement matrix formed by the number of virtual sensor arrays and a response time sequence is taken as the input matrix, and contents of the gas components are taken as the output vectors;
Step S 402 : building and training a fully data-driven convolutional network model;
Step S 403 : identifying components of a hybrid gas using the trained convolutional network model.

Assignees

• Univ Xi An Jiaotong

Inventors

• Rong Mingzhe
• Yang Aijun
• Wang Xiaohua
• Chu Jifeng

Classifications

• G01N27/122 Primary

  Circuits particularly adapted therefor, e.g. linearising circuits · CPC title

• G01N33/0031 Primary

  comprising two or more sensors, e.g. a sensor array · CPC title

• G01N27/128

  Microapparatus · CPC title