CN-122016075-A - Temperature sensing method based on micro-nano robot

CN122016075ACN 122016075 ACN122016075 ACN 122016075ACN-122016075-A

Abstract

The invention relates to the technical field of micro-nano sensing and detection, in particular to a temperature sensing method based on a micro-nano robot. A temperature detection method based on a micro-nano robot comprises the following steps of preparing a temperature sensitive material by using tetrammine copper sulfate particles and resin, preparing the micro-nano robot with a temperature detection function by adopting a droplet micro-fluidic technology and a physical vapor deposition technology based on the temperature sensitive material in the step one, extracting color characteristics by using the micro-nano robot with the temperature detection function obtained in the step two, constructing a temperature detection regression prediction model based on the color characteristics, and carrying out temperature detection on a micro-void by using the micro-nano robot with the temperature detection function on the basis of the temperature regression prediction model obtained in the step three, wherein the average value of detection results of a plurality of micro-nano robots is taken as the final detection temperature. Solves the problem that the prior temperature detection method in the industrial field is limited in mode.

Inventors

CHANG XIAOCONG
DING SHAOBO
Dong Jiaxu
LI LONGQIU
ZHOU DEKAI

Assignees

哈尔滨工业大学

Dates

Publication Date: 20260512
Application Date: 20260205

Claims (10)

1. The temperature detection method based on the micro-nano robot is characterized by comprising the following steps of: Preparing a temperature-sensitive material by using tetramine copper sulfate particles and resin; Preparing a micro-nano robot with a temperature detection function by adopting a liquid drop micro-fluidic technology and a physical vapor deposition technology based on the temperature sensitive material in the first step; step three, extracting color characteristics by using the micro-nano robot with the temperature detection function obtained in the step two, and building a temperature detection regression prediction model based on the color characteristics; and step four, on the basis of the temperature regression prediction model obtained in the step three, detecting the temperature of the micro-gap by using the micro-nano robots with the temperature detection function, and taking the average value of detection results of a plurality of the micro-nano robots as the final detection temperature.
2. The micro-nano robot-based temperature detection method according to claim 1, wherein, Grinding the copper sulfate pentahydrate crystal in a ball mill for 18 hours to obtain copper sulfate powder with the particle diameter smaller than 1 mu m; Dissolving the copper sulfate powder in 10mL of deionized water, slowly adding 10mL of ammonia water solution to form blue precipitate, and continuously stirring until the reaction is complete; Adding 25mL of absolute ethyl alcohol to promote precipitation, washing the precipitate alternately by using ammonia water solution and absolute ethyl alcohol, putting the precipitate into a 50 ℃ drying box for drying for 30 minutes to obtain high-purity copper tetrammine sulfate solid, and grinding to obtain copper tetrammine sulfate particles.
3. The micro-nano robot-based temperature detection method according to claim 1, wherein in the first step, the resin is a high temperature-resistant transparent photo-curable resin, and the high temperature resistance is 250 ℃; the mass ratio of the tetrammine copper sulfate particles to the resin is 1:4.
4. The temperature detection method based on the micro-nano robot, which is characterized in that in the first step, the temperature sensitive material is prepared by adding tetrammine copper sulfate particles into resin, performing ultrasonic treatment on the mixture, and then putting the mixture into a ball mill for mixing and ball milling for 3 hours.
5. The micro-nano robot-based temperature detection method according to claim 1, wherein in the second step, in the droplet microfluidic technology, the continuous phase solution is HFE-7500 fluorinated oil solution containing a fluorine surfactant, and the dispersed phase solution is the temperature sensitive material prepared in the first step; The flow ratio of the continuous phase solution to the disperse phase solution is controlled to be 2-20; After the liquid drops are generated by the liquid drop microfluidic technology, the microspheres are formed by ultraviolet irradiation and solidification.
6. The micro-nano robot-based temperature detection method according to claim 1, wherein in the second step, the physical vapor deposition technology is used for depositing a magnetic metal material, and the thickness of the deposited magnetic metal layer ranges from 200 nm to 600nm.
7. The micro-nano robot-based temperature detection method according to claim 1, wherein in the third step, the color characteristics are obtained by sequentially adopting edge detection, contour extraction, HSV color space conversion and threshold extraction, so as to obtain a red (R) channel color level average value, a green (G) channel color level average value, a blue (B) channel color level average value and a gray (Y) image color level average value.
8. The micro-nano robot-based temperature detection method according to claim 1 or 7, wherein in the third step, the temperature detection regression prediction model is a regression prediction model built based on a multi-layer perceptron, and inputs of the model are red (R) channel color-level average value, green (G) channel color-level average value, blue (B) channel color-level average value and gray (Y) image color-level average value, and outputs the model as a temperature T value.
9. The temperature detection method based on the micro-nano robot according to claim 1, wherein in the third step, when the temperature detection regression prediction model is built, the micro-nano robot is placed on a controllable heating platform for heating, the heating temperature ranges from 160 ℃ to 240 ℃, and the heating step length is 10 ℃.
10. The micro-nano robot-based temperature detection method according to claim 1, wherein in the fourth step, the number of samples of the micro-nano robot participating in the data calculation is not less than 5.

Description

Temperature sensing method based on micro-nano robot Technical Field The invention relates to the technical field of micro-nano sensing and detection, in particular to a temperature sensing method based on a micro-nano robot. Background Temperature is an important parameter that characterizes the state of a complex microenvironment. In the limited space such as micro-pore, micro-crack, narrow runner, etc., the traditional temperature sensor such as thermocouple, optical fiber probe, etc. often has the problems of difficult entering of size, difficult layout, disturbance environment, limited measuring points, etc. The micro-nano robot is a movable micro-nano actuator, and the micro-nano robot is utilized to detect the temperature, so that a thought is provided for detecting the complex micro-environment. The existing fields of temperature detection by micro-nano robots are roughly two types, namely, biomedical fields and industrial fields. There are many solutions for sensing temperature in the biomedical field by using micro-nano robots, but application methods in the industrial field are reported, but there are some demands for improvement in detection modes and accuracy. It is very significant to provide a micro-nano robot-based temperature detection method for micro-environment temperature detection in view of the above. Disclosure of Invention In order to solve the technical problems, the invention aims to provide a temperature detection method based on a micro-nano robot, so as to solve the problem that the mode of the temperature detection method in the prior industrial field is limited. The technical scheme adopted for solving the technical problems is as follows: a temperature detection method based on a micro-nano robot comprises the following steps: Preparing a temperature-sensitive material by using tetramine copper sulfate particles and resin; Preparing a micro-nano robot with a temperature detection function by adopting a liquid drop micro-fluidic technology and a physical vapor deposition technology based on the temperature sensitive material in the first step; step three, extracting color characteristics by using the micro-nano robot with the temperature detection function obtained in the step two, and building a temperature detection regression prediction model based on the color characteristics; and step four, on the basis of the temperature regression prediction model obtained in the step three, detecting the temperature of the micro-gap by using the micro-nano robots with the temperature detection function, and taking the average value of detection results of a plurality of the micro-nano robots as the final detection temperature. In the first step, the preparation process of the copper tetramine sulfate particles comprises the steps of grinding copper sulfate pentahydrate crystals in a ball mill for 18 hours to obtain copper sulfate powder with the particle size smaller than 1 mu m; Dissolving the copper sulfate powder in 10mL of deionized water, slowly adding 10mL of ammonia water solution to form blue precipitate, and continuously stirring until the reaction is complete; Adding 25mL of absolute ethyl alcohol to promote precipitation, washing the precipitate alternately by using ammonia water solution and absolute ethyl alcohol, putting the precipitate into a 50 ℃ drying box for drying for 30 minutes to obtain high-purity copper tetrammine sulfate solid, and grinding to obtain copper tetrammine sulfate particles. In the first step, the resin is high-temperature-resistant transparent photocuring resin, and the high-temperature resistance temperature is 250 ℃; the mass ratio of the tetrammine copper sulfate particles to the resin is 1:4. In the first step, the temperature sensitive material is prepared by adding tetramine copper sulfate particles into resin, performing ultrasonic treatment on the mixture, and then putting the mixture into a ball mill for mixing and ball milling for 3 hours to obtain the temperature sensitive material. In the second step, in the droplet microfluidic technology, the continuous phase solution is HFE-7500 fluorinated oil solution containing a fluorine surfactant, and the disperse phase solution is the temperature sensitive material prepared in the first step; The flow ratio of the continuous phase solution to the disperse phase solution is controlled to be 2-20; After the liquid drops are generated by the liquid drop microfluidic technology, the microspheres are formed by ultraviolet irradiation and solidification. In the second step, the physical vapor deposition technology is used for depositing magnetic metal materials, and the thickness of the deposited magnetic metal layers ranges from 200 nm to 600nm. In the third step, the color characteristics are obtained by sequentially adopting the methods of edge detection, contour extraction, HSV color space conversion and threshold extraction to obtain a red (R) channel color level average value, a green (G) cha