[temperature detection] thermal infrared image temperature detection system based on Matlab GUI [including Matlab source code 1920]

One 、 Introduction to thermal infrared image temperature detection

The aircraft body alloy can maintain the aircraft shape to bear aerodynamic force , At present, the main body of aircraft is made of aluminum alloy , It has high corrosion resistance 、 High hardenability and toughness . When the plane is flying , Due to combustion in engine combustion chamber, etc , As a result, the surface temperature of the aircraft body alloy rises rapidly , Increase the probability of failure . therefore , It is particularly important to detect the surface temperature of the aircraft body alloy , When high temperature is detected , It can be seen whether the aircraft main body alloy is faulty , So that it can be repaired quickly .

Jiangfan et al. Used the standard temperature method , Study the technology of self - Determination of arc high temperature zone . Rongyan chaozai Matlab On the basis of , When studying the solidification of short-circuit weld marks , Method of measuring and calculating melt temperature , But when detecting samples with excessive temperature , There are still detection errors .

Infrared thermal imaging technology has a large detection area 、 Fast detection speed and other advantages , It is mainly used for target detection 、 Optical remote sensing and other technical fields . In the existing infrared image research and application range , Usually you only need to study the objects in the image , Therefore, it is necessary to highlight the target and detail information in image processing , And reduce image noise . In this paper, the author studies the temperature detection method of aircraft main body alloy based on infrared image , The improved median filtering algorithm is adopted , Denoise the acquired image ; And the seed region growing method of color image , Extract the high temperature region in the infrared image , High precision detection of aircraft main body alloy at different temperatures .

1 Test materials and methods
1.1 Materials and preparation
With 38 box BT20 Titanium alloy as test sample , Size is 150mm×80 mm×3 mm. Placed directly in front of the infrared radiator 180mm It's about .
Irradiate the sample with a cold light source , Directly in front of the sample 1.0 m The image acquisition system at collects the surface image of the sample [9].

1.2 Method
Raise the sample surface temperature to 50℃, Collect its infrared image for comparison ; The sample temperature is changed from to by using the transient aerodynamic thermal test simulation system 50℃ Rose to 1 000℃, The heating rate is 10℃/min, Every rise 50℃, Heat preservation 1 min, until 1 000℃, Heat preservation 8 s. During this period, the surface temperature of each temperature sample shall be tested , And collect infrared images .

1.2.1 Infrared image preprocessing
An improved median filter algorithm is used to preprocess and denoise the infrared image of aircraft main body alloy .
Extract the gray value of all pixels in the infrared image , And sort by size , Extract the sorting intermediate value as the gray value of the pixel ：

The noise in the gray value of infrared image is normally distributed , The median filtering algorithm is used for processing , Output noise variance approximation ：

1.2.2 Color image seed region growing method
With RGB Based on color space , The seed zone growth method is adopted , Extract the data information and feature areas in the infrared image .

When the background temperature changes , Infrared image RGB The value varies according to the generation temperature , The characteristic area with large difference from the ambient temperature will be obvious . As the temperature increases , Red 、 The proportion of green increased , The larger change gradient is the proportion of green , The smaller change gradient is the proportion of red , What is non monotonic is the proportion of blue . The function of seed region growing method is to segment the proportion of green and red in infrared image .

The higher the brightness in the infrared image , It indicates that the higher the surface temperature of the target object [15]. Set the seed point as the pixel with the highest brightness in the infrared image . Traverse the part to be segmented in the image , Determine matrix size , Calculate the pixel mean in this matrix , And take the middle point of the maximum mean area as the seed point .

The thermal fault may have different degrees of heating , This causes its features to appear on multiple part images . To extract the seed points of multiple heating regions , Find the pixel with the highest brightness , Take this as the seed point , Find a point with a small difference from its pixel value , And set a certain pixel value difference threshold , Select the seed region .

After the seed region is automatically selected , Look for the best conditions for seed growth , Complete high temperature test , Provide basis for subsequent fault identification . Last , Green light 、 The intersection of red light seed regions constitutes the fused image , That is to achieve infrared image high temperature region extraction .

Two 、 Partial source code

function varargout = MainTempMonitor(varargin)
% MAINTEMPMONITOR MATLAB code for MainTempMonitor.fig
%      MAINTEMPMONITOR, by itself, creates a new MAINTEMPMONITOR or raises the existing
%      singleton*.
%
%      H = MAINTEMPMONITOR returns the handle to a new MAINTEMPMONITOR or the handle to
%      the existing singleton*.
%
%      MAINTEMPMONITOR('CALLBACK',hObject,eventData,handles,...) calls the local
%      function named CALLBACK in MAINTEMPMONITOR.M with the given input arguments.
%
%      MAINTEMPMONITOR('Property','Value',...) creates a new MAINTEMPMONITOR or raises the
%      existing singleton*.  Starting from the left, property value pairs are
%      applied to the GUI before MainTempMonitor_OpeningFcn gets called.  An
%      unrecognized property name or invalid value makes property application
%      stop.  All inputs are passed to MainTempMonitor_OpeningFcn via varargin.
%
%      *See GUI Options on GUIDE's Tools menu.  Choose "GUI allows only one
%      instance to run (singleton)".
%
% See also: GUIDE, GUIDATA, GUIHANDLES

% Edit the above text to modify the response to help MainTempMonitor

% Last Modified by GUIDE v2.5 26-Jun-2022 12:20:26

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
                   'gui_Singleton',  gui_Singleton, ...
                   'gui_OpeningFcn', @MainTempMonitor_OpeningFcn, ...
                   'gui_OutputFcn',  @MainTempMonitor_OutputFcn, ...
                   'gui_LayoutFcn',  [] , ...
                   'gui_Callback',   []);
if nargin && ischar(varargin{
    1})
    gui_State.gui_Callback = str2func(varargin{
    1});
end

if nargout
    [varargout{
    1:nargout}] = gui_mainfcn(gui_State, varargin{
    :});
else
    gui_mainfcn(gui_State, varargin{
    :});
end
% End initialization code - DO NOT EDIT


% --- Executes just before MainTempMonitor is made visible.
function MainTempMonitor_OpeningFcn(hObject, eventdata, handles, varargin)
% This function has no output args, see OutputFcn.
% hObject    handle to figure
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
% varargin   command line arguments to MainTempMonitor (see VARARGIN)

% Choose default command line output for MainTempMonitor
handles.output = hObject;

% Update handles structure
guidata(hObject, handles);

% UIWAIT makes MainTempMonitor wait for user response (see UIRESUME)
% uiwait(handles.figure1);


% --- Outputs from this function are returned to the command line.
function varargout = MainTempMonitor_OutputFcn(hObject, eventdata, handles) 
% varargout  cell array for returning output args (see VARARGOUT);
% hObject    handle to figure
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Get default command line output from handles structure
varargout{
    1} = handles.output;


% --- Executes on button press in ReadFig.
function ReadFig_Callback(hObject, eventdata, handles)
%  Image Reading 
% hObject    handle to ReadFig (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
% global FileName 
global I
[FileName,PathName] = uigetfile('.jpg');    %  open windows 
TotalPath = [PathName, '\', FileName];  %  The full path 
IRGB = imread(TotalPath);   %  Image Reading 
% I = rgb2gray(IRGB);
r = IRGB(:,:,1);
g = IRGB(:,:,2);
b = IRGB(:,:,3);
I = .299*r + .587*g + .114*b;   %  Go to grayscale 
set(handles.text5,'String',strcat(TotalPath,' loaded.'))    %  According to load 

axis(handles.FigOri);
imshow(I)
title(' Color image graying ')    %  Draw grayscale 



% --- Executes on button press in AddNoise.
function AddNoise_Callback(hObject, eventdata, handles)
%  Add noise button 
% hObject    handle to AddNoise (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
global I NoiseType J
if isempty(NoiseType)   %  Determine whether to select the noise type 
    msgbox(' No noise type selected ')
    error(' No noise type selected ')
end
t = get(handles.NoisePara, 'String');   
if iscell(t)
    tt = t{
    1};    
elseif isa(t, 'string') || isa(t, 'char')
    tt = t;
end

3、 ... and 、 Running results

Four 、matlab Edition and references

1 matlab edition
2014a

2 reference
[1] Cai Limei .MATLAB The image processing —— theory 、 Algorithm and example analysis [M]. tsinghua university press ,2020.
[2] Yang Dan , Zhao Haibin , Long Zhe .MATLAB Detailed explanation of image processing examples [M]. tsinghua university press ,2013.
[3] Zhou pin .MATLAB Image processing and graphical user interface design [M]. tsinghua university press ,2013.
[4] Liu Chenglong . Master MATLAB The image processing [M]. tsinghua university press ,2015.
[5] gemee . Temperature detection of aircraft main body alloy based on infrared image [J]. Weapon material science and engineering . 2022,45(01)

3 remarks
This part of the introduction is taken from the Internet , For reference only , If infringement , Contact deletion