A Demodulation Method and System for Fiber Bragg Grating Temperature Sensing Based on Inversion Algorithm
A fiber grating and inversion algorithm technology, which is applied in the field of fiber grating temperature sensing demodulation based on inversion algorithm, can solve the problem of limited temperature resistance of sensing elements, inability to perform sensing measurement, and inability to exceed sensing elements. The highest temperature resistance and other issues, to achieve the effect of improving the response speed and high temperature resistance
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0078] see Figure 1 to Figure 5 , the following takes the BP neural network optimized by genetic algorithm as an example to illustrate in detail, the input data combination method in the embodiment of the present invention adopts the wavelength value at a certain moment and the rate of change of the wavelength over time at the moment, and the rate of change of the wavelength over time is solved by gradient algorithm. The specific steps are as figure 1 shown, including:
[0079] Step 1, calibrate the response speed curve of the fiber grating temperature sensor and preprocess the original data, then divide the obtained sample data into a training set and a test set, and normalize the sample data;
[0080] Step 2. Establish a BP neural network regression model according to the sample data, respectively determine the number of nodes of the input layer, hidden layer and output layer of the BP neural network, and obtain the output of the BP neural network;
[0081] Step 3, using ...
Embodiment 2
[0097] see Figure 6 to Figure 8 , a fiber grating temperature sensing demodulation method based on an inversion algorithm according to an embodiment of the present invention specifically includes the following steps:
[0098] Step 1, calibrating the response speed curve of the fiber grating temperature sensor, and preprocessing the data to obtain sample data;
[0099] Step 2, calibrating the temperature-wavelength curve of the fiber grating temperature sensor;
[0100] Step 3. Use the sample data and the basic formula of the formula method to establish a fiber grating temperature inversion model, that is, to obtain K;
[0101] Step 4. Test the above-mentioned fiber grating temperature inversion model, and use the root mean square error as the evaluation standard. If the test passes, it means that the established model is valid; if the test fails, repeat the above step 3;
[0102] Step 5. Use the above model to predict the temperature.
[0103] In step 1 of this embodiment,...
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More 


