Filter löschen
Filter löschen

Matlab with deep learning and machine learning for vibrations to predict response

15 Ansichten (letzte 30 Tage)
can we frame matlab code for a non linear vibratory system using deep leaning RNN where we train a system with n number of input force and responses that can later predict the response for any input of force? is it possible with matlab deep learning?

Antworten (2)

Shivansh
Shivansh am 6 Dez. 2023
Hi Thushar,
I understand that you want to know if we can implement a RNN based model for a non-linear vibratory system. I am assuming that you want to model a time-series based system for prediction of unseen data.
It is possible to model a RNN in Matlab for time series data which is typical in vibration analysis. Here is a sample code for your model.
% Assuming you have inputSequence as your input forces and targetSequence as your responses
numFeatures = size(inputSequence, 1); % Number of features in input
numResponses = size(targetSequence, 1); % Number of output responses
numHiddenUnits = 50; % Number of hidden units in the RNN layers
% Define the RNN architecture
layers = [ ...
sequenceInputLayer(numFeatures)
lstmLayer(numHiddenUnits,'OutputMode','sequence')
fullyConnectedLayer(numResponses)
regressionLayer];
% Specify training options
options = trainingOptions('adam', ...
'MaxEpochs',100, ...
'GradientThreshold',1, ...
'InitialLearnRate',0.005, ...
'LearnRateSchedule','piecewise', ...
'LearnRateDropPeriod',125, ...
'LearnRateDropFactor',0.2, ...
'Verbose',0, ...
'Plots','training-progress');
% Train the RNN
net = trainNetwork(inputSequence, targetSequence, layers, options);
% Predict using the trained RNN
predictedResponse = predict(net, newInputForce);
You can modify the above code with respect to your problem and fine tune it to get better results.
You can refer to the following documentation for more information about the Recurrent neural networks in Matlab: https://www.mathworks.com/discovery/rnn.html.
Hope it helps!

Shreeya
Shreeya am 12 Dez. 2023
To predict the final state of a nonlinear system, physics informed neural networks can be used. You can refer to the link below for the implementation in MATLAB:
To understand more about these networks and how they perform better compared to traditional neural networks, refer to the link below. The article talks about the prediction of angular position and velocity of a pendulum bob using PIML.

Kategorien

Mehr zu Sequence and Numeric Feature Data Workflows finden Sie in Help Center und File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by