Matlab turbofan project

Project 1: Remaining Useful Life Prediction - When does the next fault occur? Prognostics Center of Excellence - Data Repository ([login to view URL]) [login to view URL] Data Set 6: Turbofan Engine Degradation Simulation Dataset, provided by NASA, is becoming an important benchmark in the Remaining Useful Life (RUL) estimation for a fleet of engines of the same type (100 in total). Data are available in the form of time series: 3 operational settings, 21 sensor measurements and cycle — i.e. observations in terms of time for working life. Engines have different life durations. The average working time in train data is 206 cycles with a minimum of 128 and a maximum of 362. The goal is to develop a predictive model, which can predict the remaining life cycles based on the current operational setting and sensor measurements. Here is a possible approach developed by Marco Cerliani. Remaining Life Estimation with Keras [login to view URL] ... I did ANN to fine RUL but doctor said wrong , it should be like this [login to view URL] , which is CNN .. YOU CAN FIND DOCTOR COMMENTS IN ATTACHED AND REPORT AND MATLAB >