APC-Propellers-DL-Model

A deep learning model for the regression problem of predicting the APC propellers thrust at various airspeed when given the propeller size and a certain rpm.

Data Source

Data is downloaded from the official APC propellers
Link: https://www.apcprop.com/technical-information/file-downloads/

Usage and Files

Files Info:

• 'Data_Extraction.py': python script for extracting a cleaner data from the original data and store it in the 'all_props.csv' file.
• 'Data Cleaning.ipynb': ipython notebook for additional cleaning of the 'all_props.csv' file by removing unwanted columns and saving to the 'all_props_cleaned_petite.csv' file.
• 'Fitting.ipynb': ipython notebook that contains the creation and training of the first deep learning model and saving the model into the 'Fitting_model.h5' file.
• 'Fitting_2.ipynb': ipython notebook that contains the creation and training of the second deep learning model and saving the model into the 'Fitting_2_model.h5' file.
• 'Fitting_3.ipynb': ipython notebook that contains the creation and training of the third deep learning model and saving the model into the 'Fitting_3_model.h5' file.
• 'Model UI.ipynb': ipython notebook. the user-interface of the models

Usage:

The main interface with the two created models should be done through the "Model UI" notebook.

Example Output

By changing the following values inside the "Model UI" notebook, the output will be as shown in the figure below.

diam = 16
pitch = 10
rpm = 13999
V_values = list(np.linspace(0,200,num=800))