This week didn’t bring many changes to our project. Our first demo presentations went well, and we started collecting data for the database. We ran sweeps on our variables, including different levels of flow restriction and simulated VRM power output, to observe how our testbed reacts and cools down. We based these changes of flow restriction and VRM power output on previous research. The values are then being stored to build a large dataset, which will be used to train and test our machine learning algorithms.
The project is still on track. Next week, we intend to implement the alert system and begin developing the regression and autoencoder models for anomaly detection.