Vibration Analysis

This paper covers differences in accuracies of an artificial intelligence model that classifies different sets of sensor outputs (in this case, machinery shaft vibrations) collected by sensors into varying levels of weight on the shaft. The model uses a neural network to categorize the data, and there are varying accuracies depending on weights at the end of the shaft. This paper goes over the causes for these changes and patterns one can notice by going through the results.

Explore More!

Molecular Analysis of Stellar Clusters Final Paper

By testing a multitude of models from the python package scikit-learn upon the APOGEE dataset, we’ve managed to produce a resultant product that can predict a star’s iron concentration depending upon its gravitational pull (LOGG) value or effective temperature (TEFF) value.