Turbine Bearing Failure Anomaly Detection Use Case

An HRI member built a neural network, deep learning model to retroactively look for anomalies in the turbine guide bearing leading up to a known issue. The objective of the use case was to identify the variables which effect the turbine guide bearing and to try and create a model that could be used in the future to predict possible bearing issues. The results of their analysis have been published and are available to all HRI members.