The Data Journey:An Intelligent Path to Machine Learning

In 2008 we were looking for methods to enhance our capability of monitoring the vibration of Generating Turbines through dynamic speed ranges. To solve this problem, we created an anomaly detection algorithm that was generic, scalable, and easy to use for non-data scientists and could take in many more inputs than just vibration. So, we plugged it into the company PI system and SpheriCAL was born. Over the years we have applied SpheriCAL all sorts of assets, across all the main generation technologies: CCGT, OCGT, Coal, Hydro, Wind, and even Solar. We have increased our capabilities adding more machine learning and developing our SMART systems, culminating in the Virtual Analyst.