Machine Learning based Condition Monitoring for Energy, Utilities, and Manufacturing
Over the past 10 years, Brüel & Kjær Vibro has monitored over more than 10,000 wind turbines. We have accumulated massive amounts of data and gained valuable experience from monitoring those machines. We realized that we can enhance services to our customer by utilizing the experience and data that we have gained over these past years. An obvious way forward is to use machine learning so that we can automatize many of our processes, make them more efficient and to open up new business possibilities. In this webinar, we talk about our experience in implementing machine learning for condition monitoring of wind turbines and other possible machinery in energy, utilities as well as manufacturing. We will discuss the reasons behind doing machine learning, how we prepared for it, its implementation, and we'll take a look ahead at this technology.
Kun Marhadi, PhD, Brüel & Kjær Vibro
Amit Dangle, Saviant Consulting