At Wolf Hills Energy in Virginia, a 250 MW natural gas power plant owned by Middle River Power, plant operators were seeking a solution that would enable them to optimize their staff resources and operational efficiency. Working with Siemens Energy, they implemented a computer vision system that uses a network of cameras to monitor critical systems such as emissions control, fire protection, and turbine lube oil.
AI algorithms analyze data obtained from the cameras to automatically detect anomalies, leaks, and unsafe conditions. Unlike manual inspections, the computer vision solution provides consistent, real-time data streams to reduce operator variability and improve reliability.
“Any time a customer can identify an oncoming failure, the cost of preventative action is one-fifth the cost of taking action after a failure,” Voelker says. “The main driver for anomaly detection is to identify issues before they occur.”