NRG says the system differs from Scada systems, which use sensors to detect component faults but often require trained maintenance staff to understand the data. TurbinePhD instead uses digital signal-processing techniques to detect component wear before a fault develops. Sensors with embedded processors use algorithms to diagnose problems and then transmit data to a secure website.
"Our system borrows technology from the aerospace industry to diagnose early-stage wear - months in advance of a fault - and then to accurately estimate the remaining useful life of each component," said Eric Bechhoefer, chief engineer at NRG Systems. "We also eliminate the need for a diagnostic engineer by integrating data into a single, readily understandable health indicator for each component. The data can be read and acted upon by anyone."
NRG says the system integrates multiple condition indicators into this single health indicator, eliminating the need for the engineering interpretation required by traditional systems. These indicators are accessible online, along with all of the data supporting the diagnosis. The product, which is currently in beta testing, is set to be launched in the summer.
The news came as NRG chief executive Jan Blittersdorf was recognised by the US White House as one of 10 Champions of Change for renewable energy.