Case Study: Using Condition Monitoring to Drive Risk Mitigation and Maintenance Optimization for Wind

Chris Kramm, Senior Sales Operations Leader, Wind and Hydro, Bently Nevada | Baker Hughes GE


This presentation will share and discuss achieving higher reliability and availability of your wind farm assets through the use of tools and techniques to identify, diagnose and monitor drive train health using vibration monitoring.  The case study will highlight the benefit of having an active condition monitoring strategy for diagnosing wind turbine faults, as well as discuss the prioritization of wind turbine faults .  This discussion will show how condition monitoring on individual wind turbines, and using that data as a critical input to farm and fleet level analytics, can drive risk mitigation and maintenance optimization.


For over a decade Chris Kramm has worked around the globe in the industry of vibration sensing and condition monitoring at Wilcoxon Sensing Technologies, GE Renewable Energy, and Bently Nevada.  Now at Bently, Chris drives the the Bently Nevada product line by providing strategic product and sales leadership for hardware, software, and services offerings in the Wind and Hydro power generation markets.

At Wilcoxon, Chris managed new technology and product development activities for condition monitoring products offered across a broad range of industries, including Wind. He later served as Product Manager of Wilcoxon’s Industrial product line, where he was instrumental in defining and developing a new generation of digital condition monitoring sensors and transmitters. At GE Renewable Energy’s Onshore Wind business Chris served as the Condition Monitoring Systems Product Manager and was responsible for setting the strategic direction and development of vibration monitoring hardware, software, and analytics, working closely with GE’s Remote Monitoring & Diagnostics team to improve automation and efficiencies. This integration allowed the number of wind turbines under monitoring to grow, increasing from 6,500 to 12,000.  Chris was also instrumental in the development of GE’s Wind turbine gearbox analytics, which represented a significant leap forward in automated detectability of wind turbine bearing and gearing faults.