This paper describes work by Bachmann Monitoring GmbH, along with customers and suppliers, to develop an holistic health monitoring system. Bachmann condition monitoring systems (CMS) are installed in almost 10,000 WEA worldwide; however, there is more to turbine health than vibration.

Whilst vibration is a proven indicator of drivetrain condition, there are many other measures that could be added to provide a more holistic view of the machine. Our developments target early detection of conditions which may reduce turbine life, such as: rotor unbalance; blade loading; tower fatigue. 

Each problem has been approached as a “plug in” to the standard CMS, to minimise the overall cost. However, if considered individually, the statistical variation of the individual measurements would lead to an unmanageable number of alarms. So, we have also used data analytics methods to optimise the generation of alarms.

Our Rotor Unbalance Calculator module uses horizontal vibration of the nacelle and a simple tower model to distinguish the mechanical unbalance force from the aerodynamic unbalance of the shaft and compensate for variation in response due to the proximity of rotor speed to tower natural frequency.

Our blade measurement system is based on blade bending detected using inductive sensors. Our tower Structural Health Monitoring module uses rain flow counting of the tower motion in order to generate a life-usage estimation for the structure.

Our data analytics uses entropy-based methods to extract systematic changes from random events. Our aim is to generate useful knowledge that organisations can use to optimise their maintenance scheduling.

First Published: 01.07.2020