Wind Turbines are autonomous production plants of electric energy that provide information about their statur. These data are normally collected at the Control Center of the Wind Farm (SCADA, but also may come from Specialized autonomous dataloggers, like the Condition Monitoring systems.
The data transfered from the Wind Turbines to the SCADA are typically slow (in the range of one set each 2 minutes),and with low content (around 20 signals each), although this is per Wind Turbine. The main problem with these data is that they are ‘aggregated data‘ while what is required is to have ‘causility chains‘ (i.e, is there any evolution of signals that can be used to predict a gearbox failure? how advanced in time?)
Condition Monitoring systems are used to monitor (and, in some cases, to record and to process) signals related to rotative parts (inside the Gearbox pinnions and bearings, the rotor bearing, the generator bearings, etc.) These signals are typical several orders of magnitude faster that others in the Wind Turbine, and therefore pose high demands on processing capabilities and communications channels. They require also specialiazed applications for their treatment.
Specialized dataloggers (such us our DL1300) provide additional information that complement the data stored in the SCADA, but with higher rates, typically in the 1 sample per second range or lower. For example, for the evolution of gurrents, voltages, powers and frequency in the Grid, power consumption in the yaw motors, blades pitch angles, etc.)
In ACM SL we provide services and applications for the analysis of these data: these analyses have a complex statistic treatment, but requires a in depth knowledge of the internals of the Wind Turbines to be really meaningful.
We also offer a simple to use tool (‘Oscilloscope‘) to visualize and edit the raw data. The main benefit is ‘easy of use’ for long time series: with multiple simultaneous channels, automatic resizing of vertical scales, ‘very fast zooms‘ , etc.