## 4 Analyses
### Results
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Signal Name** & **IQR** & **Unit** \\ \hline Active power generation & 1052.1 & kW \\ Ambient temperature & 6.8 & \({}^{\circ}\)C \\ Current phase A & 843.0 & A \\ Current phase B & 842.0 & A \\ Current phase C & 838.2 & A \\ Generator speed & 804.5 & rpm \\ Grid frequency & 0.098 & Hz \\ Pitch angle blade 1 & 1.6 & deg \\ Pitch angle blade 2 & 1.6 & deg \\ Pitch angle blade 3 & 1.5 & deg \\ Power factor & 1.998 & - \\ Rotor speed & 7.8 & rpm \\ Temperature inside nacelle & 12.0 & \({}^{\circ}\)C \\ Temperature of gearbox oil & 4.9 & \({}^{\circ}\)C \\ Temperature of gearbox shaft bearing 1 & 6.0 & \({}^{\circ}\)C \\ Temperature of gearbox shaft bearing 2 & 8.2 & \({}^{\circ}\)C \\ Temperature of generator bearing 1 & 11.6 & \({}^{\circ}\)C \\ Temperature of generator bearing 2 & 5.1 & \({}^{\circ}\)C \\ Temperature of generator stator & 6.0 & \({}^{\circ}\)C \\ Temperature of main bearing & 5.5 & \({}^{\circ}\)C \\ Top box temperature & 10.9 & \({}^{\circ}\)C \\ Voltage phase A & 5.5 & V \\ Voltage phase B & 6.4 & V \\ Voltage phase C & 6.1 & V \\ Wind direction & 151.5 & deg \\ Wind speed & 4.4 & m/s \\ Yaw angle & 153.4 & deg \\ \hline \hline \end{tabular}
\end{table} 
Table 4: List of the available signals and corresponding interquartile range values used to normalize results for comparability. The IQR is defined as the difference between the third and first quartile of a distribution. * Current and active power signals are strongly affected for resolutions above 5 s. Changing the aggregation from 5 s to 30 s causes a loss of \(>\)20% of the total data in the lowest error bin of \([0,0.025]\times\) IQR. While the amount of data in this lowest error bin kept decreasing with a further reduction of the resolution, it was not as drastic as from 5 s to 30 s.
* The typical SCADA data resolution, i.e., 600 s, was not sufficient to correctly represent wind measurements, electrical signals, and the temperatures of gearbox and generator components as more than 20%, even \(>\)50% for the wind speed, of the data have losses greater than 0.1 IQR. On the other hand ambient temperature, main bearing, top box temperature, and yaw angle were barely affected retaining more than 80% of the data in error bins lower than 0.1 IQR
* Pitch angle values were occasionally affected by large differences between the aggregated and original signal. Approximately 10% of the data manifested losses superior to 1 IQR, even at short aggregation periods such as 30 s.
* The transition from 150 to 300 s caused a visible drop from approximately 90 to 70% of the size of the lowest error bin of the generator bearing temperature. Behavior of Temperature Signals  
Temperature signals constitute a special interest subgroup, as they are typically used as inputs for predictive maintenance to monitor the status of turbine components. Therefore, we conduct a separate investigation specifically for temperatures. Here, a normalization of results was not necessary as all temperatures already shared the same physical unit, i.e., degrees Celsius. The results for selected aggregation times are presented in Figure 6. Except for the error bins now in \({}^{\circ}\)C, it is the same representation as in the previous part. All data are provided in the Supplementary Materials. The following observations are emphasized:  
* Up to an aggregation period of 150 s information losses above 1 \({}^{\circ}\)C were almost nonexistent. More than 97% of the data were contained in the [0, 1 \({}^{\circ}\)C] error bin. Only gearbox shaft bearings and internal temperatures had a negligible amount of data in the second error bin.