# Machine Learning-Based Tools for Wind Turbine Acoustic Monitoring
## 3 Results and Discussion  
The measurements were carried out during May 2018. In the monitoring period, average wind speeds ranging between 9.0 m/s and 23.0 m/s were detected. During the measurements, the turbines were switched on and off according to the sequence shown in Table 1. During the measurements, the following operating conditions were monitored: all turbines off, all turbines on, one turbine off, and two turbines off. The monitoring period covered approximately 18 h of overall measurements. Figure 3 shows the time history of the sound pressure level for the operating conditions performed in the measurement session. The different operating conditions have been highlighted in the following paragraphs to better appreciate the differences in the measured levels from a visual point of view. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Operating** & \begin{tabular}{c} **Start of** \\ **Monitoring** \\ **(Hours)** \\ \end{tabular} & \begin{tabular}{c} **Monitoring Periods** \\ **(Hours:Minutes:Seconds)** \\ \end{tabular} & \
\begin{tabular}{c} **LegA** \\ **(dBA)** \\ \end{tabular} &
\begin{tabular}{c} **Average Wind** \\ **Speed (m/s)** \\ \end{tabular} \\ \hline
1 & 22:00:00 & 02:00:00 & 38,4 & 9.0 \\
2 & 00:00:00 & 00:20:00 & 36,8 & 9.1 \\
3 & 00:20:00 & 00:20:00 & 31.2 & 9.2 \\
0 & 00:40:00 & 00:20:00 & 24.9 & 9.0 \\
1 & 23:00:00 & 01:00:00 & 40.2 & 13.0 \\
2 & 00:00:00 & 00:20:00 & 38.4 & 14.0 \\
3 & 00:20:00 & 00:20:00 & 38.5 & 15.0 \\
0 & 00:40:00 & 00:20:00 & 40.7 & 17.0 \\
1 & 01:00:00 & 02:40:00 & 50.3 & 14.0 \\
0 & 02:40:00 & 01:50:00 & 50.8 & 23.0 \\
1 & 20:30:00 & 02:30:00 & 43.7 & 12.0 \\
2 & 00:00:00 & 00:30:00 & 42.0 & 10.8 \\
0 & 00:30:00 & 00:30:00 & 36.7 & 10.5 \\
1 & 01:12:00 & 04:01:00 & 45.8 & 10.7 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of the acoustic measurements carried out in time intervals representative of different operating conditions. The measurements refer to several days of monitoring (Figure 3). 0 = all turbines off, 1 = all turbines on, 2 = one turbine off, 3 = two turbines off. Figure 3: Time history of the sound pressure level measured in situ, in different operating conditions. Analyzing Figure 3, it is possible to identify the operating conditions indicated above, at least in the first part of the measurements where the wind speed was kept at low levels. This indicates that the source characterizing the background noise is represented by the wind turbine under analysis. The background noise, in fact, undergoes a substantial decrease in the period in which the wind turbine is switched off. It is also possible to verify that under the same operating conditions, the recorded noise changes over time. This fact in the case of turbines in operation can be attributed to the different speeds of the blades, which generate different contributions to the environmental noise. On the contrary, in the conditions with the turbine off, this different trend of background noise confirms that the contributions to the environmental noise have a different origin. A considerable increase in the noise detected by the instrument can be seen in the central part of Figure 3. By analyzing the measured values of the wind speed in this monitoring period (Table 1) it is possible to verify that these speeds undergo a significant increase. This helps us to understand that the increase in noise is due to the noise of the blades which, turning with greater speed due to the greater energy supplied by the wind, produce greater noise. However, analyzing the final part of the monitoring where all the turbines have been turned off, we can see that the background noise with the turbines off is much greater than that recorded in the initial part of the monitoring. This confirms the essential contribution of sources other than wind turbines to the background noise. Among these, the noise of the wind demonstrates a significant weight, impacting on trees or buildings and on the pavement and thus contributing to the background noise.