## 4 Results  
This section presents the results obtained applying the methodology described in the previous section. The available data are measured on an in-service vehicle travelling on a high-speed line in Germany (maximum speed 200 km/h). The non-motorised vehicle under consideration is equipped with eight axle box accelerometers and eight microphones. The measurement locations are shown in Figure 3. The sampling frequency of the data is 8 kHz. From the acquired data, a section is identified based on the microphone measurements searching for the maximum value of the (_Leq_) calculated every 100 m.  
A section is identified and highlighted in relation to the curvature in Figure 4. The noise level is significantly higher on the left side than the right one, for both the first and second wheelset. As the section represents a left-hand curve, the noise level is in accordance with the definition of slip waves: rail corrugation that occurs on the inner/low rail in curves. Therefore, the potential rail corrugation is expected on the left side and the following investigation is focused on the left axle box accelerations (acc_left_1, acc_left_2). Firstly, it is important to verify that the noise is not caused by a bridge, switch or tunnel. The location of these construction singularities is shown in Figure 5 in combination with the axle box acceleration measurements. No singularities are found in the highlighted section and therefore the FFT analysis is carried out. To verify that the axle box accelerations are consistent with the microphone measurements, the FFT analysis is performed on the left side as shown in Figure 6. The acceleration measurements clearly show peaks within the wavelength range of the rail corrugation. These peaks can be observed on the left side on both the first and second wheelset of the front bogie (main acceleration peaks at wavelengths: 65, 60, 47 mm). Figure 4: Curvature. Figure 5: Axle box acceleration and construction positions. Figure 3: Sensor positions. The decision to analyse the left side is based on the _Leq_ and the curvature in the selected section. However, to support the preliminary hypothesis, it is important to compare the accelerations on both sides. To do this, the amplitude spectrum in the 100 m section is compared between the left and right axle box accelerations of the first wheelset in Figure 7. Looking at the three main peaks, there is a higher excitation on the left side, where slip waves are expected, but the peaks can also be seen on the right side with much lower amplitudes. This can be explained by the vibration transfer path of a rigid wheelset. At this stage of the analysis, the characteristics of the peaks found in the 40-70 mm wavelength range in the 100 m section are consistent with the rail corrugation hypothesis. However, these excitations may be due to other effects. To further investigate the cause, it is important to understand whether the peaks are constant in frequency or in wavelength. To do this, three passages at different vehicle speeds over the section are compared. Figure 8a shows the three vehicle speeds (42.3, 30.2 and 18.2 m/s) considered for comparison over the 100 m section highlighted. In Figure 8b,c, the passages are compared in terms of FFT in the frequency and wavelength domain, respectively. It is clear from the comparison that the peaks analysed are constant in the wavelength domain and not in the frequency domain. This means that the cause could be rail or wheel defects. Therefore, constant frequency excitation, such as vehicle and track modes of vibration, can be excluded. The rail corrugation hypothesis is still valid, but the spectrogram analysis is required to distinguish between wheel and rail defects. If runs at different vehicle speeds over the same section are not available, this result can also be achieved with the spectrogram analysis, as shown in the following. With the spectrogram analysis along the track, a complete overview of the axle box acceleration frequencies can be easily visualised to complete the exclusion process.