## 3. Gear Test Experimental Setup and Data Processing  
Raw AE signals and vibration signals collected from gear pitting fault experiments were used to validate the effectiveness of the presented method for the diagnosis of gear pitting faults. The experiments were carried out on a gearbox test rig. The raw vibrational signals and AE signals of seven different gear pitting conditions were collected during the experiments. The gearbox test rig is shown in Figure 4. It consists of two 45 kW Siemens servos, one of the servos is the driving motor, and the other is the loading motor. An acceleration sensor and an AE sensor were mounted on the surface of the gearbox housing. The main parameters of the gearbox are shown in Table 1.  
Figure 4. Picture of the gearbox test rig. The gear speed was set to 1000 RPM, and 100 Nm torque was used in the experiments. The vibrational signals were collected with a sampling rate of 10.24 kHz. The AE signals were collected with a sampling rate of 51.2 kHz. Table 2 shows the seven gear pitting conditions. Condition 1 represents a normal gear. In Condition 2, the pitting is about 10% of the area of a middle tooth, and the adjacent two teeth are normal. Condition 3 has a pitting of about 30% of the area of the middle gear tooth, and the adjacent two teeth are normal. Under Condition 4, the middle gear tooth pitting is about 50% of the area, and the adjacent two teeth are normal. Under Condition 5, the middle gear tooth pitting is about 50% of the area, the upper tooth pitting is about 10% of the area, and the lower tooth is normal. Under Condition 6, the pitting of the middle gear tooth is about 50% of the area, and the adjacent two teeth pitting is about 10% of their area. Under condition 7, the middle gear tooth pitting is about 50% of the area, upper tooth pitting is about 30% of the area, and the lower tooth pitting is about 10% of the area. Figure 5 shows pictures of the gear pitting degree under each pitting condition. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Gear Condition** & **Upper Tooth** & **Middle Tooth** & **Lower Tooth** \\ \hline Condition 1 & Normal & Normal & Normal \\ Condition 2 & Normal & 10\% & Normal \\ Condition 3 & Normal & 30\% & Normal \\ Condition 4 & Normal & 50\% & Normal \\ Condition 5 & 10\% & 50\% & 10\% \\ Condition 6 & 10\% & 50\% & 10\% \\ Condition 7 & 30\% & 50\% & 10\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The approximate percentage of pitting area under seven gear conditions. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Gear Parameter** & **Driving Gear** & **Driving Gear** \\ \hline Tooth number & 72 & 40 \\ Module (mm) & 3 & 3 \\ Pitch diameter (mm) & 120 & 120 \\ Base circle diameter (mm) & 202.974 & 112.763 \\ Pressure angle (\({}^{\circ}\)) & 20 & 20 \\ Tooth width (mm) & 85 & 85 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The major parameters of the gearbox. Figure 5: Fitting degree of driven gears. The sample raw vibrational signals of the gears are shown in Figure 6. As shown in Figure 6, Conditions 1 and 3 have relatively distinct spikes and show slightly different from the remaining five vibrational signals. The raw vibration signals of the remaining five conditions are not significantly different. The sample AE signals of gears are shown in Figure 7. As can be seen from Figure 7, there are no significant differences among raw AE signals of the seven conditions. It is almost impossible for the naked eye to distinguish the difference in the pitting conditions of the gears from the AE signals. The number of samples for the vibration data/ AE data under each condition was 1000, with 800 for training set, 150 for validation, and 50 for testing. Each condition had the same number of samples. The CNN was connected using 4 convolutional layers, which was an arbitrary choice based on the experience. The number of channels in each layer was set 32, 64, 128, and 128, respectively. Figure 6: Raw vibrational signals of the gear pitting fault conditions.