# End-To-End Convolutional Neural Network Model for Fear Fault Diagnosis Based on Sound Signals
## 3 Experiment System  
Gear fault diagnosis experiments based on an acoustical signal was conducted in a semi-anechoic room. The experiment system we built is composed of a two-stage gearbox, a variable frequency motor, a frequency converter, a programmable magnetic brake component, a tension controller, and measuring systems. The measuring system consisted of four 4189-A-021 free-field microphones from Denmark B&K company, a data acquisition instrument from Germany HEAD company, and Artemis data recording software. The microphones and data acquisition instrument were connected by a Bayonet Nut Connector (BNC) interface for data transmission and data were recorded by Artemis software. The whole experiment system is shown in Figure 4. The top-left corner of Figure 4 shows the test bench and the lower-left corner shows the data acquisition system. The two-stage gearbox reduction ratio was 23.34, the high-speed shaft reduction ratio was 18/81, and the low speed shaft reduction ratio was 16/83. The sketch map of the gearbox is shown in Figure 5. In this study, the gear fault of low speed shaft was chosen to be studied, and the acoustical signals are collected from normal gears, gears with a tooth fracture, gears with pitting, and gears with wear. All these gears' acoustical signals were measured by a four-channel microphone array, which was arranged symmetrically with a hemispherical enveloping surface and the coordinates were set according to the ISO 3745:2003 standard. The layout of the array is shown in right picture of Figure 4. The different fault patterns are shown in Figure 6.  
We set the speed of motor to 1800 rev/min by adjusting the frequency converter. In this condition, the shaft frequency of the three shafts and the meshing frequency of the two pairs of gears are shown in Table 2. We assumed that the interference of other parts of the gearbox, such as bearing and shaft by vibration, were minor. The acoustical signal that we measured can be viewed as only containing the gears. In addition, the tension controlled by a programmable magnetic brake component was set to 0 mA and 0.45 mA to simulate the no load state and the load state of 13.5 Nm. the sampling frequency of microphones was set to 16,000 Hz. The audio file was recorded for 60 s, and for each fault type of gears, we collected 40 audio samples with four channels.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Layer** & **Input Shape** & **Filter** & **Kernel Size** & **Stride** & **Output Shape** \\ \hline Conv1 & [batch,16896,1,4] & 32 & (8,1) & (1,1) & [batch,16896,1,32] \\ Conv2 & [batch,16896,1,32] & 32 & (8,1) & (1,1) & [batch,16896,1,32] \\ Pool & [batch,16896,1,32] & - & (64,1) & (64,1) & [batch,264,1,32] \\ Reshape & [batch,264,1,32] & - & - & - & [batch,264,32,1] \\ Conv3 & [batch,264,32,1] & 48 & (5,5) & (1,1) & [batch,264,32,48] \\ Conv4 & [batch,264,32,48] & 48 & (5,5) & (1,1) & [batch,264,32,48] \\ Conv5 & [batch, 264,32,48] & 48 & (5,5) & (2,2) & [batch,132,16,48] \\ Conv6 & [batch,132,16,48] & 48 & (5,5) & (2,2) & [batch,66,8,48] \\ Conv7 & [batch,66,8,64] & 64 & (5,5) & (2,2) & [batch,33,4,64] \\ Fc8 & [batch,200] & - & - & - & [batch,4] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameter of the end-to-end stacked CNN.  
Figure 4: Experiment system in semi-anechoic.  
Figure 5: The sketch map of two-stage gearbox.  
Figure 6: Three different fault patterns of gears.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Number** & f1 & f12 & f2 & f34 & f3 \\ \hline
**Working Frequency (Hz)** & 25 & 540 & 15 & 106.6 & 3 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Working frequency of each part of gearbox.