## 3 Experiments  
### Inlet Distortion Experiment  
In this study, an engine was used to simulate the disfunction of inlet distortion, and the AE monitoring technique was employed to identify the impact of inlet distortion on the stability of the engine. Figure 2 shows a schematic representation of the experiment. With the arrangement of two mobile spoilers in front of the engine to block the inlet through its horizontal motion, a large number of turbulent flows were generated to simulate the process of inlet distortion. The AE sensors were located on the engine casing to collect the AE signals generated by the faults. By applying the AE monitoring technique, it would be feasible to continuously monitor and identify the simulated faults.  
Four types of sensors, R3, R6, R15, and WSa, are selected in this paper. Their characteristic parameters are shown in Table 1. Each measurement point was equipped with 2 sensors, and a total of 14 sensors were arranged on the casing. During this experiment, the sample rate was 1 MHz, and the hit length was 2 KHz. Threshold for AE detection is 38 dB for R1, R2, R3, R4, R9, R10, and R11 and 38 dB for R5, R6, R7, R8, R13, and R14. Accordingly, with setting the relevant parameters of the AE monitoring technique appropriately, efficient identification of the inlet distortion is applicable.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Type of Sensors** & **Center Frequency (kHz)** & **Frequency Range (kHz)** & **Sampling Frequency (MHz)** \\ \hline R3 & 30 & 20–80 & 1 \\ R6 & 60 & 35–100 & 1 \\ R15 & 150 & 50–200 & 1 \\ WSa & 550 & 100–1000 & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Characteristic parameters of sensors.  
Figure 2: Schematically representation of testing the inlet distortion.  
Figure 3 shows the flowchart of an experiment performed to study inlet distortion of the engine.  
In Figure 3, \(\overline{\text{N}}_{2}\) is the actual speed of the engine divided by 10,000. The engine would be started until all the technical indicators of engine satisfy the requirements of airworthiness [25; 26] and the AE technique was normally running. Then, the speed of the engine was controlled at 8976 rpm after warming up the engine. Next, the Spoiler1 was moved to start the inlet distortion experiments at a speed of V1 = 40 mm/s, and the Spoiler2 remained stationary. According to the parallel compressor model, the inlet distortion \(J\) is defined as:  
\[J=\frac{S_{1}+S_{2}}{S} \tag{8}\]  
where \(S_{1}\) and \(S_{2}\) are the areas where the inlet was blocked by Spoiler1 and Spoiler2, respectively, and \(S\) is the total area of the inlet, as shown in Figure 4.  
Figure 4: Inlet distortion diagram.  
Figure 3: The flowchart of an experiment conducted to study inlet distortion based on the acoustic emission (AE) technique.  
Hence:  
\[S_{1}=\frac{1}{720}\pi D^{2}\arccos(1-\frac{2H_{1}}{D})-\sqrt{DH_{1}-H_{1}{}^{2}}( \frac{D}{2}-H_{1}) \tag{9}\]  
\[S_{2}=0 \tag{10}\]  
\[S=\frac{1}{4}\pi D^{2} \tag{11}\]  
where \(H_{1}\) is the moving distance of the Spoiler1, \(D\) is the diameter of the engine inlet, and \(H_{1}/D\) is an independent variable.  
Entering Equations (9)-(11) into Equation (8) yields Equation (12):  
\[J=\frac{1}{180}\arccos(1-\frac{2H_{1}}{D})-\sqrt{\frac{H_{1}}{D}-(\frac{H_{1}}{ D})^{2}}(2-4\frac{H_{1}}{D})\frac{1}{\pi} \tag{12}\]  
where \(J\) is one of the important parameters to characterize the degree of the inlet distortion [27]. Eventually, when \(H_{1}/D\) reaches 45%, i.e., \(J\) reaches 43.64%, the spoiler1 will stop moving. Then, the spoiler1 will be withdrawn, and the engine will stop operating to stop the experiment.