# Diagnosis Method for Mechanical Faults Based on Rotation Synchrotexting Chirplet Transform
## 4 Experiment Test  
The data of the fault signal in this experiment comes from the fault data of the heavy oil machine set [1; 12]. The device structure of collected mechanical fault signals is shown in Figure 14. In the figure, 1#, 2#, 3#, and 4# represent four sets of support bearings. This device consists of gas turbine, compressor, gearbox, motor, etc. The fault signal is collected at a speed of 5381 rpm, the sampling frequency is 2000 Hz. Therefore, the fault characteristic  
Figure 12: TF distribution of \(f(t)\) based on SET. (**a**) TF distribution (**b**) Local enlarged figure. Figure 13: TF distribution of \(f(t)\) based on RSECT. (**a**) TF distribution (**b**) Local enlarged figure. From Figure 16, although the GLCT extracts the faulty feature frequency, the resolution of the features in the time and frequency domains is obviously unsatisfactory and needs further improvement. From Figures 17 and 18 both the SET and RSECT can clearly extract the fault feature frequency of 90 Hz with better resolution in both time and frequency domains, which has obvious advantages. Comparing Figures 17 and 18, the RSECT retains the advantages of the SET, thus further improving the time-frequency resolution and the smoothness of the time-frequency features. The effectiveness of the proposed RSECT is further verified. To further verify the effectiveness, the proposed method is applied to the analysis and processing of the rubbing test data of the double-disk rotor. The rotor experimental stage is illustrated in Figure 19a. The rotor is driven by an electric motor and the bearings are sliding bearings. The vertical and horizontal vibrations are measured by a non-contact eddy current sensor. The rubbing rotor test bench is shown in Figure 19b. Radial rubbing of the rotor is artificially caused by a friction block, as shown in Figure 20.  
Figure 19: (**a**) Schematic diagram of rubbing rotor test bench. (**b**) Rubbing rotor test bench. Figure 20: Rotor radial rubbing fault simulation. Figure 18: Time–frequency distribution obtained by the RSECT. The vibration signals in the horizontal and vertical directions are measured by setting the speed at 3000 r/min, 1024 sampling points and 1600 Hz sampling frequency. Figure 21 shows the time-domain diagrams of two sets of horizontal vibration signals. Figure 22 shows the frequency spectrograms corresponding to Figure 21. From the frequency spectrograms, the signals contain various frequency multiplier components, which are the typical spectral characteristics of rubbing faults. It can be roughly judged that the first group of signals corresponds to slight rubbing, while the second group is severe rubbing. The 1600 Hz sampling frequency and 128 window width is taken to perform the GLCT, SET and RSECT for the signal of slight rubbing and serious rubbing, respectively. The corresponding time-frequency distribution of the three methods are shown in Figures 23-25. Figure 21: Vibration signal of rubbing fault. (**a**) Slight rubbing (**b**) Serious rubbing. Figure 22: Spectrum diagram of rubbing fault. (**a**) Slight rubbing (**b**) Serious rubbing. Figure 12:0 The GLCT for rubbing fault signals. (**a**) Slight rubbing (**b**) Serious rubbing. Figure 12:1 The SET for rubbing fault signals. (**a**) Slight rubbing (**b**) Serious rubbing. From the time-frequency results of the slight-rubbing-fault signal, the GLCT results only represent 1\(\times\) and 2\(\times\) component that are present throughout the signal, and the magnitude of the 2\(\times\) component is less obvious. However, the other higher-order components are not clearly characterized. The SET and RSECT not only characterize the 1\(\times\) and 2\(\times\) components, but also the other high-order components such as 4\(\times\), 6\(\times\), 8\(\times\), and 10\(\times\) components. In the characterization results of high-order components, the RSECT obtains higher amplitudes of the components, which is more advantageous than the SET.