## 4 Experimental Data Acquisition
### Health State Settings of Axial Piston Pumps  
Figure 6 illustrates the six distinct health states of the axial piston pump: the normal piston pump (NOR), cavitation damage of the valve plate pair (CDV), slipper wear fault (SWF), piston wear fault (PWF), rolling element damage of the front-end bearing (RDFB), and rolling element damage of the rear-end bearing (RDRB). In Figure 7, the corresponding time domain signals for each of these fault types are presented. The normal state, NOR, is characterized by a lack of any fault. Conversely, the CDV, SWF, and PWF represent fault states pertaining to the valve plate pair, slipper pair, and piston pair, respectively. Specifically, CDV is indicative of cavitation damage faults (1 mm in width) between adjacent piston holes on the cylinder block. SWF points to slipper wear faults (0.02 mm in wear along the thickness). PWF signifies piston wear faults (0.009 mm in wear along the diameter). Lastly, RDFB and RDRB denote rolling element damage affecting the front-end and rear-end bearings. In both cases, rolling element damage manifests as grooves 0.5 mm in width. A detailed overview of these states can be found in Table 4. \begin{table}
\begin{tabular}{c c c} \hline \hline
**No.** & **Names** & **Descriptions** \\ \hline
1 & Electric motor & ABB-IEL-280M75 \\
2 & Axial piston pump & A4 VSO40 \\
3 & Output pressure transducer & HM90-0–35 MPa-H3V2F1 \\
4 & Reliewe valve & DBW30B-1-50B/350 bar \\
5 & Data acquisition module & Type LAN-XI 3050, Bruel and Kjaer, \\
6 & Laptop & ASUS K450V with PULSE \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Detailed descriptions of the test platform. \begin{table}
\begin{tabular}{c c c} \hline \hline
**No.** & **Names** & **Descriptions** \\ \hline
1 & Transducer model & WIKA A-10 pressure transmitter \\
2 & Pressure range & 0–10 MPa \\
3 & Accuracy & \(\pm\)0.25\% full scale (FS) \\
4 & Sampling frequency & 10 kHz \\
5 & Output signal & 4–20 mA (converted via 16-bit ADC) \\
6 & Impulse tube length & \textless{}200 mm \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Technical specifications of the pressure transducer. \begin{table}
\begin{tabular}{c c c} \hline \hline
**No.** & **Names** & **Value** \\ \hline
1 & Rotating speed & 1500 r/min \\
2 & Maximum displacement & 40 mL/r \\
3 & Output pressure & 21 MPa \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Detailed parameters of the axial piston pump. Figure 6: Six health states of axial piston pumps. Figure 7: Time domain signals corresponding to different fault types. (**a**) NOR; (**b**) CDV; (**c**) SWF; (**d**) PWF; (**e**) RDFB; (**f**) RDRB. As illustrated in Figure 8, FFT analysis was carried out on a range of time domain pressure signals for various fault types associated with axial piston pumps, and the results show minimal differences in the spectral output between different fault types. These findings clearly suggest that when subject to significant background noise, a lack of significant variance in spectral features underscores the point that shallow spectral analysis of system data should not be solely relied upon as an accurate method of diagnosing potential faults. To investigate the time-frequency spectrum of the output pressure signal, continuous wavelet transforms (CWT) were employed to convert six distinct health conditions into 2D time-frequency representations. In the signal pre-processing phase, the complex Morlet \begin{table}
\begin{tabular}{c c c} \hline
**No.** & **Names** & **Descriptions** \\ \hline
1 & NOR & Normal \\
2 & CDV & Cavitation damage of the valve plate pair \\
3 & SWF & Slipper wear fault \\
4 & PWF & Piston wear fault \\
5 & RDFB & Rolling element damage of the front-end bearing \\
6 & RDRB & Rolling element damage of the rear-end bearing \\ \hline \end{tabular}
\end{table} 
Table 4: Detailed descriptions of different health states. Figure 8: Frequency domain corresponding to different failure types. (**a**) NOR; (**b**) CDV; (**c**) SWF. (**d**) PWF; (**e**) RDFB; (**f**) RDRB. wavelet was selected as the basis function.