## 5 Application for Reciprocating Compressor
### Reciprocating Compressor Bearing Clearance Failure Experimental Study  
The reciprocating compressor is one of the most commonly used power tools for compressing natural gas for long-distance transportation. This type of compressor is highly efficient and reliable, making it adaptable to different operational conditions and environmental situations [36; 37]. The reciprocating compressor structure is complex, with multiple parts, mainly including body parts, power transmission mechanisms, working chamber, and auxiliary accessories. The connecting rods of connecting rod members in the reciprocating compressor drive train are connected to the crankshaft and the crosshead pins through rotary joints. In practical constructions, plain bearings are usually used as heavily loaded joints. Over time, plain bearings experience an increase in clearance due to friction and wear [38]. Excessive clearance produces large impact and friction-damping problems under reciprocating inertia forces, which seriously affects the performance of the equipment. Therefore, a set of processing methods suitable for reciprocating compressor-bearing fault signals is proposed, which realizes feature extraction and pattern recognition of different faults through adaptive decomposition preprocessing and the fusion of the entropy analysis method and the feature preference strategy, and has relatively high value for engineering applications. The bearing clearance vibration signal of the reciprocating compressor 2D12-70 is selected as the data source for this paper. The main technical parameters of the 2D12-70 reciprocating compressor are shown in Table 1[39; 40]. A study was conducted on the failure of a double-acting reciprocating compressor of type 2D12. In the actual test, sensor A was set above the crankcase to record the vibration signal. Figure 10 illustrates the three-dimensional and planar positioning of sensor A. The data acquisition analyzer used in this study was a portable 16-channel device, specifically the UT9001 model. The sensor employed was an ICP accelerometer with a sensitivity of 10 mv/unit. The frequency of the reciprocating compressor was determined to be 8.27 Hz, derived from a rotational speed of 496 r/min. The sampling time was set at 4 s, the sampling frequency at 50 kHz, and continuous sampling was conducted 100 times. Data were collected for three different states: normal condition bushing with a 0.1 mm gap, moderate wear state with a 0.2 mm gap, and severe wear state with a 0.3 mm gap [41]. Bushings in normal and different wear states are shown in Figure 11. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter Type** & **Parameter Valve** \\ \hline Shaft power (kW) & 500 \\ Exhaust volume (m\({}^{3}\)/min) & 70 \\ Primary exhaust pressure (MPa) & 0.2746–0.2942 \\ Secondary exhaust pressure (MPa) & 1.2749 \\ Piston stroke (mm) & 240 \\ Crank speed (rpm) & 496 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Main technical parameters of the 2D12-70 reciprocating compressor. Figure 9: Flowchart of the fault diagnosis method. The fault simulation experiments were conducted on a type 2D12 opposed double-acting reciprocating compressor, selecting technical parameters reflective of actual operational conditions. In the wear diagnosis of reciprocating compressor bearings, high-dimensional mapping entropy (HDME) should accurately reflect fault characteristics under varying wear conditions and possess strong discriminatory power regarding the severity of faults. This paper discusses the applicability of HDME, focusing primarily on the capture of characteristic features at different stages of bearing wear within an engineering production context and quantifying states of normal, moderate, and severe wear. A normal bearing at 0.1 mm clearance, a moderately worn bearing at 0.2 mm clearance, and a severely worn bearing at 0.3 mm clearance were chosen. These gaps represent typical wear gaps encountered in engineering experimental production operations.