## 4 Experimental Setup and Data Processing  
### Experimental Setup  
The data acquisition system includes compressors, an acceleration sensor, a data acquisition card with a corresponding crate and a computer. The connectivity of the data acquisition system components is shown in Figure 3. The computer uses LabVIEW2020, a software that integrates signal measurement, control and visualization. The crate and data acquisition card are both made by National Instruments. The crate is a Cdaq-9171 minicrate, and the data acquisition card is a NI-9234 high\(-\)speed acquisition board. The acceleration sensor is installed in the center of the upper surface of the compressor, as shown in Figure 3. In order to match the detection time on the production line with the production beat, it can be seen that a sensor measuring vibration signal is the best choice. The sensor has a sensitivity of 100 mV/g. The sampling frequency of the sensor is 25.6 kHz. The speed of the compressor is 3000 rpm. These typical manufacturing defects are shown in Table 2 and Figure 4. The model is conducted in Python 3.6, 64 bits running on Windows 10 \(\times\) 64, an Intel Xeon Silver 4214 CPU with 128 G and a GeForce RTX 2080 Ti GPU with 11 GB. Keras version 2.1.6 is used for deep learning analysis.  
Figure 2: The overall framework of the proposed method.  
In order to analyze the system of acquiring and analyzing data in energy saving, the following calculation steps are required. Firstly, we calculate the energy consumption when the acquisition and analysis system diagnoses a malfunctioning compressor. Assuming that a factory produces 3000 units a day, the probability of failure (\(\Delta_{p}\)) is 0.5%.  
\[Q_{acq}=P_{acq}*h_{acq}/(P*\Delta_{p}) \tag{15}\]  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Label** & **Manufacturing Defect Description** & **Number of Training/Testing Sample** \\ \hline \#0 & Normal hermetic refrigeration compressor & 1200/300 \\ \#1 & Discharge pipe contacting stator & 1200/300 \\ \#2 & Crankshaft contacting discharge pipe & 1200/300 \\ \#3 & Shedding of support spring & 1200/300 \\ \#4 & Incorrect position of silencer & 1200/300 \\ \#5 & Foreign body in suction valve & 1200/300 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Description of hermetic refrigeration compressor manufacturing defect.  
Figure 4: Fault type of hermetic refrigeration compressor. (**#1**) Discharge pipe contacting stator; (**#2**) Crankshaft contacting discharge pipe; (**#3**) Shedding of support spring; (**#4**) Incorrect position of silencer; (**#5**) Foreign body in suction valve.  
Figure 3: Experiment platform.  
The power of the acquisition and analysis system (\(P_{acq}\)) is 450 w/h, and the system run time (\(h_{acq}\)) is 20 h a day. P is daily production. Therefore, \(Q_{acq}\) is 0.6 kWh.  
Secondly, we calculate the energy consumption of the refrigerator when the compressor fails.  
\[Q_{ref}=W_{comp}*\Delta_{w}*h_{r}*\beta \tag{16}\]  
The refrigerator compressor consumes (\(W_{comp}\)) 385 kWh of energy annually [29]; the life of the refrigerator (\(h_{r}\)) is ten years; the utilization rate of the refrigerator (\(\beta\)) is 0.8; and \(\Delta_{w}\) represents power consumed increase rate. The calculation formula of COP is as follows:  
\[COP=Q_{h}/W \tag{17}\]  
Here, \(Q_{h}\) represents the heating capacity (kW), and \(W\) represents the power consumed (kW).  
The COP of a compressor (\(\Delta_{cop}\)) reduces by about 10% when the compressor valve leaks [6]. When the heating capacity is not changed, power consumed (\(\Delta_{w}\)) increases by about 10%.  
Therefore, the energy consumption of the refrigerator increases by 308 kWh when the compressor fails. The energy that can be saved is 307.4 kWh when producing a malfunctioning compressor.