## 4 Experiments
### Signal Storage by Image Style  
The vibration signal acquired by \(\Phi\)-OTDR is stored by the image style. The specific image of each step is shown in Figure 8.  
Figure 8: _Cont_.  
Figure 6: Image of \(\Phi\)-OTDR instrument.  
Figure 7: Image of the standard five-hammer vibration device.  
According to Figure 8, it is obvious that the image of the original signals was not very clear, that of the filtered signals was clearer, with the noise becoming a white background, and that of the enhanced signals was clear and distinguishable.  
Then, the proposed filtering method was contrasted with the Kalman filter and other mainstream methods in terms of the SNR and efficiency. The results are recorded in Table 2 below.  
Table 2 shows that the proposed method outperformed the other approaches in both SNR and efficiency. The advantage was particularly obvious in efficiency, as the proposed method consumed 45% less time than the Kalman filter. This is attributable to two main reasons: First, the vibration signals in our research are mechanically damped and thus easy to handle; second, it is very time-consuming to process distributed vibration signals on each length point. Meanwhile, the SNR of the proposed method was not notably stable because the strong and weak signals had not been fitted by advanced methods at the same time.  
Next, several experiments were carried out between data files in different formats to see if the strategy of saving as images could save disk drive space. The experimental results are shown in Table 3.  
The results in Table 3 reveal that saving signals as images could greatly reduce the storage space. For instance, an image file occupied 1000 times less space than a binary file. In general, the image-based method allows the hard disk space to be searched about 2000 times. This is because the data in images are stored as integers while those in.csv and.mat files are saved as double-precision floating-points, and the image files are smaller than the other files. Thus, the image-based method is a desirable way to save the massive amount of data generated by the \(\Phi\)-OTDR technique.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**No.** & **Name** & **Average SNR (dB)** & **Time (s)** \\ \hline
1 & The method in the paper & 5.0422 & 6.78 \\
2 & Wiener filter & 4.6231 & 12.71 \\
3 & Kalman filter & 4.8672 & 11.18 \\
4 & Adaptive filter & 4.4517 & 14.31 \\
5 & Wavelet filter & 4.9951 & 16.14 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of filtering effects among various methods.  
Figure 8: Images of the signals of each step: (**a**) Image of the original signals; (**b**) image of the filtered signals; and, (**c**) image of the enhanced signals.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**No.** & **Data Format** & **Time** & **Number of Files** & **Size of Single File** & **Total** & **Compress by RAR (Roshal ARchive)** \\ \hline
1 &.mat & 10 s & 1 & 604 MB & 604 MB & 312 MB \\
2 &.csv & 10 s & 1 & 451 MB & 451 MB & 229 MB \\
3 &.bin & 10 s & 1 & 367 MB & 367 MB & 190 MB \\
4 &.jpg & 10 s & 20 & 16.6 KB & 352 KB & 189 KB \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of data file sizes in different formats.