## 5 Conclusions  
For power transmission line state monitoring, many types of sensors have been developed and used. IoT-based sensor networks need to deploy corresponding sensors, which are bound to consume a lot of manpower. In addition, supplying the power for the sensors and networks is also a hard and challenging issue, especially when a large number of sensors are distributed in a wide area. The all-optical fiber point type sensors, such as FBG and FPI, can be used to monitor the ice circumstances and temperature information, but they can only cover dozens of sensing nodes, so the dead zone is quite obvious. Therefore, the distributed optical fiber sensors that adopt the optical fiber in OPGW/OPPC as the sensing media have great application potential. The OPGW and OPPC are widely used in optical fiber composite power transmission lines, so they provide a natural media to monitor the health state of the power transmission lines by distributed optical fiber sensors, in which massive sensing nodes are considered to be continuously distributed along the sensing fiber. For distributed temperate/strain measurement with a high dynamic range, COTDR is a preferential instrument. So, for ultra-long-distance OPGW/OPPC monitoring, the measurement efficiency within acceptable accuracy has to be studied. Then, a COTDR system is constructed, and the OTDR trace is obtained. By statistical analysis, the CRN in the OTDR trace is similar to the standard normal distribution, so the Gaussian noise is adopted to simulate Rayleigh scattering spectra by frequency sweeping at each position along  
\begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Array Length** & **11** & **21** & **31** & **51** & **101** \\ \hline Average number & 10,000 & 10,000 & 10,000 & 10,000 & 1000 \\ Time for signal sampling & 110 s & 210 s & 310 s & 510 s & 101 s \\ Time for data processing & 78.2 s & 81.6 s & 82.3 s & 85.7 s & 90.4 s \\ Total time consumption & 188.2 s & 291.6 s & 392.3 s & 595.7 s & 191.4 s \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of the system measurement time with different array lengths.  
Figure 12: The time consumption of signal processing for different array lengths.  
the sensing fiber. In consideration of the system measurement range, an array with 301 frequency points at each fiber position is built as the standard reference of Rayleigh spectra. Then, the arrays with 11, 21, 31, 51, and 101 frequency points with extra Gaussian noise are formed. By maximal cross-correlation coefficient algorithm, the Rayleigh frequency shift is computed and compared, and it is found that a longer array length has a better anti-noise effect. By the analysis of the signal acquisition time, which is decided by OTDR trace average number and signal processing time, the results indicate that the signal acquisition time is the key factor that influences the system measurement efficiency. To balance the system measurement efficiency and accuracy, the array length with 101 frequency sweeping points and an OTDR trace average number of 1000 times are the best parameters for ultra-long-distance OPGW/OPPC distributed temperature/strain monitoring.  
Conceptualization, L.L. and X.S.; methodology, L.L.; software, X.S.; validation, L.L. and X.B.; formal analysis, C.Z.; investigation, C.Z. and Q.G.; resources, L.L.; data curation, X.S.; writing--original draft preparation, L.L.; writing--review and editing, L.L.; visualization, X.S.; supervision, L.L.; project administration, L.L.; funding acquisition, L.L. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Natural Science Foundation of China with Grant No. 51977001.  
Not applicable.  
The authors declare no conflict of interest.