# Monitoring System of Transmission Line in Mountainous Area Based on LPWAN
## 4 Experiment and Simulation Analysis
### Model Validation and Calibration  
In the experimental simulation, according to the Egli path loss mathematical model established in the previous chapter, the simulation parameters were applied to the model to evaluate the path loss of mountain transmission lines in the application of LoRa transmission module networking. The LoRa operating frequency was set at 474 MHz, the height of transceiver antenna was 40 m, the transmission power was 27 dBm, the gain of the transmitting antenna and receiving antenna were 5 and 2 dB, respectively, and the feeder loss was 0.5 dB. The relationship between the path loss obtained by the program and the distance between the transmitter and receiver of LoRa is shown in Figure 6.  
Figure 6 shows the relationship between the strength of the LoRa signal and the transmission distance in the Egli model. It can be seen from the figure that the actual and theoretical LoRa signal field strength monotonically decreases with the increase in transmission distance, which is consistent with the trend that the field strength decreases with the increase in distance in the Egli model. By comparing the theoretical field strength with the actual field strength, it was found that the actual measured value was significantly lower than the theoretical calculation value, and the decline amplitude of the actual field strength curve was also lower than the theoretical field strength curve, indicating that there were still other factors affecting the LoRa signal transmission. It can be concluded that the Egli model can reflect the distribution trend of the LoRa signal intensity in mountainous areas, but there is a large error, so the model has to be modified. Through the curve fitting toolbox of MATLAB(2016a, MathWorks, Boston) Simulink, the error fitting formula is as follows:  
\[fr(d)=-16.87\lg d+4.225 \tag{25}\] \begin{table}
\begin{tabular}{c c c} \hline \hline
**Detection Target** & **Detection Mode** &
\begin{tabular}{c} **Data Generated by Single** \\ **Acquisition (bit)** \\ \end{tabular} \\ \hline Ambient temperature & Temperature sensor & 170 \\ Ambient humidity & Humidity sensor & 170 \\ Inclination angle of transmission tower & Angle sensor & 830 \\ Climatic wind speed & Wind speed sensor & 170 \\ Vibration acceleration of transmission line & Acceleration sensor & 570 \\ Vibration amplitude of transmission line & Amplitude sensor & 400 \\ Conductor temperature & Temperature sensor & 170 \\ Insulator leakage current & Electromagnetic sensor & 100 \\ String tension & Friction sensor & 150 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Monitoring node sensor data. Figure 6: Comparison of the theoretical field strength and actual field strength of the Egli model. By introducing Equation (25) into Equations (1) and (3), the relationship between the field strength and the transmission distance of the LoRa signal in the case of mountain shelter can be obtained:  
\[E_{R}r=-65.23-20\lg{f}-23.13\lg{d}+20\lg(h_{t}h_{r})+K_{h} \tag{26}\]  
The establishment of a delay model and energy consumption model was the key of this paper. In the delay model, the system delay is determined by the terminal node with the highest transmission delay, so in the experimental simulation, we used the maximum delay \(D_{M}\) to represent the system delay model; similarly, the system life was determined by the terminal node with the highest energy consumption, so the energy consumption of this terminal node was called the bottleneck energy \(E_{B}\) of the system. In this paper, the RHF78-052 LoRa experimental platform was used to test the relationship between the maximum delay and bottleneck energy of the system based on different LoRa wireless transmission groups. In the simulation experiment, the LoRa module works in the same SF and BW and transmits the same byte data at the same time. The number of LoRa wireless transmission groups is the key for the design of a monitoring network.