# Monitoring-System Development for a Bottom-Set Gillnet through Time-Domain Dynamic Simulations
## 7 Example of Monitoring Algorithm  
In this section, we demonstrate an example of the machine-based problem-detection algorithm based on sensor signals. Figure 19 shows the developed monitoring algorithm, which was based on the monitoring parameters identified in the previous section. For simplicity, it was assumed that there are four inputs and six outputs. The four inputs were one tension sensor installed at the top of the center-upper-mooring line (Y = 0 m), X-Y accelerometers at the middle height of the net (Y = 0 m), and one displacement sensor on the middle location buoy (Y = 0 m). Since accurate judgment within a time step is difficult, the algorithm detects evidence of abrupt changes within the window by considering continuous small windows of the sensor signals. Mooring lines other than the center one at Y = 0 m are defined as neighboring mooring lines. To check the variation of sensor signals, the average values and standard deviations were continuously obtained inside a small window. To validate the flowchart-based-monitoring algorithm, various failure scenarios were additionally simulated using a wave condition of \(H_{s}\) = 2.5 m and \(T_{p}\) = 7.5 s. The current was also fixed as 0.6 m/s.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Mooring-Line-Breakage** & \begin{tabular}{c} **TEN** \\ **Location** \\ \end{tabular} & \begin{tabular}{c} **TEN** \\ **(Y = 0 m)** \\ \end{tabular} & \begin{tabular}{c} **TEN** \\ **(Y = -150 m)** \\ \end{tabular} & \begin{tabular}{c} **DX** \\ **(Y = 0 m)** \\ \end{tabular} & \
\begin{tabular}{c} **AX** \\ **(Y = 0 m)** \\ \end{tabular} &
\begin{tabular}{c} **AY** \\ **(Y = 0 m)** \\ \end{tabular} \\ \hline \(-100\) m & TOP & 0.178 & 0.124 & 0.116 & 0.080 & 96.867 & 0.266 & 0.136 & 0.045 \\ \(-100\) m & BOT & 0.178 & 0.124 & 0.116 & 0.081 & 96.867 & 0.266 & 0.140 & 0.035 \\ \(-100\) m & TOP and BOT & 0.180 & 0.124 & 0.197 & 0.129 & 96.858 & 0.266 & 0.144 & 0.074 \\ \(-150\) m & TOP & 0.178 & 0.125 & 0.000 & 0.002 & 96.867 & 0.266 & 0.134 & 0.058 \\ \(-150\) m & BOT & 0.178 & 0.125 & 0.184 & 0.126 & 96.867 & 0.266 & 0.139 & 0.025 \\ \(-150\) m & TOP and BOT & 0.173 & 0.121 & 0.000 & 0.002 & 96.833 & 0.267 & 0.141 & 0.052 \\ \hline \hline \end{tabular}
\end{table}
Table 6: _Cont._  
Figure 18: Time histories of the surge motion of the location buoy in the middle location as the rope in the middle location (Y = 0 m) is broken after 600 s (\(H_{s}\) = 2.0 m, \(T_{p}\) = 7.0 s, current velocity = 0.6 m/s).  
Figures 20 and 21 show test results for Output 1 = both mooring lines at Y = 0 m are broken and Output 3 = both of the adjacent mooring lines at Y = \(-\)50 m are broken. The mooring lines were broken after 600 s. Failures were detected well in both cases and the problems were correctly identified. In the case of Output 1, there was a small time lag for detection of about 20 s. The slowly varying surge motion of the location buoy leads to this time delay even if the top mooring tension suddenly became zero. However, the time lag for detecting failure was small, which is acceptable for fishing gear failure monitoring. In the case of Output 3, even though the average value and standard deviation of the mooring tension varied slowly, X and Y accelerations abruptly changed, which resulted in the fast detection of failure even without the time lag. Although not presented here, we tested a number of other failure scenarios, and the developed algorithm was always able to correctly detect and identify the given problem. The overall results demonstrate that the proposed monitoring algorithm can be used for the machine-based problem-detection system of the bottom-set gillnet. A more extensive monitoring system can also be developed with more input and/or output variables.  
Figure 19: Failure detection algorithm.  
Figure 20: Time histories of failure detection status when both mooring lines in the middle location (Y = 0 m) are broken after 600 s (\(H_{s}\) = 2.5 m, \(T_{p}\) = 7.5 s, current velocity = 0.6 m/s). Status 1 indicates the Output 1 case.