# Improving the Strategy of Maintaining Offshore Wind Turbines through Petri Net Modelling
## 4 Dynamic PN Modelling of the O&M of an Offshore Wind Turbine
### Detection Petri Net (DPN)  
Since the DPN is developed for simulating the fault detection process by the CMS, the DPN is embedded into the model only when there is at least one fault occurring in any one of the six subsystems.  
As Figure 6 shows, in the DPN, Transition \"D1\" governs the whole process. The arcs, represented by the dashed arrow lines, connect Transition \"D1\" with the condition places, \"Fault is detected\" and \"Fault is not detected\". The probabilities that a token transfers  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Subsystem**} & \multirow{2}{*}{**Annual Failure Rate**} & \multicolumn{2}{c}{**Subsystem Fault**} & \multicolumn{2}{c}{**Subsystem Failure**} \\ \cline{3-5}  & & & **Year** & & **Year** \\ \hline Rotor & 0.0868 & \(\beta=1.2\) & \(\eta=9.22\) & \(\beta=1.2\) & \(\eta=2.30\) \\ \hline Drivetrain & 0.0600 & \(\beta=1.2\) & \(\eta=13.33\) & \(\beta=1.5\) & \(\eta=3.33\) \\ \hline Power system & 0.1430 & \(\beta=1.2\) & \(\eta=5.59\) & \(\beta=1.2\) & \(\eta=1.40\) \\ \hline Bearing system & 0.1534 & \(\beta=1.2\) & \(\eta=5.22\) & \(\beta=1.2\) & \(\eta=1.30\) \\ \hline Braking system & 0.0799 & \(\beta=1.2\) & \(\eta=10.01\) & \(\beta=1.2\) & \(\eta=2.50\) \\ \hline Structure & 0.0790 & \(\beta=1.2\) & \(\eta=10.13\) & \(\beta=1.2\) & \(\eta=2.53\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Weibull distribution parameters for Transitions “W1” to “W12”.  
to either of the two places are dependent on the fault detection capability of the CMS. This fault detection capability may be affected by many factors, such as the types of the sensors, condition monitoring algorithm, the scope of components that the CMS monitors, etc. [27]. In this study, to investigate the influence of the quality of the CMS on the O&M, three scenarios are considered. These scenarios are \"Without using CMS\", \"After using a basic CMS\", and \"After using a premier CMS\". The probabilities that the faults can be detected by the CMS in the three scenarios are listed in Table 2. The probability data for the scenario of using a basic CMS is from [28]. The probability data for the scenario of using a premier CMS is set to be 0.997 for all six subsystems in order to investigate the maximum contribution of the CMS to the O&M under ideal conditions. All the data in Table 2 can be modified based on the actual capability of the CMS. Once the fault is detected by the CMS, i.e., a token is produced in Place \"Fault is detected\", the RMPN will then be embedded into the model to prepare the essential maintenance resources and then fix the fault. If the fault is not detected by the CMS, a token is produced in Place \"Fault is not detected\" and no action will be taken in the DPN. Once a token is produced either in Place \"Fault is detected\" or in Place \"Fault is not detected\", the DPN will be removed from the model. The undetected fault will continue to develop with time. This developed fault will either eventually lead to the failure of the corresponding subsystem or it will be discovered during the next run of the inspection during \"advanced service\".