The Ampelmann system offers a safe and reliable solution for offshore access. As safety is a key factor, an extensive safety and warning management system is employed which accommodates for different fault types that may occur. Accommodation of sensor failure in the Ampelmann system is currently done through switching to a redundant component. However, there are several faults that are left undetected in the system. Detection only occurs when the faults exceed a critical threshold. Exceeding this threshold immediately results in shut-down of the system as safety is no longer guaranteed. For sensor equipment critical to the motion compensation, this leads to a code black in the system. The occurrences of code blacks should be limited where possible due to the fact that these lead to downtime. A critical sensor for the motion control is the position transducer in the hydraulic cylinders. The measured lengths are used for feedback purposes in the control system. The position transducer is redundant in each cylinder. The redundant sensor is mainly utilized for checking the main sensor. However, when the measurements from both sensors deviate too much from one another the system will shut down. Therefore, in this thesis, the possibility of a model-based fault detection method for the position transducer in the hydraulic cylinder is explored. Firstly, an accurate model of the hydraulic cylinder is derived and identified. Then, the model is combined with an observer to generate accurate estimates of the cylinder lengths. Furthermore, the estimates are compared with the actual measured cylinder lengths from the position transducer to generate residuals. Finally, the residuals are evaluated in order to make a decision about the health of the sensor. Three different fault types have been defined, which are expected to cause sensor degradation/failure. For each fault type, the residuals are evaluated. Prior to this a threshold has been defined based on a fault-free case. The threshold determines whether the system is healthy or not. Ideally, when there is no fault in the system, the residual is close to zero. Whereas, when there is a fault present the residual will be much larger. Whenever the threshold is exceeded, the detection system knows that there is a fault present, which allows it to sent out a warning. There are three model-based fault detection estimators which generate three different residuals. These three estimators are combined into one fault detection architecture. The results developed throughout this thesis have provided new insights for the fault monitoring system in the Ampelmann system. Currently it has only been applied for the position transducer. However, it can be extended to other critical components in the system. Furthermore, the work presented in this thesis is valuable for predictive maintenance purposes. Finally, the detection estimators can be used for the implementation of fault tolerant control in the system.