Electrical machines are subject to different types of failures. Early detection of the incipient faults and fast maintenance may prevent costly consequences. Fault diagnosis of wind turbine is especially important because they are situated at extremely high towers and therefore inaccessible. For offshore plants, bad weather can prevent any repair actions for several weeks. In some of the new wind turbines synchronous generators are used and directly connected to the grid without the need of power converters. Despite intensive research efforts directed at rotor fault diagnosis in induction machines, the research work pertinent to damper winding failure of synchronous machines is very limited. This dissertation is concerned with the in-depth study of damper winding failure and its traceable symptoms in different machine signals and parameters. First, a model of a synchronous machine with damper winding based on the winding function approach is presented. Next, simulation and experimental results are presented and discussed. A specially designed inside-out synchronous machine with a damper winding is employed for the experimental setup. Finally, a novel analytical method is developed to predict the behavior of the left sideband amplitude for different numbers and locations of the broken bars. This analysis is based on the magnetic field theory and the unbalanced multiphase circuits. It is found that due to the asymmetrical structure of damper winding, the left sideband component in the stator current spectrum of the synchronous machine during steady state asynchronous operation is not similar to that of the induction machine with broken bars. As a result, the motor current signature analysis (MCSA) for detection rotor failures in the induction machine is usable to detect broken damper bars in synchronous machines. However, a novel intelligent-systems based approach is developed that can identify the severity of the damper winding failure. This approach potentially can be used in a non-invasive condition monitoring system to monitor the deterioration of a synchronous motor damper winding as the number of broken bars increase over time. Some other informative features such as speed spectrum, transient time, torque-speed curve and rotor slip are also found for damper winding diagnosis.