Although the history of diesel engines extends back to the end of the nineteenth century and in spite of the predominant position such engines now hold in various applications, they are still subject of intensive research and development. Economic pressure, safety critical aspects, compulsory onboard diagnosis as well as the reduction of emission limits lead to continuous advances in the development of combustion engines. Condition monitoring and fault diagnosis represent a valuable set of methods designed to ensure that the engine stays in good condition during its lifecycle, [7] and [13]. Diagnosis in the context of diesel engines is not new and various approaches have been proposed in the past years, however, recent technical and computational advances and environmental legislation have stimulated the development of more efficient and robust techniques. In addition, the number of electronic components such as sensors or actuators and the complexity of engine control units (ECUs) are steadily increasing. Meanwhile, most of the software running on the main ECU is responsible for condition monitoring of sensor signals, monitoring parameter ranges, detecting short/open circuits, and verifying control deviations. However, these kinds of condition monitoring systems (CMS) are not designed to detect and clearly identify different engine failures, sensor drifts and to predict developing failures, i.e. to asses degradation of certain components right in time. Especially the reliable detection and separation of engine malfunctions is of major importance in various fields of industry in order to predict and to plan maintenance intervals. Diesel engines usually consist of a fuel injection system, pistons, rings, liners, an inlet and exhaust system, heat exchangers, a lubrication system, bearings and an ECU. For the design of an efficient CMS it is essential to know as much as possible about the underlying thermodynamical processes and possible faults and malfunctions. This information can be seen as a-priori knowledge and can be used to increase the robustness of fault detection algorithms. In the following, common diesel engine faults and fault mechanisms, and their causes are listed.…