The measurement of acoustic emission data in experiments reveals informative details about the tribological contact. The required recording rate for conclusive datasets ranges up to several megahertz. Typically, this results in very large datasets for long-term measurements. This in return has the consequence, that acoustic emissions are mostly acquired at predefined cyclic time intervals, which leads to many blind spots. The following work shows methods for effective postprocessing and a feature based data acquisition method. Additionally, a two stage wear mechanism for bearings was found by the described method and could be substantiated by a numerical simulation.

Acoustic emissions from tribological contacts have become an interesting field of science in recent years. This study focuses on predicting the friction power of a given system (lubricated ring-on-disc geometry), independently of the used sliding material and lubricant, from the acoustic emissions emitted from the system. The low-frequency (1 Hz), continuously measured RMS value of the acoustic data is combined with short-duration and high-frequency (850 kHz) signal data in form of the power spectra and hit rate with three prominence levels. The classification system then predicts the friction power of the test system continuously over the whole test time. Prediction is achieved by four different machine learning methods (tree-type, support vector machine, K-nearest-neighbor, neural network) trained with data from 54 ring-on-disc tests with high variation in material and oil combinations. The method allows for the quantifiable and step-free prediction of absolute values of friction power with accuracy of 97.6% on unseen data, with a weighted K-nearest-neighbor classifier, at any point in time during an experiment. The system reacts well to rapid changes in friction conditions due to changes in load and temperature. The study shows the high information degree of acoustic emissions, concerning the actual friction mechanisms occurring and the quantitative, and not only qualitative, information that one can gain about a tribological system by analyzing them.

The main objective of the present paper is the validation of new methods concerning experimental investigations of journal bearings under ordinary and extraordinary operational conditions. Derived results should facilitate the determination of damage mechanisms and a qualitative ranking for a prospective coating development. Prior investigated scenarios like start/stop and emergency running behavior were extended by starved and unlubricated experiments for an aircraft application. Focusing on thermal stability and reproducibility, two new subscale test strategies were developed derived from generalized operational conditions of journal bearings. For an improved ex-situ wear measurement of bearing shells, a new device was developed successfully. The results showed that the newly designed test methodologies are suitable to investigate unlubricated coatings leading to conclusive and repetitive results.

Conventional test rigs for fatigue testing (servo hydraulic, resonant test systems) are usually working up to 100 Hz. For the characterization of VHCF (very high cycle fatigue) phenomena up to 10⁹ load cycles should be proved, this would lead to exorbitant testing period behavior. The desire for material testing at higher frequencies is obvious. In the design process of high frequency test devices, it is essential to have detailed knowledge of the resonant behavior for the planned system. Finite- Element calculations are a widespread tool for frequency predictions tough they are time consuming. The aim of this work is the development of an accurate analytical calculation routine for resonant frequency identification. Resonant frequencies strongly depend on the stiffness of the system; therefore, the focus is laid on the calculation of the stiffness. A good accordance between measured and calculated resonant frequencies has been observed.

Alternative fuels such as hydrogen, ammonia, and methanol are becoming increasingly important to meet global climate goals. However, their impact on mechanical and tribological properties is not yet fully understood. This creates a pressing need for the development of novel experimental methods to establish reliable design criteria for components exposed to these fuels. To date, hydrogen embrittlement has been the most extensively studied in this context.