Tribologists often rely on triboexperiments to investigate factors that affect a tribosystem.The inherent dynamic behavior of the respective tribometer setups and its effect on data interpretation remain often unknown...Tribologists often rely on triboexperiments to investigate factors that affect a tribosystem.The inherent dynamic behavior of the respective tribometer setups and its effect on data interpretation remain often unknown.In this study,a comprehensive analysis of sensor data obtained from lubricated and dry triboexperiments is performed.Data are generated on a pin-on-disc test rig with a silicon nitride ball on a steel disc contact with a rotation frequency of~3 Hz.High-speed acquisition of sensor data up to 5 kHz is performed to resolve changes in the data within individual cycles.The characteristic frequencies of the system and their temporal evolution are determined via time--frequency analysis,which reveals periodic patterns in the sensor data.Cycle-based data evaluation allows the detection of localized events and changes during an operation and considerably reduces the apparent measurement uncertainty,as compared with an unreduced dataset.The data analysis and visualization routines presented herein may serve as a prototype for further application to tribometer setups.展开更多
基金This work was funded by the Austrian COMET Program(Project InTribology,No.872176)via the Austrian Research Promotion Agency(FFG)and the Provinces of Niederosterreich and Vorarlberg,and has been carried out within the Austrian Excellence Centre of Tribology(AC2T research GmbH).
文摘Tribologists often rely on triboexperiments to investigate factors that affect a tribosystem.The inherent dynamic behavior of the respective tribometer setups and its effect on data interpretation remain often unknown.In this study,a comprehensive analysis of sensor data obtained from lubricated and dry triboexperiments is performed.Data are generated on a pin-on-disc test rig with a silicon nitride ball on a steel disc contact with a rotation frequency of~3 Hz.High-speed acquisition of sensor data up to 5 kHz is performed to resolve changes in the data within individual cycles.The characteristic frequencies of the system and their temporal evolution are determined via time--frequency analysis,which reveals periodic patterns in the sensor data.Cycle-based data evaluation allows the detection of localized events and changes during an operation and considerably reduces the apparent measurement uncertainty,as compared with an unreduced dataset.The data analysis and visualization routines presented herein may serve as a prototype for further application to tribometer setups.
