Multi-source sensor data and worn surface topography for tribo-informatics research

Abstract

Real-time monitoring of the wear state of key components of mechanical equipment is one of the key engineering applications of tribology. It can be realized with the help of data-driven technology. In this study, the multiple-source sensor data and the surface topography of the disc specimen during the tribo-test were collected using the pin-on-disc test. The pin material was polyimide, and the disc material was titanium alloy. During the test, the surface topography of the disc specimen was collected by restarting multiple times for single pair of specimens. The data collected by the sensors of the tribometer itself include the applied normal load, the measured friction force, the calculated friction coefficient, the position of the pin, and the rotational speed of the disc. The data collected by the data acquisition platform include the vibration data in three directions, sound pressure, and audio data. The data collected by the white-light interferometer are the surface topography of the four worn areas on the disc. These data can be used to explore the trend of surface topography during the friction process and to verify the performance of different data-driven methods in studying the correlation between surface topography and multi-source sensor data.