Abstract
Normal displacements are measured by sensors on current wear apparatus to represent wear depth. In practice, measured normal displacements are interfered by actual working condition factors such as thermal expansion and mechanical vibration, resulting in a puzzle of relationship between wear depth and measured normal displacements. This paper provides a characterization method of such relationship under mixed lubrication condition. By introducing Taylor expansion to measured normal displacements, Archard model and dissipation model are unified as the first order of such Taylor expansion. A non-integer fractal order D is determined to give the function relationship between wear depth and measured normal displacements. The fractal order D is verified to be a characterization parameter of measurement quality based on a series of wear experiments. Further analysis proves that the fractal order D is capable to be a prediction parameter of wear depth, the prediction errors are below 15%. These works are expected to make contributions for online wear monitoring in engineering.
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Funding
This research was funded by National Natural Science Foundation of China (51975315) and National Science and Technology Major Project (2019-IV-0020–0088).
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Li, H., Liu, Y., Liao, H. (2024). A Wear Depth Characterization Method Based on Fractal Order Taylor Expansion of Measured Normal Displacements. In: Okada, M. (eds) Advances in Mechanism and Machine Science. IFToMM WC 2023. Mechanisms and Machine Science, vol 149. Springer, Cham. https://doi.org/10.1007/978-3-031-45709-8_82
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DOI: https://doi.org/10.1007/978-3-031-45709-8_82
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