4.7 Article

Investigation on the relationship between macropits and wear particles in a gear fatigue process

期刊

WEAR
卷 484, 期 -, 页码 -

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.wear.2021.203724

关键词

Gear wear; Fatigue pitting; Surface replication; Wear debris

资金

  1. Australian Government through the Australian Research Council [DP160103501]

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The study characterized macropits on gear moulds and sampled wear particles using optical microscopy, revealing that the concentration of wear particles had a similar trend to pitted area growth, yet with a delay. This behavior was also reflected in four non-dimensional numerical features characterizing the geometry of particles and pits.
Macropitting is one of the most common gear wear mechanisms, and monitoring its initiation and propagation is critical to ensure the safe operation of gearboxes. Wear debris analysis (WDA) is widely used to monitor and diagnose gear macropitting and its diagnostic capability relies on good understanding of the relationship between wear particle features and those of actual gear macropits. However, the study on this relationship has been impeded by on-going challenges in characterising gear macropits during the wear process. As a result, detailed experimental data of macropits and the quantitative relationships between wear particles and macropits evolving in the fatigue process are scarce. In order to address the above issues, this study examines macropits and wear particles generated on gear surfaces and their evolution in a gear fatigue process through employing a moulding method to obtain 38 batches of gear teeth moulds in the wear process. 2D characterisations of macropits on the moulds and sampled wear particles were conducted using optical microscopy. Qualitative and quantitative relationships between different features of macropits and wear particles were investigated. Results showed the concentration of wear particles had a similar trend to pitted area growth, yet with a delay. This behaviour was also found in 4 non-dimensional numerical features characterising the geometry of particles and pits. The results of this study provide further insight in the evolution of the fatigue process of gears and can assist in its monitoring.

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