Test and Identification Analysis of Wear Response Signal of Contact Interface of Rotary Seal-Reference-Cited by-同舟云学术

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Test and Identification Analysis of Wear Response Signal of Contact Interface of Rotary Seal

Published:2024-07-30 Issue:3 Volume:72 Page:
ISSN:1023-8883
Container-title:Tribology Letters
language:en
Short-container-title:Tribol Lett

Author:

Lu Junjie,Zheng Shize,Zhang Xuechang,Hou Yaochun

Funder

Ningbo Natural Science Foundation

Basic Public Welfare Research Program of Zhejiang Province

National Natural Science Foundation of China

Ningbo Science and Technology Innovation Major Project

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11249-024-01902-z.pdf

Reference25 articles.

1. Zhu, J.M., Zhan, H., Zhang, T.C., Wang, J.: Tool wear state recoanition based on cutting AE signal measurement. Acta Metrol. Sin. 36, 268–272 (2015). https://doi.org/10.3969/j.issn.1000-1158.2015.03.10

2. Li, F., Tian, B., Shi, J.F., Ran, J.Y.: Effect of lubrication conditions on tribological behavior of friction pairs of soybean and stainless steel. Lubr. Eng. (0254-0150) (2023). https://doi.org/10.3969/j.issn.0254-0150.2023.02.017

3. Senthil, S.M., Parameshwaran, R., Nathan, S.R., et al.: Non-destructive testing and evaluation of friction stir welded AA6063 circularly butted pipes. Russ. J. Nondestruct. Test. 55, 957–966 (2019). https://doi.org/10.1134/S1061830919120106

4. Zhou, X.Y., Yu, T.Y., Wang, G.Z., Guo, R.Y., Fu, Y.X., Sun, Y.Z., Chen, M.J.: Tool wear classification based on convolutional neural network and time series images during high precision turning of copper. Wear (2023). https://doi.org/10.1016/j.wear.2023.204692

5. Feng, K., Borghesani, P., Smith, W.A., Randall, R.B., Chin, Z.Y., Ren, J.Z., Peng, Z.: Vibration-based updating of wear prediction for spur gears. Wear 426, 1410–1415 (2019). https://doi.org/10.1016/j.wear.2019.01.017

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