Convolutional Neural Networks—Long Short-Term Memory—Attention: A Novel Model for Wear State Prediction Based on Oil Monitoring Data

Convolutional Neural Networks—Long Short-Term Memory—Attention: A Novel Model for Wear State Prediction Based on Oil Monitoring Data

Wear state prediction based on oil monitoring technology enables the early identification of potential wear and failure risks of friction pairs, facilitating optimized equipment maintenance and extended service life. However, the complexity of lubricating oil monitoring data often poses challenges i...

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Bibliographic Details
Main Authors:	Ying Du, Hui Wei, Tao Shao, Shishuai Chen, Jianlei Wang, Chunguo Zhou, Yanchao Zhang
Format:	Article
Language:	English
Published:	MDPI AG 2025-07-01
Series:	Lubricants
Subjects:	lubricating oil convolutional neural networks (CNN) long short-term memory (LSTM) wear state prediction
Online Access:	https://www.mdpi.com/2075-4442/13/7/306
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