Research on Classification and Identification of Crack Faults in Steam Turbine Blades Based on Supervised Contrastive Learning

Steam turbine blades may crack, break, or suffer other failures due to high temperatures, high pressures, and high-speed rotation, which seriously threatens the safety and reliability of the equipment. The signal characteristics of different fault types are slightly different, making it difficult to...

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Bibliographic Details
Main Authors: Qinglei Zhang, Laifeng Tang, Jiyun Qin, Jianguo Duan, Ying Zhou
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/26/11/956
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