Methodology and Experimental Verification for Predicting the Remaining Useful Life of Milling Cutters Based on Hybrid CNN-LSTM-Attention-PSA

Authors: Mengge Zhu, Ji Zhang, Lingfan Bu, Sen Nie, Yu Bai, Yueqi Zhao, Ning Mei

Source: Machines, Vol 12, Iss 11, p 752 (2024)

Subject Terms: remaining useful life, CNN-LSTM-Attention-PSA, multi-channel feature extraction, milling cutter wear, Mechanical engineering and machinery, TJ1-1570

File Description: electronic resource

Relation: https://www.mdpi.com/2075-1702/12/11/752; https://doaj.org/toc/2075-1702

Access URL: https://doaj.org/article/21b06437be8c452fb109cf092793d016