IFRN: Insensitive feature removal network for zero-shot mechanical fault diagnosis across fault severity

Author:

Liu Ziqi,Yang RuiORCID,Liu WeiboORCID,Liu Xiaohui

Funder

Jiangsu Provincial Qinglan Project

Science and Technology Program of Suzhou

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference60 articles.

1. Graph-based semi-supervised random forest for rotating machinery gearbox fault diagnosis;Chen;Control Eng. Pract.,2021

2. A random forest and model-based hybrid method of fault diagnosis for satellite attitude control systems;Chen;IEEE Trans. Instrum. Meas.,2023

3. Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems;Yang,2022

4. Neural-network-based set-membership fault estimation for 2-D systems under encoding–decoding mechanism;Zhu;IEEE Trans. Neural Netw. Learn. Syst.,2023

5. A survey on state estimation of complex dynamical networks;Hu;Internat. J. Systems Sci.,2021

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