This paper presents a method to recognize open set samples without changing the neural network architecture, the training process, nor the trained models. In ...
The main contribution of this paper is the proposal of a novel open set recognition method for machinery fault diagnosis in the context of deep learning and ...
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The proposed method involves training a classifier to rate the similarity between unknown data and the stored knowledge, and using this similarity rating to ...
Mar 1, 2024 · As an Open Set Recognition (OSR) problem, nuclear power plant fault diagnosis requires not only the correct classification of known faults, but ...
Feb 14, 2023 · The results show that the method is effective in open set fault diagnosis and superior to the common domain adaptation methods.
A novel approach is proposed that focuses on addressing two open-set diagnosis issues simultaneously. A multiple metric weighting learning strategy
Open Set Recognition Methods for Fault Diagnosis: A Review
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A high classification accuracy of training set and test set is sustained and over-fitting and under-fitting are avoided. Experiment results indicate that this ...
sign in. Inproceedings,. Open Set Recognition for Machinery Fault Diagnosis. J. Xu, M. Kovatsch, and S. Lucia. INDIN, page 1-7. IEEE, (2021 ). 1. 1. Meta data.
May 4, 2024 · A novel UCRAN approach is proposed for open set domain adaptation fault diagnosis of rotating machinery, which can accurately diagnose known ...
However, a more realistic scenario is usually open and non-stationary such as driverless, fault/medical diagnosis, etc., where unseen situations can emerge ...