Sensors Information Fusion System with Fault Detection Based on Multi-Manifold Regularization Neighborhood Preserving Embedding
Electrical drive systems play an increasingly important role in high-speed trains. The whole system is equipped with sensors that support complicated information fusion, which means the performance around this system ought to be monitored especially during incipient changes. In such situation, it is...
Main Authors: | Jianping Wu, Bin Jiang, Hongtian Chen, Jianwei Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-03-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/19/6/1440 |
Similar Items
-
Weighted Neighborhood Preserving Ensemble Embedding
by: Sumet Mehta, et al.
Published: (2019-02-01) -
Bilateral Two-Dimensional Neighborhood Preserving Discriminant Embedding for Face Recognition
by: Jiuzhen Liang, et al.
Published: (2017-01-01) -
Markov Chain Neighborhood Sparse Preserving Graph Embedding Based on Tensor Factorization for Batch Process Monitoring
by: Xiaoqiang Zhao, et al.
Published: (2021-01-01) -
Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding
by: Jing An, et al.
Published: (2021-01-01) -
Robust Manifold Embedding for Face Recognition
by: Zhonghua Liu, et al.
Published: (2020-01-01)