Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems

By Steven X. Ding. 2014

485 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/a89854cdd95890ffa1aca554a83d5628e9c7639b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Bin Jiang
2. Hongtian Chen
3. Zhiqiang Ge
4. Biao Huang
5. Steven X. Ding
6. Zhihuan Song
7. Zhiwei Gao
8. Shen Yin

Citations in the corpus

• Canonical correlation analysis-based fault detection methods with application to alumina evaporation process (2016, unknown): “The reader is referred to (Russell, Chiang, & Braatz, 2000; Venkatasubramanian, Rengaswamy, Kavuri, & Yin, 2003; Kano & Nakagawa, 2008; Qin, 2012; Yin, Ding, Haghani, Hao, & Zhang, 2012; Ding, 2014) for a comprehensive literature study.”
• Data Mining and Analytics in the Process Industry: The Role of Machine Learning (2017, background): “detailed state-of-the-art of the research on this topic [1]–[8], [12]–[16].”
• A Review of Fault Detection and Diagnosis for the Traction System in High-Speed Trains (2020, methodology): “Typically, principal component analysis (PCA), partial least squares (PLS), and canonical correlation analysis (CCA) are the fundamental methods in feature extraction [42], [51], [57],”