Ethylene compressor monitoring using model-based PCA

By Y. Rotem, A. Wachs, D. Lewin. 2000

49 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/306b922c2dee80a2c1914207c266517b5d6b5bb3

How researchers see this paper

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

In Analytical Chemistry

1. Manabu Kano
2. Bogdan Gabrys
3. Yoshiaki Nakagawa
4. Sibylle Strandt
5. Petr Kadlec

In Control and Systems Engineering

1. Manabu Kano
2. Bogdan Gabrys
3. Yoshiaki Nakagawa
4. Sibylle Strandt
5. Petr Kadlec
6. Okyay Kaynak
7. Shen Yin

In Statistics and Probability

1. Manabu Kano
2. Bogdan Gabrys
3. Yoshiaki Nakagawa
4. Sibylle Strandt
5. Petr Kadlec

Citations in the corpus

• Data-driven Soft Sensors in the process industry (2009, methodology): “Among them are the Model-Based PCA Rotem et al. (2000) and the Non-Linear PCA (Dong and McAvoy, 1996).”
• Data-based process monitoring, process control, and quality improvement: Recent developments and applications in steel industry (2008, methodology): “…for monitoring signals at several different frequency ranges (Bakshi, 1998), model-based PCA for integrating a first-principle model with PCA (Rotem et al., 2000), moving PCA that monitors changes in directions of principal components (Kano et al., 2001), a method called DISSIM that is based…”