Reconstruction-based contribution for process monitoring

By Carlos F. Alcala, S. Qin. at - Automatisierungstechnik, 2009

553 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/564cb7955b42e2021336c0ef362082477419e983

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. S. Qin
2. Bin Jiang
3. Hongtian Chen
4. Steven X. Ding
5. Haitao Zhao
6. Bo Jin
7. Shaoyuan Sun
8. Qingchao Jiang

In Control and Systems Engineering

1. S. Qin
2. Steven X. Ding
3. Bin Jiang
4. Hongtian Chen
5. Zhiqiang Ge
6. Steven L. Brunton
7. J. Nathan Kutz
8. Joshua L. Proctor

In Statistics and Probability

1. S. Qin
2. Qingchao Jiang
3. Xue-feng Yan
4. Steven X. Ding
5. Carlos F. Alcala
6. Bin Jiang
7. Hongtian Chen

Citations in the corpus

• Survey on data-driven industrial process monitoring and diagnosis (2012, methodology): “To answer this question it is shown in Alcala and Qin (2009) that even if a fault sample x coincides with the jth variable direction nj, there is no guarantee that cSPE j P c SPE i for i – j, but we always have RBC j P RBC SPE i for i – j. This result indicates that the traditional contribution plot”