Fault Detection and Diagnosis in Industrial Systems

By Leo H. Chiang, E. L. Russell, Richard D. Braatz. 2001

1,138 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/5c5421de05f5fc1479c73031c961774efd93c2fd

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. S. Qin
2. Qingchao Jiang
3. Xue-feng Yan
4. Jin Jiang
5. Jianping Ma
6. Enrico Zio
7. Donghua Zhou
8. Sylvain Verron

Citations in the corpus

• Weighted kernel principal component analysis based on probability density estimation and moving window and its application in nonlinear chemical process monitoring (2013, methodology): “Themissed detection rates for each fault in the TE process using PCA [15], WPCA [30], KPCA [22], KICA [45], P-WKPCA, and PM-WKPCA are summarized in Table 1.”
• Pattern Matching in Historical Data (2002, neutral): “Jackson 1991 , Wang 1999 , and Chiang et al. 2001 describe the PCA methodology and its applications to a wide variety of processes.”
• Applications of fault detection and diagnosis methods in nuclear power plants: A review (2011, methodology): “Data-driven FDD methods and signal-based FDD methods have been extensively used in various industrials (Chiang et al., 2001) (Yue and Qin, 2001) (Venkatasubramanian et al.”
• Geometric properties of partial least squares for process monitoring (2010, background): “The TEP contains two blocks of variables: 12 manipulated variables and 41 measured variables (Chiang et al., 2001; Lee et al., 2004).”
• A data-driven fuzzy approach for predicting the remaining useful life in dynamic failure scenarios of a nuclear system (2010, methodology): “Approaches to prognostics can be categorized broadly into model-based and data-driven [Chiang et al., 2001].”
• Bridging data-driven and model-based approaches for process fault diagnosis and health monitoring: A review of researches and future challenges (2016, methodology): “According to Chiang et al. (2001) , the model-based approaches are not suitable for large-scale and complex systems and their performances depend on how good and precise the model is.”