Fault diagnosis of Tennessee Eastman process with multi-scale PCA and ANFIS
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2013/01/01
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Indian UGC (journal)
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Refrences43
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Citations117
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C.K. Lau
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Kaushik Ghosh
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M.A. Hussain
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C.R. Che Hassan
Journal Categories
Science
Chemistry
Science
Chemistry
Analytical chemistry
Science
Mathematics
Science
Mathematics
Instruments and machines
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Science
Mathematics
Probabilities
Mathematical statistics
Technology
Mechanical engineering and machinery
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Parallel Analysis: a method for determining significant principal components | Journal of Vegetation Science |
| 232 | 1995 |
| Designing a hierarchical neural network based on fuzzy clustering for fault diagnosis of the Tennessee–Eastman process | Applied Soft Computing |
| 81 | 2011 |
| State-space independent component analysis for nonlinear dynamic process monitoring | Chemometrics and Intelligent Laboratory Systems |
| 43 | 2010 |
| Fault diagnosis of the polypropylene production process (UNIPOL PP) using ANFIS | ISA Transactions |
| 15 | 2010 |
| Incipient gear box fault diagnosis using discrete wavelet transform (DWT) for feature extraction and classification using artificial neural network (ANN) | Expert Systems with Applications |
| 205 | 2010 |
Refrences Analysis
The category
Technology: Chemical technology: Chemical engineering 16
is the most frequently represented among the references in this article. It primarily includes studies from AIChE Journal and Chemometrics and Intelligent Laboratory Systems. The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Application of time‐space neighborhood standardization technology to complex multi‐stage process fault detection | Journal of Chemometrics |
| 2024 | |
| Development of a CNN-based fault detection system for a real water injection centrifugal pump | Expert Systems with Applications |
| 1 | 2024 |
Data-Driven Process Monitoring and Fault Diagnosis: A Comprehensive Survey | Processes |
| 2024 | |
| SensorSCAN: Self-supervised learning and deep clustering for fault diagnosis in chemical processes | Artificial Intelligence |
| 1 | 2023 |
| Identification of unknown faults in chemical processes using few-shot learning | Measurement |
| 1 | 2023 |
Citations Analysis
The category
Science: Chemistry 48
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Fault detection and classification in chemical processes using NMFSC and structural SVMs and was published in 2013. The most recent citation comes from a 2024 study titled Application of time‐space neighborhood standardization technology to complex multi‐stage process fault detection. This article reached its peak citation in 2022, with 15 citations. It has been cited in 56 different journals, 17% of which are open access. Among related journals, the Industrial & Engineering Chemistry Research cited this research the most, with 8 citations. The chart below illustrates the annual citation trends for this article.