Fault Detection and Identification for Nonlinear Process Based on Inertia-Based KEPCA and a New Combined Monitoring Index
| العنوان: | Fault Detection and Identification for Nonlinear Process Based on Inertia-Based KEPCA and a New Combined Monitoring Index |
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| المؤلفون: | El Hassan Sbai, Loubna El Fattahi |
| المصدر: | Journal of Electrical and Computer Engineering, Vol 2021 (2021) |
| بيانات النشر: | Hindawi Limited, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Computer engineering. Computer hardware, Article Subject, General Computer Science, Computer science, media_common.quotation_subject, Gaussian, Feature vector, Kernel density estimation, 02 engineering and technology, Inertia, 01 natural sciences, Fault detection and isolation, TK7885-7895, 010104 statistics & probability, symbols.namesake, 020401 chemical engineering, Entropy (information theory), 0204 chemical engineering, 0101 mathematics, Electrical and Electronic Engineering, media_common, Estimator, Kernel (statistics), Signal Processing, symbols, Algorithm |
| الوصف: | In the present study, we introduce a new approach for the nonlinear monitoring process based on kernel entropy principal component analysis (KEPCA) and the notion of inertia. KEPCA plays double roles. First, it reduces the data in the high-dimensional space. Second, it constructs the model. Before data reduction, KEPCA transforms input data into high-dimensional feature space based on a nonlinear kernel function and automatically determines the number of principal components (PCs) based on the computation of the inertia. The retained PCs express the maximum inertia entropy of data in the feature space. Then, we use the Parzen window estimator to compute the upper control limit (UCL) for inertia-based KEPCA instead of the Gaussian assumption. Our second contribution concerns a new combined index based on the monitoring indices T2 and SPE in order to simplify the detection task of the fault and prevent any confusion. The proposed approaches have been applied to process fault detection and diagnosis for the well-known benchmark Tennessee Eastman process (TE). Results were performing. |
| وصف الملف: | text/xhtml |
| تدمد: | 2090-0155 2090-0147 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9210ce76be9d9875fe12d4505119054 https://doi.org/10.1155/2021/5320241 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....a9210ce76be9d9875fe12d4505119054 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 20900155 20900147 |
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