Multivariate Detection of Transient Disturbances for Uni- and Multirate Systems
| Autor: | James R. Ottewill, Inês M. Cecílio, Harald Fretheim, Nina F. Thornhill |
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| Přispěvatelé: | Commission of the European Communities |
| Rok vydání: | 2015 |
| Předmět: |
Technology
REPRESENTATION Engineering Multivariate statistics MODELS Context (language use) industrial process Fault detection and isolation Automation & Control Systems multivariate 0102 Applied Mathematics Singular value decomposition Electrical and Electronic Engineering Time series multirate Science & Technology IDENTIFICATION business.industry 0906 Electrical And Electronic Engineering Univariate Engineering Electrical & Electronic Control engineering MULTISCALE PCA Electric machines fault detection STATE Industrial Engineering & Automation Control and Systems Engineering PROCESS TRENDS Data analysis singular value decomposition (SVD) Transient (oscillation) FAULT-DIAGNOSIS business Algorithm nearest neighbors (NNs) |
| Zdroj: | IEEE Transactions on Control Systems Technology. 23:1477-1493 |
| ISSN: | 1558-0865 1063-6536 |
| Popis: | This paper presents a method to detect transient disturbances in a multivariate context, and an extension of that method to handle multirate systems. Both methods are based on a time series analysis technique known as nearest neighbors, and on multivariate statistics implemented as a singular value decomposition. The motivation for these developments is that there is an increasing industrial requirement for the analysis of data sets comprising measurements from industrial processes together with their associated electrical and mechanical equipment. These systems are increasingly affected by transient disturbances, and their measurements are commonly sampled at different rates. This paper demonstrates superior results with the multivariate method in comparison with the univariate approach, and with the multirate method in comparison to a unirate method, for which the fast-sampled measurements had to be downsampled. The method is demonstrated on experimental and industrial case studies. |
| Databáze: | OpenAIRE |
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