A wavelet-based algorithm without a priori knowledge of noise level for gross errors detection
Publikation: Beiträge in Sammelwerken › Aufsätze in Sammelwerken › Forschung › begutachtet
Authors
This paper deals with Gross Error Detection using a signal-based approach and proposes an algorithm to be applied in industrial processes. The developed algorithm is used in some industrial software platforms to detect sensor outliers. A validation of this algorithm through computer simulations is shown. At the end of the paper, results using real sensor measurements from industrial processes are presented.
| Originalsprache | Englisch |
|---|---|
| Titel | Advances in Intelligent Systems |
| Herausgeber | Ford Lumban Gaol, Zenon Chaczko, Kiyota Hashimoto, Tokoro Matsuo, William Grosky |
| Anzahl der Seiten | 8 |
| Erscheinungsort | Southampton (UK) |
| Verlag | WIT Press |
| Erscheinungsdatum | 2014 |
| Seiten | 9-16 |
| ISBN (Print) | 978-184564869-5 |
| ISBN (elektronisch) | 978-1-84564-870-1 |
| DOIs | |
| Publikationsstatus | Erschienen - 2014 |
- Ingenieurwissenschaften