Process trend analysis using wavelet-based de-noising
| Autor: | Amid Bakhtazad, Jose A. Romagnoli, Ahmet Palazoglu |
|---|---|
| Rok vydání: | 2000 |
| Předmět: |
Engineering
Series (mathematics) business.industry Estimation theory Applied Mathematics Fuzzy set Process (computing) Wavelet transform Pattern recognition computer.software_genre Computer Science Applications Trend analysis Wavelet Control and Systems Engineering Data mining Artificial intelligence Electrical and Electronic Engineering business Hidden Markov model computer |
| Zdroj: | Control Engineering Practice. 8:657-663 |
| ISSN: | 0967-0661 |
| DOI: | 10.1016/s0967-0661(99)00197-5 |
| Popis: | This paper presents a strategy to represent and classify process data for detection of abnormal operating conditions, focusing on a novel approach in de-noising of process data using wavelet coeffiCIents. A case study features two Continuous Stirred Tank Reactors (CSTRs) in series that uses an intermediate mixer for the second feed. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect