Optical-Ultrasonic Heterogeneous Sensor Based on Soft-Computing Models
| Autor: | Marcia Muller, Cesar Yutaka Ofuchi, Lúcia Valéria Ramos de Arruda, Flávio Neves, José Luís Fabris, Rafael Jose Daciuk, Gustavo Rafael Collere Possetti, Galileu G. Terada |
|---|---|
| Rok vydání: | 2015 |
| Předmět: | |
| Zdroj: | IEEE Transactions on Instrumentation and Measurement. 64:2338-2346 |
| ISSN: | 1557-9662 0018-9456 |
| DOI: | 10.1109/tim.2015.2415071 |
| Popis: | A heterogeneous sensor system to determine the ethanol concentration in ethanol–water solution is demonstrated. The system consists of an optical-fiber refractometric transducer based on a long-period grating and a pair of ultrasonic transducers in transmission–reception mode, connected to a stand-alone electronic board for data acquisition, storage, and signal preprocessing. To implement a coherent sensor fusion from both measurement techniques, two soft computing methods (artificial neural network model and neuro-fuzzy model) are studied. A comparative analysis of these models was carried out based on the measured data. The best performance was obtained with the neural-network-based model. This model showed that it was able to correlate the responses of the optical-fiber transducer and the ultrasound system with the ethanol–water concentration. The final performance of the heterogeneous system is better within the whole range of concentrations, even if compared with the best performance of the individual sensors for limited ranges. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|