Abstract
Four optical fiber sensors have been grouped in an array which is able to distinguish odors of different drinks. The sensing materials employed have been deposited onto optical fibers following the electrostatic self assembly method. The responses have been characterized in terms of reflected optical power; more specifically, the dynamic range and the recovery of each device have been used to discriminate between the samples. Data mining techniques based on the combination of principal component analysis and artificial neural networks are performed. The final system is trained to distinguish between grape juice, wine, and vinegar by using a set of one hundred samples of each one. Furthermore, the array can be located at up to 6 km away from the optical header, offering the possibility of in situ measurements.
| Original language | English |
|---|---|
| Article number | 6280589 |
| Pages (from-to) | 3156-3162 |
| Number of pages | 7 |
| Journal | IEEE Sensors Journal |
| Volume | 12 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 2012 |
| Externally published | Yes |
Keywords
- Array signal processing
- chemical sensors
- multiplexing
- optical fiber sensors
- remote sensing
- wavelength division