Passive sensors that vary its impedance per measured parameter may be used with surface acoustic wave (SAW) reflective transducers (SRT) for wireless acquisition of the measurand. The device is composed of two transducers, where one, which may be attached to an antenna, is used to launch the wave within the device substrate, and the other is where the sensor load is attached to. The latter is able to reflect the incident wave. How much power is reflected is determined by the attached sensor load. Amplitude variations as well as peak frequency variations of the SRT reflectivity response are explored in this thesis. SAW passive temperature sensors with an orthogonal frequency coded (OFC) time response were previously investigated and prove to be ideal for use in harsh environments. Each sensor is distinguishable from the other due to the OFC code embedded within its time response. However, this coding technique poses a difficulty in designing antennas for the sensor due to its inherently wide bandwidth, and capacitive, non-uniform input impedance. This work covers antenna design and testing for the 250MHz wireless temperature acquisition prototype with a 28% fractional bandwidth, and for the 912MHz system which has 10% fractional bandwidth. Apart from the tag, antennas for the transmitter and receiver were designed for 50 Ohm matching with the required bandwidth maintained. Wireless temperature acquisition runs for the 250MHz prototype were successfully performed and show good agreement with measurements made by a thermocouple. Since a transceiver for the 912MHz system is not complete, the performance of the antennas was gauged by observing the signal transmitted wirelessly by the SAW tag and by comparing this with the sensor time response measured directly by a vector network analyzer.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-5179 |
| Date | 01 January 2009 |
| Creators | Santos, Bianca Maria |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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