Development of Wireless and Passive SAW Temperature Sensor with Very High Accuracy
A surface acoustic wave (SAW) temperature sensor with high accuracy was developed and wirelessly characterized in this work. The sensing chip with reflective delay line pattern was simulated using typical coupling of modes (COM) model and prepared by the standard photolithographic technique. Sharp r...
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| Published in | Applied sciences Vol. 11; no. 16; p. 7422 |
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| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
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MDPI AG
01.08.2021
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| Online Access | Get full text |
| ISSN | 2076-3417 2076-3417 |
| DOI | 10.3390/app11167422 |
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| Abstract | A surface acoustic wave (SAW) temperature sensor with high accuracy was developed and wirelessly characterized in this work. The sensing chip with reflective delay line pattern was simulated using typical coupling of modes (COM) model and prepared by the standard photolithographic technique. Sharp reflection peaks with high signal-to-noise (SNR) were observed from the developed sensing chip operating at 433 MHz. Referring to the frequency-stepped continuous wave (FSCW)-based transceiver, planar antennas, and the developed SAW chip, the wireless and passive temperature sensor system was built. Adaptive Least Mean Square (LMS) algorithm was used for the first time in the SAW sensor signal processing to significantly improve the system SNR, and the corresponding phase fluctuation is down to only 3°. High temperature sensitivity of 36.5 °C and very high accuracy of ±0.2 °C in the range of −30 °C∼100 °C were achieved successfully by wireless measurement. |
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| AbstractList | A surface acoustic wave (SAW) temperature sensor with high accuracy was developed and wirelessly characterized in this work. The sensing chip with reflective delay line pattern was simulated using typical coupling of modes (COM) model and prepared by the standard photolithographic technique. Sharp reflection peaks with high signal-to-noise (SNR) were observed from the developed sensing chip operating at 433 MHz. Referring to the frequency-stepped continuous wave (FSCW)-based transceiver, planar antennas, and the developed SAW chip, the wireless and passive temperature sensor system was built. Adaptive Least Mean Square (LMS) algorithm was used for the first time in the SAW sensor signal processing to significantly improve the system SNR, and the corresponding phase fluctuation is down to only 3 ° . High temperature sensitivity of 36.5 ° C and very high accuracy of ±0.2 ° C in the range of −30 ° C∼100 ° C were achieved successfully by wireless measurement. A surface acoustic wave (SAW) temperature sensor with high accuracy was developed and wirelessly characterized in this work. The sensing chip with reflective delay line pattern was simulated using typical coupling of modes (COM) model and prepared by the standard photolithographic technique. Sharp reflection peaks with high signal-to-noise (SNR) were observed from the developed sensing chip operating at 433 MHz. Referring to the frequency-stepped continuous wave (FSCW)-based transceiver, planar antennas, and the developed SAW chip, the wireless and passive temperature sensor system was built. Adaptive Least Mean Square (LMS) algorithm was used for the first time in the SAW sensor signal processing to significantly improve the system SNR, and the corresponding phase fluctuation is down to only 3°. High temperature sensitivity of 36.5 °C and very high accuracy of ±0.2 °C in the range of −30 °C∼100 °C were achieved successfully by wireless measurement. |
| Author | Cheng, Lina Zhai, Shoupei Xue, Xufeng Liu, Mengwei Gao, Xu Liang, Yong Wang, Wen Zhu, Jialiang Li, Zhuoyue |
| Author_xml | – sequence: 1 givenname: Xu surname: Gao fullname: Gao, Xu – sequence: 2 givenname: Lina surname: Cheng fullname: Cheng, Lina – sequence: 3 givenname: Xufeng surname: Xue fullname: Xue, Xufeng – sequence: 4 givenname: Shoupei surname: Zhai fullname: Zhai, Shoupei – sequence: 5 givenname: Yong surname: Liang fullname: Liang, Yong – sequence: 6 givenname: Wen surname: Wang fullname: Wang, Wen – sequence: 7 givenname: Mengwei surname: Liu fullname: Liu, Mengwei – sequence: 8 givenname: Jialiang surname: Zhu fullname: Zhu, Jialiang – sequence: 9 givenname: Zhuoyue surname: Li fullname: Li, Zhuoyue |
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| Cites_doi | 10.1016/j.sna.2015.01.028 10.1109/41.915404 10.1109/JSEN.2020.2977837 10.1109/ICCEA50009.2020.00115 10.1109/ULTSYM.1987.199024 10.3390/s20071959 10.3390/mi8100301 10.1109/ACCESS.2021.3065564 10.1109/JSEN.2014.2344972 10.1108/SR-03-2020-0061 10.1021/acssensors.0c00013 10.3390/s18020532 10.1088/0960-1317/17/3/014 10.1109/ULTSYM.2015.0460 10.1109/JSEN.2014.2335058 10.1016/j.sna.2006.10.018 10.1109/JMEMS.2016.2642580 10.1109/TUFFC.2008.840 10.1109/JSEN.2020.2990997 10.3390/s151229793 10.1109/FREQ.2006.275412 10.1007/978-3-662-04223-6 10.1109/JSEN.2015.2394776 10.1016/j.sna.2020.112015 |
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| Copyright | 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| SubjectTerms | Accuracy Algorithms Antennas Approximation high accuracy High temperature LMS Noise Receivers & amplifiers reflective delay line SAW temperature sensor Sensors Signal processing Simulation wireless and passive |
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| Title | Development of Wireless and Passive SAW Temperature Sensor with Very High Accuracy |
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