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Journal of Medical Signals and Sensors، جلد ۲، شماره ۴، صفحات ۰-۰
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Extrapolation of Calibration Curve of Hot-Wire Spirometer Using a Novel Neural Network Based Approach |
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| چکیده انگلیسی مقاله |
Hot-wire spirometer uses a constant temperature anemometer (CTA) for its operation. The working principle of CTA, used for the measurement of fluid velocity and flow turbulence, is based on convective heat transfer from a hot-wire sensor to a fluid being measured. The calibration curve of a CTA is nonlinear and cannot be easily extrapolated beyond its calibration range. Therefore, a method for extrapolation of calibration curve will be of great practical application. In this paper, a novel approach based on the conventional neural network method has been proposed to extrapolate CTA calibration curve for measurement range of 0.7-30 m/sec. Results show that using this approach, the standard deviation for the extrapolation of the CTA calibration curve beyond its upper limit is about -0.5%, which is acceptable in most cases. Moreover, the application of this approach for the extrapolation of the CTA calibration curve below its lower limit produces standard deviation of about 4.5%, which is acceptable in spirometery applications. Finally the standard deviation on the whole measurement range (0.7-30 m/s) is about 1.5% |
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| کلیدواژه‌های انگلیسی مقاله |
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| نویسندگان مقاله |
محمد علی اردکانی | mohammad ali ardekani
وحید رضا نفیسی | vahid reza nafisi
فواد فرحانی | foad farhani
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| نشانی اینترنتی |
http://www.jmss.mui.ac.ir/index.php/jmss/article/view/101 |
| فایل مقاله |
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| کد مقاله (doi) |
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| زبان مقاله منتشر شده |
en |
| موضوعات مقاله منتشر شده |
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| نوع مقاله منتشر شده |
Original Articles |
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