DESAIN DETEKTOR JENIS GAS DENGAN GELOMBANG ULTRASONIK DAN JARINGAN SYARAF TIRUAN
<b></i>Abstract :</b><i><p align=\"justify\"> <br /> ABSTRACT <br /> A device has designed for detecting kinds of gas. It used ultrasonic wave that passing through the gas. By AT89C51 microcontroller is measured traveling time and output voltage...
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id-itb.:52742006-06-15T11:51:48ZDESAIN DETEKTOR JENIS GAS DENGAN GELOMBANG ULTRASONIK DAN JARINGAN SYARAF TIRUAN Nyoman Sudiana (NIM 20200501), I Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/5274 <b></i>Abstract :</b><i><p align=\"justify\"> <br /> ABSTRACT <br /> A device has designed for detecting kinds of gas. It used ultrasonic wave that passing through the gas. By AT89C51 microcontroller is measured traveling time and output voltage of ultrasonic sensor after ultrasonic wave passing through the gases for each temperature increasing. Than the result compared to data of teoretical calculation. The quantities of traveling time after converted to wave velocity (v) , output voltage (Vow) and temperature (T) are used as input of neural network. The using backpropagation algorithm with three layers architecture and the numbers of neuron for each layer are 15, 30 and 3. After learning we got from 70 tested pattern 90,2 % identified and 9,8% unidentified . In this research we use 7 kinds of gas i.e. : Air, Argon, 02, CO2, H2, N2, and Smoke. <br /> text |
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<b></i>Abstract :</b><i><p align=\"justify\"> <br />
ABSTRACT <br />
A device has designed for detecting kinds of gas. It used ultrasonic wave that passing through the gas. By AT89C51 microcontroller is measured traveling time and output voltage of ultrasonic sensor after ultrasonic wave passing through the gases for each temperature increasing. Than the result compared to data of teoretical calculation. The quantities of traveling time after converted to wave velocity (v) , output voltage (Vow) and temperature (T) are used as input of neural network. The using backpropagation algorithm with three layers architecture and the numbers of neuron for each layer are 15, 30 and 3. After learning we got from 70 tested pattern 90,2 % identified and 9,8% unidentified . In this research we use 7 kinds of gas i.e. : Air, Argon, 02, CO2, H2, N2, and Smoke. <br />
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| format |
Theses |
| author |
Nyoman Sudiana (NIM 20200501), I |
| spellingShingle |
Nyoman Sudiana (NIM 20200501), I DESAIN DETEKTOR JENIS GAS DENGAN GELOMBANG ULTRASONIK DAN JARINGAN SYARAF TIRUAN |
| author_facet |
Nyoman Sudiana (NIM 20200501), I |
| author_sort |
Nyoman Sudiana (NIM 20200501), I |
| title |
DESAIN DETEKTOR JENIS GAS DENGAN GELOMBANG ULTRASONIK DAN JARINGAN SYARAF TIRUAN |
| title_short |
DESAIN DETEKTOR JENIS GAS DENGAN GELOMBANG ULTRASONIK DAN JARINGAN SYARAF TIRUAN |
| title_full |
DESAIN DETEKTOR JENIS GAS DENGAN GELOMBANG ULTRASONIK DAN JARINGAN SYARAF TIRUAN |
| title_fullStr |
DESAIN DETEKTOR JENIS GAS DENGAN GELOMBANG ULTRASONIK DAN JARINGAN SYARAF TIRUAN |
| title_full_unstemmed |
DESAIN DETEKTOR JENIS GAS DENGAN GELOMBANG ULTRASONIK DAN JARINGAN SYARAF TIRUAN |
| title_sort |
desain detektor jenis gas dengan gelombang ultrasonik dan jaringan syaraf tiruan |
| url |
https://digilib.itb.ac.id/gdl/view/5274 |
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