MEASURING PERCENTAGE OF BIODIESEL IN DIESEL FUEL USING ULTRASONIC WAVE

Biodiesel is one of the altenative diessel fuel. Biodiesel has some advantages and disadvantages. To overcome these disadvantages, biodiesel have to react to fossil diesel first. The percentage of biodiesel in diesel fuel is quite important as the indicator for quality of diesel fuel in applications...

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Main Author: SYAHNARIZA NAN BARENO (NIM : 13311034), FADYA
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/20090
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:20090
spelling id-itb.:200902017-09-27T11:05:16ZMEASURING PERCENTAGE OF BIODIESEL IN DIESEL FUEL USING ULTRASONIC WAVE SYAHNARIZA NAN BARENO (NIM : 13311034), FADYA Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/20090 Biodiesel is one of the altenative diessel fuel. Biodiesel has some advantages and disadvantages. To overcome these disadvantages, biodiesel have to react to fossil diesel first. The percentage of biodiesel in diesel fuel is quite important as the indicator for quality of diesel fuel in applications. To estimate the percentage of biodiesel in diesel fuel accurately, precisely, fast, and user friendly, in this study the ultrasonic based instrument is proposed. <br /> <br /> <br /> <br /> <br /> To perform ultrasonic measurement, two types of transducers placement were used. First, the distance between transmitter and receiver which had frequency in 2.25 MHz were 13,23 cm. Second, the distance between transmitter and receiver which had frequency in 2 MHz were 1.13 cm. The result of both designed ultrasonic measurement were time of flight ultrasonic wave. The longest distance obtained better result than the shortest distance. The longest distance obtained the highest accuration and precision, so these result were used as the learning data for neural network. Neural network were used as the data interpretation. The input of neural network was not only the time of flight, but also colour of the sample and kinematic viscocity of biodiesel at room temperature. <br /> <br /> <br /> <br /> <br /> The outcome of data interpretation was using three types of neural network (NN 1, NN 2, NN 3) then compared with linear regression approximation. Average failure for linear regression was 24.51%. The average failure for NN 1 and NN 3 were 14,13% and 14,58%. Among three types of neural network, NN 2 proved the best performance which had the lowest average failure, 12,66%. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Biodiesel is one of the altenative diessel fuel. Biodiesel has some advantages and disadvantages. To overcome these disadvantages, biodiesel have to react to fossil diesel first. The percentage of biodiesel in diesel fuel is quite important as the indicator for quality of diesel fuel in applications. To estimate the percentage of biodiesel in diesel fuel accurately, precisely, fast, and user friendly, in this study the ultrasonic based instrument is proposed. <br /> <br /> <br /> <br /> <br /> To perform ultrasonic measurement, two types of transducers placement were used. First, the distance between transmitter and receiver which had frequency in 2.25 MHz were 13,23 cm. Second, the distance between transmitter and receiver which had frequency in 2 MHz were 1.13 cm. The result of both designed ultrasonic measurement were time of flight ultrasonic wave. The longest distance obtained better result than the shortest distance. The longest distance obtained the highest accuration and precision, so these result were used as the learning data for neural network. Neural network were used as the data interpretation. The input of neural network was not only the time of flight, but also colour of the sample and kinematic viscocity of biodiesel at room temperature. <br /> <br /> <br /> <br /> <br /> The outcome of data interpretation was using three types of neural network (NN 1, NN 2, NN 3) then compared with linear regression approximation. Average failure for linear regression was 24.51%. The average failure for NN 1 and NN 3 were 14,13% and 14,58%. Among three types of neural network, NN 2 proved the best performance which had the lowest average failure, 12,66%.
format Final Project
author SYAHNARIZA NAN BARENO (NIM : 13311034), FADYA
spellingShingle SYAHNARIZA NAN BARENO (NIM : 13311034), FADYA
MEASURING PERCENTAGE OF BIODIESEL IN DIESEL FUEL USING ULTRASONIC WAVE
author_facet SYAHNARIZA NAN BARENO (NIM : 13311034), FADYA
author_sort SYAHNARIZA NAN BARENO (NIM : 13311034), FADYA
title MEASURING PERCENTAGE OF BIODIESEL IN DIESEL FUEL USING ULTRASONIC WAVE
title_short MEASURING PERCENTAGE OF BIODIESEL IN DIESEL FUEL USING ULTRASONIC WAVE
title_full MEASURING PERCENTAGE OF BIODIESEL IN DIESEL FUEL USING ULTRASONIC WAVE
title_fullStr MEASURING PERCENTAGE OF BIODIESEL IN DIESEL FUEL USING ULTRASONIC WAVE
title_full_unstemmed MEASURING PERCENTAGE OF BIODIESEL IN DIESEL FUEL USING ULTRASONIC WAVE
title_sort measuring percentage of biodiesel in diesel fuel using ultrasonic wave
url https://digilib.itb.ac.id/gdl/view/20090
_version_ 1821120045381582848