A Neural Network Approach to Fluid Quantity Measurement in Dynamic Environments

Sloshing causes liquid to fluctuate, making accurate level readings difficult to obtain in dynamic environments. The measurement system described uses a single-tube capacitive sensor to obtain an instantaneous level reading of the fluid surface, thereby accurately determining the fluid quantity in t...

Disgrifiad llawn

Wedi'i Gadw mewn:
Manylion Llyfryddiaeth
Prif Awduron: Terzic, Edin, Terzic, Jenny (Awdur), Nagarajah, Romesh (Awdur), Alamgir, Muhammad (Awdur)
Fformat: Livre numérique
Iaith:Anglais
Cyhoeddwyd: London : Springer London [20..].
Cham : Springer Nature
Rhifyn:1st ed. 2012.
Mynediad Ar-lein:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
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Nodyn: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• A Neural Network Approach to Fluid Quantity Measurement in Dynamic Environments, Texte imprimé, 9781447140597
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100 1 |a Terzic, Edin. 
245 1 0 |a A Neural Network Approach to Fluid Quantity Measurement in Dynamic Environments   |c by Edin Terzic, Jenny Terzic, Romesh Nagarajah, Muhammad Alamgir. 
250 |a 1st ed. 2012. 
260 |a London :  |b Springer London. 
260 |a Cham :  |b Springer Nature,  |c [20..]. 
500 |a Archives Springer e-books (Licence nationale) 
500 |a Archives Springer e-books (Licence nationale) 
505 1 |a Chapter 1 Introduction Chapter 2 Capacitive Sensing Technology Chapter 3 Fluid Level Sensing Using Artificial Neural Networks Chapter 4 Methodology Chapter 5 Experimentation Chapter 6 Results Chapter 7 Discussion Chapter 8 Conclusions and Future Work 
506 |a Accès en ligne pour les établissements français bénéficiaires des licences nationales 
506 |a Accès soumis à abonnement pour tout autre établissement 
506 |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 
520 |a Sloshing causes liquid to fluctuate, making accurate level readings difficult to obtain in dynamic environments. The measurement system described uses a single-tube capacitive sensor to obtain an instantaneous level reading of the fluid surface, thereby accurately determining the fluid quantity in the presence of slosh. A neural network based classification technique has been applied to predict the actual quantity of the fluid contained in a tank under sloshing conditions.  In A neural network approach to fluid quantity measurement in dynamic environments, effects of temperature variations and contamination on the capacitive sensor are discussed, and the authors propose that these effects can also be eliminated with the proposed neural network based classification system. To examine the performance of the classification system, many field trials were carried out on a running vehicle at various tank volume levels that range from 5 L to 50 L. The effectiveness of signal enhancement on the neural network based signal classification system is also investigated. Results obtained from the investigation are compared with traditionally used statistical averaging methods, and proves that the neural network based measurement system can produce highly accurate fluid quantity measurements in a dynamic environment. Although in this case a capacitive sensor was used to demonstrate measurement system this methodology is valid for all types of electronic sensors.The approach demonstrated in A neural network approach to fluid quantity measurement in dynamic environments can be applied to a wide range of fluid quantity measurement applications in the automotive, naval and aviation industries to produce accurate fluid level readings. Students, lecturers, and experts will find the description of current research about accurate fluid level measurement in dynamic environments using neural network approach useful 
700 1 |a Terzic, Jenny.  |4 aut 
700 1 |a Nagarajah, Romesh.  |4 aut 
700 1 |a Alamgir, Muhammad.  |4 aut 
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