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A Neural Network Approach to Fluid Quantity Measurement in Dynamic Environments by Edin Terzic; Jenny Terzic; Romesh Nagarajah; Muhammad Alamgir is a book available to read on EtoBox.

What is A Neural Network Approach to Fluid Quantity Measurement in Dynamic Environments about?

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

Author

Edin Terzic; Jenny Terzic; Romesh Nagarajah; Muhammad Alamgir

Publisher

Springer London Ltd

Published

2012

Language

EN

ISBN

9781280794643

Subjects

Science, Engineering, Computer Science