A Neural Network Approach to Fluid Quantity Measurement in Dynamic Environments. 1st ed. 2012

種類:

電子ブック

責任表示:

by Edin Terzic, Jenny Terzic, Romesh Nagarajah, Muhammad Alamgir

出版情報:

London : Springer London : Imprint: Springer, 2012

著者名:

• Terzic, Edin.
• Terzic, Jenny.
• Nagarajah, Romesh.
• Alamgir, Muhammad.
• SpringerLink (Online service)

ISBN:

9781447140603 [1447140605]    

注記:

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.
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

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