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A neural network approach to fluid quantity measurement in dynamic environments

editor, Edin Terzic ([Springer-Verlag, Springer-Verlag], 2012)

 Abstrak

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.

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 Metadata

Jenis Koleksi : eBooks
No. Panggil : e20418592
Entri tambahan-Nama orang :
Subjek :
Penerbitan : London: [Springer-Verlag, Springer-Verlag], 2012
Sumber Pengatalogan: LibUI eng rda
Tipe Konten: text
Tipe Media: computer
Tipe Pembawa: online resource
Deskripsi Fisik:
Tautan: http://link.springer.com/book/10.1007%2F978-1-4471-4060-3
Lembaga Pemilik:
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No. Panggil No. Barkod Ketersediaan
e20418592 20-21-74603337 TERSEDIA
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