Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Cover of the book

2013 | OriginalPaper | Chapter

1. Introduction

Authors : Jenny Terzic, Edin Terzic, Romesh Nagarajah, Muhammad Alamgir

Published in: Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This book documents a research program undertaken to design and develop an ultrasonic sensor-based fluid level measurement system for dynamic environments, in particular automotive applications. This research is a subset of an overall research program titled “Smart Sensor for Fluid Level Measurement in Hazardous and Dynamic Environments.” The research work presented herein is based on the use of an ultrasonic sensors coupled with a support vector machines-based signal processing system for accurately determining the fluid level in dynamic environments. The objective of this research project is to design and develop a fluid level measurement system based on a nonmechanical and contactless sensor to accurately determine the level of fluid in a dynamic environment, especially in vehicular fuel tanks. The motivation for this research is the automotive industry’s requirement for a robust and accurate fuel level measurement system that would function reliably in the presence of slosh, and temperature variations.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
next chapter Ultrasonic Sensing Technology
Literature
1.
Pallas-Areny R, Webster JG (2001) Resistive sensors. Sensors and signal conditioning. Wiley. New York, pp 73–131
2.
Fischer-Cripps AC (2002) Force, pressure and flow. Newnes interfacing companion. Newnes, Oxford, pp 54–70
3.
Astashev VK, Babitsky VI (2007) Ultrasonic processes and machines: dynamics, control and applications. In: Babitsky VI, Wittenburg J (eds). Springer, Berlin
4.
Hauptmann P, Lucklum R, Püttmer A, Henning B (1998) Ultrasonic sensors for process monitoring and chemical analysis: state-of-the-art and trends. Sens Actuator A: Phys 67(1–3):32–48
5.
Jan J (2006) Medical image processing, reconstruction, and restoration: concepts and methods. Taylor & Francis, Boca Raton
6.
Dunn WC (2005) Level measurement. Introduction to instrumentation, sensors and process control. Artech House, Boston, pp 115–126
7.
Dunn WC (2005) Introduction to instrumentation, sensors and process control. Artech House, Boston
8.
Kuttruff H (1991) Ultrasonics—fundamentals and applications. Elsevier Applied Science, London
9.
Serway RA, Jewett JW (2004) Sound waves. Physics for scientists and engineers, 6th edn. Thomson-Brooks/Cole, Belmont, pp 512–542
10.
Song Z-Y, Liu C-Y, Song X-L (2004) Application research of information fusion technology of multi-sensor in level measurement. In: International conference on machine learning and cybernetics, vol 6, pp 3511–3514
11.
Song Z, Liu C, Song X, Zhao Y, Wang J (2007) A virtual level temperature compensation system based on information fusion technology. In: IEEE international conference on robotics and biomimetics, pp 1529–1533
12.
Gazis DC, Kane WF, von Gutfeld RJ (inventors), International Business Machines Corporation, (assignee) (1996) Ultrasonic liquid level gauge for tanks subject to movement and vibration. Patent no. 5,793,705
13.
Combs CM, Goodwin PH Jr, (inventors), Robertshaw Controls Company, (assignee) (1978) Adjustable ultrasonic level measurement device. Patent no. 4221004
14.
Ibrahim RA (2005) Liquid sloshing dynamics: theory and applications. Cambridge University Press, Cambridge
15.
Kim H-S, Lee Y-S (2008) Optimization design technique for reduction of sloshing by evolutionary methods. J Mech Sci Technol 22:25–33
16.
aus der Wiesche S (2003) Computational slosh dynamics: theory and industrial application. Comput Mech 30(5–6):374–387
17.
Kobayashi H, Obayashi H (inventors), Nissan Motor Company, Limited, (assignee) (1983) Fuel volume measuring system for automotive vehicle. Patent no. 4611287
18.
Kobayashi H, Kita T (inventors), Nissan Motor Company, Limited (assignee) (1982) Fuel gauge for an automotive vehicle. Patent no. 4470296
19.
Guertler T, Hartmann M, Land K, Weinschenk A (inventors); Daimler Benz AG (DE) (assignee) (1997) Process for determining a liquid quantity, particularly an engine oil quantity in a motor vehicle. Patent no. 5831154
20.
Zhao S (2004) Remote sensing data fusion using support vector machine. In: IEEE international geoscience and remote sensing symposium proceedings, vol 4, pp 2575–2578
21.
Reyna RA, Esteve D, Houzet D, Albenge M-F (2000) Implementation of the SVM neural network generalization function for image processing. In: IEEE International workshop on computer architectures for machine perception (CAMP’00)
22.
Vapnik VN (1998) Statistical learning theory. Wiley, New York
23.
Vapnik VN (1995) The nature of statistical learning theory. Springer, New York
24.
Hu YH, Hwang J-N (2002) Handbook of neural network signal processing. CRC Press, Boca Raton
25.
Kecman V (2001) Learning and soft computing: support vector machines, neural networks, and fuzzy logic models. MIT Press, Cambridge
26.
Zhang J, Liu X, Liu J, Peng F, Tian J, Wang Y, Zhang W, Xie M (2001) SVM-based ultrasonic medicine image diagnosis. Med Image Acquis Process 4549:92–95
27.
Meyer D, Leischa F, Hornikb K (2003) The support vector machine under test. Neurocomputing 55(1–2):169–186
28.
Ahmad AR, Viard-Gaudin C, Khalid M, Poisson E (2004) Online handwriting recognition using support vector machine. In: IEEE Region 10 international conference (TENCON’04)
29.
Ganapathiraju A, Hamaker J, Picone J (2004) Applications of support vector machines to speech recognition. IEEE Trans Signal Process 52(8):2348–2355
30.
Rajpoot KM, Rajpoot NM (2004) Wavelets and support vector machines for texture classification. In: Proceedings of international multitopic conference (INMIC), pp 328–333
31.
Huang J, Shao X, Wechsler H (1998) Face pose discrimination using support vector machines (SVM). In: International conference on pattern recognition, vol 1, pp 154–156
32.
Boni A, Gasparini L, Pianegiani R, Petri D (2005) Low-power and low-cost implementation of SVMs for smart sensors. In: IEEE instrumentation and measurement technology conference proceedings, vol 1, pp 603–607
33.
Wang J, Wu X, Zhang C (2005) Support vector machines based on K-means clustering for real-time business intelligence systems. Int J Bus Intell Data Min 1(1):54–64MathSciNetCrossRef
34.
35.
36.
Allen RL, Mills DW (2004) Time-domain signal analysis. Signal analysis: time, frequency, scale, and structure. IEEE Press; Wiley-Interscience. Piscataway, p 322
37.
Bass I, Lawton B (2009) Improve. Lean six sigma using SigmaXL and Minitab. McGraw-Hill, New York, pp 213–282
38.
Yom-Tov E (2004) An introduction to pattern classification. In: Bousquet O, von Luxburg U, Rätsch G, School, Machine Learning Summer, (eds) Advanced lectures on machine learning: ML Summer Schools 2003, Canberra, Australia, 2–14 Feb 2003, Tübingen, Germany, Springer, Berlin, pp 1–20 (4–16 Aug 2003: revised lectures)
Metadata
Title
Introduction
Authors
Jenny Terzic
Edin Terzic
Romesh Nagarajah
Muhammad Alamgir
Copyright Year
2013
Publisher
Springer International Publishing
Book
Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications

Print ISBN: 978-3-319-00632-1

Electronic ISBN: 978-3-319-00633-8

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-3-319-00633-8_1

Premium Partner

    Image Credits