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Designing an Immunity-Based Sensor Network for Sensor-Based Diagnosis of Automobile Engines

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4252))

Abstract

This paper reports on the construction and use of a dynamic relational network that has been studied as an immunity-based system based on the concept of immune networks. The network is constructed by an immunological algorithm that tunes the network not to react to normal sensor data, but to react to abnormal data thereafter. The tuning is not straightforward, since even normal sensor data involve many situations such as accelerating phase and cruise phase; on-road and off-road; and running at altitude. A case study on sensor systems for the combustion control system of an automobile engine is presented.

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Author information

Authors and Affiliations

  1. Department of Knowledge-Based Information Engineering, Toyohashi University of Technology, Tempaku, Toyohashi, 441-8580, Japan

    Yoshiteru Ishida

Authors
  1. Yoshiteru Ishida
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Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK

    Bogdan Gabrys

  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, SA, 5095, Mawson Lakes, Australia

    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Ishida, Y. (2006). Designing an Immunity-Based Sensor Network for Sensor-Based Diagnosis of Automobile Engines. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004_19

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  • DOI: https://doi.org/10.1007/11893004_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46537-9

  • Online ISBN: 978-3-540-46539-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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