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An Innovative Online Diagnostic Tool for a Distributed Spatial Coordinate Measuring System

In: Statistics for Innovation

Author

Listed:
  • Fiorenzo Franceschini

    (Politecnico di Torino, Department of Production Systems and Business Economics (DISPEA))

  • Maurizio Galetto

    (Politecnico di Torino, Department of Production Systems and Business Economics (DISPEA))

  • Domenico Maisano

    (Politecnico di Torino, Department of Production Systems and Business Economics (DISPEA))

  • Luca Mastrogiacomo

    (Politecnico di Torino, Department of Production Systems and Business Economics (DISPEA))

Abstract

There is currently an increasing trend for accurate measurements of large-scale lengths; in particular, 3D coordinate metrology at length scales of 5 m to 60 m has become a routine requirement in industries such as aircraft and ship construction. This chapter focuses on the Mobile Spatial coordinate Measuring System (MScMS), a new system developed at the Industrial Metrology and Quality Engineering Laboratory of DISPEA of the Politecnico di Torino. Based on a distributed sensor network structure, MScMS is designed to perform simple and rapid indoor dimensional measurements of large-size objects. Using radiofrequency (RF) and ultrasound (US) signals, the system makes it possible to localize-in terms of spatial coordinates-the points “touched” by a wireless mobile probe. To protect the system from potential causes of error, such as US signal diffraction and reflection, external uncontrolled US sources (key jingling, neon blinking, etc.) or unacceptable software solutions, MScMS implements some statistical tests in order to perform online diagnostics. One of these tests is analyzed in depth in this chapter: the “energy model-based diagnostics test.” Although it is specifically developed for the MScMS

Suggested Citation

  • Fiorenzo Franceschini & Maurizio Galetto & Domenico Maisano & Luca Mastrogiacomo, 2009. "An Innovative Online Diagnostic Tool for a Distributed Spatial Coordinate Measuring System," Springer Books, in: Pasquale Erto (ed.), Statistics for Innovation, chapter 0, pages 161-176, Springer.
    • Handle: RePEc:spr:sprchp:978-88-470-0815-1_9
    DOI: 10.1007/978-88-470-0815-1_9
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