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Automation of Wear Debris Analysis for Machine Health Diagnostics

Automation of Wear Debris Analysis for Machine Health Diagnosticsvon Muhammad Khan Sie sparen 23% des UVP sparen 23%
Über Automation of Wear Debris Analysis for Machine Health Diagnostics

The technique that deals with the lost surface material or debris of the component for its condition assessment is known as Wear Debris Analysis (WDA). As wear debris is formed from the surface interactions of components, its basic features contain valuable information of surface failure events that can aid in the determination of component health. To utilise the full potential of WDA for reliable health diagnosis, it is essential to analyse all the basic features of debris simultaneously. Since the Mid 70¿s, researchers have used WDA for machine health diagnosis. However, due to lack of automation, it still requires research to demonstrate its effectiveness to prevent machine sudden failures by using its full potential. In this book, the deficiencies of the current automation efforts are discussed. Ideas and methodologies are developed and used that eventually overcome these deficiencies. A novel system of automation is also proposed and discussed. The experimentation on this novel system helps to determine the effectiveness of wear debris analysis in near real-time machine health diagnostics.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9786134951678
  • Einband:
  • Taschenbuch
  • Seitenzahl:
  • 236
  • Veröffentlicht:
  • 25 Januar 2018
  • Abmessungen:
  • 150x15x220 mm.
  • Gewicht:
  • 369 g.
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Beschreibung von Automation of Wear Debris Analysis for Machine Health Diagnostics

The technique that deals with the lost surface material or debris of the component for its condition assessment is known as Wear Debris Analysis (WDA). As wear debris is formed from the surface interactions of components, its basic features contain valuable information of surface failure events that can aid in the determination of component health. To utilise the full potential of WDA for reliable health diagnosis, it is essential to analyse all the basic features of debris simultaneously. Since the Mid 70¿s, researchers have used WDA for machine health diagnosis. However, due to lack of automation, it still requires research to demonstrate its effectiveness to prevent machine sudden failures by using its full potential. In this book, the deficiencies of the current automation efforts are discussed. Ideas and methodologies are developed and used that eventually overcome these deficiencies. A novel system of automation is also proposed and discussed. The experimentation on this novel system helps to determine the effectiveness of wear debris analysis in near real-time machine health diagnostics.

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