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Wireless Sensor Networks for Machinery Monitoring

[+] Author Affiliations
V. Sundararajan

University of California at Riverside

Andrew Redfern, Michael Schneider, Paul Wright, James Evans

University of California at Berkeley

Paper No. IMECE2005-82224, pp. 425-433; 9 pages
doi:10.1115/IMECE2005-82224
From:
  • ASME 2005 International Mechanical Engineering Congress and Exposition
  • Manufacturing Engineering and Materials Handling, Parts A and B
  • Orlando, Florida, USA, November 5 – 11, 2005
  • Conference Sponsors: Manufacturing Engineering Division and Materials Handling Division
  • ISBN: 0-7918-4223-1 | eISBN: 0-7918-3769-6
  • Copyright © 2005 by ASME

abstract

Wireless sensor networks (WSNs) are currently been actively investigated in the research community on account of their unprecedented spatial density of sensors, local computational plus storage capacity, and potential for distributed and fault-tolerant monitoring. Today, they are mainly deployed for environmental monitoring - e.g. for “smart building” control, water quality monitoring, and botanical studies. In the future, it is clear they have a huge potential for industrial applications such as machinery monitoring, shop instrumentation, and process control. Wireless sensor nodes can be mounted on various parts of machinery and plant to promote early fault detection and analysis. Their small size and autonomy enables their placement in locations that are usually difficult to access. In addition, it is also possible, with minimal changes to the machine configuration, to deploy sensors on the machinery after it has been installed. The sensor nodes cannot only monitor their own output but also collaborate with neighboring nodes to determine the health of the overall machines and provide early warnings of potential failure. We study, in this paper, the benefits of using wireless sensor networks in machine tools and plant equipment. We discuss the uses of these networks and the issues that must be addressed in order for these implementations to be successful. We also present two case studies for machinery and machine too monitoring.

Copyright © 2005 by ASME

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