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Wireless Condition-based Maintenance System for Rotating Machinery

Tran, Van Tung (2011) Wireless Condition-based Maintenance System for Rotating Machinery. In: International Symposium on Mechatronics and Robotics, 27-28 October 2011, Hochiminh City, Vietnam.

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Condition-based maintenance (CBM) presently plays an important role in avoiding unexpected failures, improving machine reliability, and providing accurate maintenance records and activities for rotating machinery. Traditional wired sensors commonly used for gathering data are costly and of limited value in industry. Recently, together with the advancement of sensor technology and communication networks, sensors have been virtually metamorphosed into smaller, cheaper, and more intelligent ones. These sensors are equipped with wireless interface that can communicate with others to form a network. This enables the sensors to be flexibly applicable and the hard cables from the sensors to the data acquisition/analysis system to be eliminated, hence, lead to reduction of the capital and maintenance costs. In this study, a wireless CBM system comprised hardware and software components is proposed to deal with the maintenance issues of rotating machinery. The hardware component consists of wireless sensors and networks used for receiving, processing, and transmitting signals obtained from the machine. The software component is a Matlab graphic user interface which is implemented for data processing and analysis, condition monitoring, diagnostics, and prognostics. The viability of the wireless CBM system for industrial application is presented using the water pump system as a case-study to evaluate the reliability and applicability of this system

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering
Depositing User: Van Tran
Date Deposited: 07 Feb 2013 14:12
Last Modified: 04 Nov 2015 16:41


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