Development of diagnosis system for rolling bearings faults on real time based on FPGA
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Data
2012-04-01
Autores
Kashiwagi, M. [UNESP]
da Costa, C.
Mathias, M. H. [UNESP]
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Resumo
The real-time monitoring of events in an industrial plant is an advanced technique that presents the real conditions of operation of the machinery responsible for the manufacturing process. A predictive maintenance program includes various rotating machinery condition monitoring techniques of the machine to determine the conditions of failure. To increase the operational reliability and to reduce preventive maintenance, it is necessary an efficient tool for analysis and process monitoring, in real time, enabling the detection of incipient faults for rolling bearings. Over the past few years there has been a major technological developments related to digital system, including innovations in both hardware and software. These innovations enable the development of new design methodologies that take into account the ease of future modifications, upgrades and expansions of the designed system. This paper presents a study of new design tools for embedded digital systems based on open hardware architecture with reconfigurable logic. Will be discussed a case study in the area of fault detection of rolling bearings, as well as its implementation and testing.
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Digital signal processing and FPGA, Embedded system, Mechanical vibration
Como citar
Renewable Energy and Power Quality Journal, v. 1, n. 10, p. 545-549, 2012.