Abstract
A remote real-time machine condition monitoring system is reported in this paper, which is applied for diagnosis and prognosis of gearboxes’ working condition. Within the system, the diagnostic classification is performed by pattern recognition using statistic parameters, and remote diagnostic capability is enhanced by applying Wireless Web technology. An online signal-processing scheme is adopted based on time-frequency analysis, digital filtering and statistic parameter algorithm to detect early fault signals of gears and to provide expert advice for decision making for maintenance. The effectiveness of the developed remote diagnostic system is verified via experimental investigation of monitoring a gearbox on a test rig under different conditions.
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