Abstract
Due to growth of mechanisation and automation, today’s industrial systems are becoming more complex. A small breakdown of any non-redundant machine component affects the operation of the entire system. To increase the availability and reliability, automated health monitoring and self-diagnostic capability (SDC) becoming essential to many industrial machineries like pumps, motors, etc. Condition monitoring does not prevent the failure, but it can predict the possibility of future failure by measuring certain machine parameters. Though there are various condition monitoring techniques, vibration analysis and motor current signature analysis (MCSA) are most suitable for detection of faults and abnormalities in machine systems . This work attempts to develop an SDC framework and diagnose the impeller condition of a centrifugal pump using MCSA. Time and frequency domain analyses are done for different impeller conditions of the pump, such as normal impeller and defective impellers. Significant differences are observed and a fault prediction strategy is recommended.
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