The results revealed that, for centrifugal pumps within 15 to 300kw power range, vibration-velocity amplitude of between 0.9 and 2.7mm/s was within acceptable limits. The model was validated using data obtained from a centrifugal pump on full load and fed into the program written in Visual Basic. For various categories of this type of machinery, a vibration-severity chart (ISO 12372 / BS 4675: 1971) appropriately colour coded according to defined mechanical faults, was used in training of the ANN. A computer-based diagnostic tool employing an artificial neural-network (ANN) was developed to analyse the ensuing machinery faults, their causes and consequences. In particular, this project explored the use of vibration parameters in the diagnosis of equipment failure. To ensure plant reliability and equipment availability, a condition-based maintenance policy has been developed in this investigation. A major part of the energy used in any production process is expended during the maintenance of the employed equipment. Wise maintenance-procedures are essential for achieving high industrial productivities and low energy expenditure.
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