Centrifugal pump condition monitoring and diagnosis using frequency domain analysis

Centrifugal pumps are rotating machines which are widely used in process operations and other applications. Efficient and failure-free operation of these pumps is important for effective plant operation and productivity. However, the complexity of pumps, combined with continuous operation, can lead to failure and expensive maintenance requirements, thus motivating interest in on-line condition monitoring. This work investigates the application of frequency-domain analysis for classification of various centrifugal pump conditions. Seven conditions are considered, namely, healthy (non-faulty); five mechanical faults: misalignment, imbalance, faulty bearing, faulty impeller and mechanical looseness; and a hy-draulic fault: cavitation. A centrifugal pump test rig was built specifically for this research to simulate each fault condition and acquire the resulting vibration measurements. Signals are acquired from the pump using an accelerometer which is mounted on its bearing housing, and a data acquisition device (DAQ) is used to acquire the signals. Fast Fourier Transform (FFT) is used to analyze the signals using MATLAB, and the obtained results demonstrate the ability of FFT in detecting the pump’s conditions. However, the accuracy of detection for the non-stationary signals is shown to require further improvement, and alternate methods are suggested accordingly.