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In this paper, the detection of faults in fan at early stages is carried out using vibration signals so that proper corrective measures can be performed before final failure. The early detection of faults will reduce the downtime of critical equipment. The unbalance fault is seeded on the fan by putting m-seal masses in one of its fan blade and detection of this fault is carried out by using vibration signal. These detections are carried out at two different speeds. In the second phase broken blade fault is seeded on the fan by cutting fan blade along its width into small parts in incremental manner and then the detection is performed at two different speeds. Both the faults detection data of fan is compared with data of healthy fan and notice the variation in amplitude on their characteristic defect frequency. Signal processing like STFT and wavelet transform analysis is carried out in broken blade fault condition by using time domain data. A comparison of signal processing between FFT, STFT and wavelet transform analysis using time domain data is performed.
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