Downloads: 130 | Views: 221 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

M.Tech / M.E / PhD Thesis | Mechanical Engineering | India | Volume 4 Issue 8, August 2015

Vibration Based Blind Identification of Bearing Failures in Rotating Machinery

Rohit Gopalkrishna Sorte | Pardeshi Ram

Abstract: Present paper deals with a suitable tests rig, which can help in determination the vibration in wind mill or other rotating machinery with the help of Test rig assembly, which can be further utilized to check on the behaviour of bearing in various corrupted noise and signal. Therefore we can know the early fault in bearing to avoid loss of cost production and catastrophic accident. So it is important to detect incipient faults. In condition monitoring, the early detection of incipient bearing signal is often made difficult due to its unusual noise by background vibration. Hence it is essential to minimize the noise of component in the observed signal. This paper shows that the proposed technical with optimum filter length does improved the signal and can be used for automatic feature extraction and fault classification. This technique has potential for use in wind mill or rotating machine diagnostics.

Keywords: Signal-Noise-Ratio SNR, Corrupting signal, Noise, Filter, Frequency

Edition: Volume 4 Issue 8, August 2015,

Pages: 199 - 207