Year: 2015
Type: preprint
Abstract: A pattern recognition (PR) based diagnostic scheme is presented to identify bearing faults, using time domain features. Vibration data is acquired from faulty bearings using a test rig. The features are extracted from the data, and processed prior to utilize in the PR process. The processing involves smoothing of feature distributions. This reduces the undesired impact of vibration randomness on the PR process, and thus enhances the diagnostic accuracy of the model.
Source: arXiv (Cornell University)
Authors: Tahir, Muhammad Masood, Hussain, Ayyaz
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2286821407