An adaptive morphological impulses extraction method and its application to fault diagnosis

An adaptive morphological impulses extraction method (AMIE) for bearing fault diagnosis is proposed. This method uses the morphological closing operation with a flat structuring element (SE) to extract impulsive features from vibration signals with strong background noise. To optimize the flat SE, firstly , a theoretical study is carried out to investigate the effects of the length of the flat SE. Then, based on the theoretical findings, an adaptive algorithm for the flat SE optimization is proposed. The AMIE method is tested by the simulated signal and bearing vibration signals. The test results show that this method is effective and robust in extracting impulsive features.