An adaptive morphological impulses extraction method （AMIE） for bearing fault diagnosis is pro- posed. This method uses the morphological closing operation with a flat structuring element （SE） to extract impulsive...An adaptive morphological impulses extraction method （AMIE） for bearing fault diagnosis is pro- posed. 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.展开更多
基金Supported by the High Technology Research and Development Programme of China （No. 2007AA04Z433） and the National Natural Science Foundation of China （No. 50635010）.
文摘An adaptive morphological impulses extraction method （AMIE） for bearing fault diagnosis is pro- posed. 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.
