Based on the statics theory, a novel and feasible twice-suspended-mass method(TSMM) was proposed to deal with the seldom-studied issue of fault diagnosis for damping springs of large vibrating screen(LVS). With the st...Based on the statics theory, a novel and feasible twice-suspended-mass method(TSMM) was proposed to deal with the seldom-studied issue of fault diagnosis for damping springs of large vibrating screen(LVS). With the static balance characteristic of the screen body/surface as well as the deformation compatibility relation of springs considered, static model of the screen surface under a certain load was established to calculate compression deformation of each spring. Accuracy of the model was validated by both an experiment based on the suspended mass method and the properties of the 3D deformation space in a numerical simulation. Furthermore, by adopting the Taylor formula and the control variate method, quantitative relationship between the change of damping spring deformation and the change of spring stiffness, defined as the deformation sensitive coefficient(DSC), was derived mathematically, from which principle of the TSMM for spring fault diagnosis is clarified. In the end, an experiment was carried out and results show that the TSMM is applicable for diagnosing the fault of single spring in a LVS.展开更多
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Project(20120095110001)supported by the PhD Programs Foundation of Ministry of Education of ChinaProject(51134022,51221462)supported by the National Natural Science Foundation of China+1 种基金Project(CXZZ13_0927)supported by Research and Innovation Program for College Graduates of Jiangsu Province,ChinaProject(2013DXS03)supported by the Fundamental Research Funds for Central Universities of China
文摘Based on the statics theory, a novel and feasible twice-suspended-mass method(TSMM) was proposed to deal with the seldom-studied issue of fault diagnosis for damping springs of large vibrating screen(LVS). With the static balance characteristic of the screen body/surface as well as the deformation compatibility relation of springs considered, static model of the screen surface under a certain load was established to calculate compression deformation of each spring. Accuracy of the model was validated by both an experiment based on the suspended mass method and the properties of the 3D deformation space in a numerical simulation. Furthermore, by adopting the Taylor formula and the control variate method, quantitative relationship between the change of damping spring deformation and the change of spring stiffness, defined as the deformation sensitive coefficient(DSC), was derived mathematically, from which principle of the TSMM for spring fault diagnosis is clarified. In the end, an experiment was carried out and results show that the TSMM is applicable for diagnosing the fault of single spring in a LVS.
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.
