Ball Mill Shell Vibration Signal Analysis Strategy Based on DEM-FEM Method and Multi-Component Signal Adaptive Decomposition Technique
Jian Tang, Zhiwei Wu, Zhuo Liu
Available Online January 2016.
- https://doi.org/10.2991/ifmeita-16.2016.55How to use a DOI?
- DEM, FEM, Ball mill, Vibration signal analysis, EMD, HVD.
- Ball mills are heavy rotating mechanical devices of industrial processes. Ball mill shell vibration signal has characteristics of multi-component and non-stationary. It has been a new focus to estimate some difficult-to-measure process parameters, such as load parameters within mill. The detailed analysis of the shell vibration signal production mechanism can help us construct estimation model with reasonable physical interpretation and well generalization performance. Thus, a new strategy of the shell vibration signal analysis based on DEM-FEM method and multi-component signal adaptive decomposition technique is proposed. At first, a simple ball mill shell FEM model is constructed. Then, this model is imported to DEM for producing impaction forces to mill shell. Then, these forces are added on the FEM model to active the mill shell vibration for producing the virtual accelerator vibration signal. Finally, the virtual shell vibration signal is analyzed with the multi-component signal adaptive decomposition techniques, such as empirical mode decomposition (EMD) and Hilbert vibration decomposition (HVD). Further research would focus on experimental calibration to give reasonable simulation results.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jian Tang AU - Zhiwei Wu AU - Zhuo Liu PY - 2016/01 DA - 2016/01 TI - Ball Mill Shell Vibration Signal Analysis Strategy Based on DEM-FEM Method and Multi-Component Signal Adaptive Decomposition Technique BT - 2016 International Forum on Management, Education and Information Technology Application PB - Atlantis Press SP - 293 EP - 297 SN - 2352-5398 UR - https://doi.org/10.2991/ifmeita-16.2016.55 DO - https://doi.org/10.2991/ifmeita-16.2016.55 ID - Tang2016/01 ER -