- Title
- Identifying grinding mill dynamics using acoustic beamforming and numerical modelling
- Creator
- Wu, Dongling; Chen, Wei; Yan, Hongjie; Fischer, Jeoffrey; Doolan, Con
- Relation
- Powder Technology Vol. 371, Issue 30 June 2020, p. 231-243
- Publisher Link
- http://dx.doi.org/10.1016/j.powtec.2020.05.092
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2020
- Description
- Online measurement of the grinding dynamics within mills is crucial for its optimal operation in terms of reduced liner wear and maximised throughput. Non-invasive measurement techniques, such as the noise-based acoustic beamforming may be utilised to more effectively identify charge dynamics, which is studied in this paper. A pilot mill and an associated acoustic microphone array were purposely designed and constructed, and a suite of experiments with various mill charge compositions and mill speeds was conducted. Numerical modelling of the pilot mill with a coupled discrete element modelling (DEM) and smoothed particle hydrodynamics (SPH) was also performed to compare the acoustic beamforming results. It was indicated that level of the acoustic noise generated during mill operation is more associated with steel ball filling rate rather than the mill speed. Beamforming results suggested that grinding dynamics and mill charge shape can be reconstructed from acoustic noise measured at 500 Hz frequency band. Numerical modelling indicated that charge throw trajectory was more susceptible to mill speed than the ball filling rate. DEM contact parameters showed negligible effect on altering the grinding dynamics. In addition, comparison between numerical modelling and acoustic beamforming showed analogous results. The outcome of this study suggested that acoustic beamforming can be utilised for online detection of grinding dynamics in operation.
- Subject
- grinding mills; acoustic noise; beamforming; discrete element modelling; smoothed particle hydrodynamics
- Identifier
- http://hdl.handle.net/1959.13/1436030
- Identifier
- uon:39897
- Identifier
- ISSN:0032-5910
- Language
- eng
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