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Factors affecting the production of broadband acoustic emission signals and their use in particle characterisation

Factors affecting the production of broadband acoustic emission signals and their use in particle characterisation. Nichola Townshend and Alison Nordon WestCHEM, Department of Pure and Applied Chemistry and CPACT University of Strathclyde, Glasgow, UK. Benefits of acoustics. Non-invasive

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Factors affecting the production of broadband acoustic emission signals and their use in particle characterisation

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  1. Factors affecting the production of broadband acoustic emission signals and their use in particle characterisation Nichola Townshend and Alison Nordon WestCHEM, Department of Pure and Applied Chemistry and CPACT University of Strathclyde, Glasgow, UK.

  2. Benefits of acoustics • Non-invasive • Non-destructive • Relatively inexpensive • Information on physical properties • Opaque samples can be analysed • No window required • Multi-point measurements can be made • Real-time measurement

  3. Acoustic emission (AE) • Many processes give rise to AE (passive acoustics) • Solids processes, e.g. blending, granulation and milling • Heterogeneous processes, e.g. crystallisation, chemical reactions, bioprocesses • AE typically at frequencies up to 500 kHz • Commercial AE systems available that have been used successfully for process monitoring • Tend to employ resonant transducer and/or convert signal to DC level  AE frequency information lost

  4. Broadband acoustic emission • Acoustic emission signals acquired across a range of frequencies • Signal acquisition requirements • Sampling rate  frequency range • Number of points  resolution • Time between signals  ability to monitor process changes • Broadband measurements demanding in terms of data acquisition requirements • Both frequency and amplitude information retained  higher information content

  5. Summary of research • Fundamental investigations to gain an understanding of contributions to AE signals • Experimental • Finite element modelling (Manuel Tramontana) • Hertz-Zener impact theory (Dept. of Maths) •  Design of measurement system to obtain information of interest • Applications • Solid processes • Heterogeneous processes

  6. FEM - particle impact with wall Manuel Tramontana, University of Strathclyde

  7. Factors that affect signal • Transducer • Response characteristics • Position • Attachment • Vessel • Shape • Size • Material • Sample • Particle size • Particle concentration • Impact velocity • Impact position • Material properties, e.g. density etc } important for process scale up

  8. time Impact of glass bead with plate Glass bead Matlab computer Glass plate GPIB/USB oscilloscope Transducer (up to 750 kHz)

  9. Fourier transform sum n repeats frequency time frequency Signal processing

  10. Example spectrum 1500-2000 m; 0 cm; 2.0 ms-1

  11. 1500-2000 m; 0 cm; 2.0 ms-1 Transducer response cubic spline of average of 10 spectra

  12. Sample – glass beads • Impact position • 0, 3 and 6 cm from transducer • Impact velocity • 1.4, 2.0 and 2.4 ms-1 • Particle size • 850-1000, 1200-1400 and 1500-2000 m

  13. Impact position 1500-2000 m; 1.4 ms-1

  14. Impact velocity 1500-2000 m; 0 cm

  15. Particle size - amplitude 0 cm; 1.4 ms-1

  16. Particle size - frequency 0 cm; 1.4 ms-1

  17. 2.4 ms-1 2.0 ms-1 1.4 ms-1 Signal area

  18. 1.4 ms-1 2.0 ms-1 2.4 ms-1 % signal area

  19. Vessel shape and size • 1 L pyrex glassware • Beaker, bath, conical flask and round bottom flask • Pyrex beakers • 50, 250 and 600 mL and 1, 3, 5 and 10 L

  20. Impact of glass bead with vessel Glass bead Matlab computer GPIB/USB oscilloscope Transducer (up to 750 kHz)

  21. Vessel shape – 1 L 1500-2000 m; 0 cm; 2.0 ms-1

  22. Vessel size 1500-2000 m; 0 cm; 2.0 ms-1

  23. Process scale up • Beaker size • 50 mL, 1 L and 20 L • Particle size • 850-1000, 1200-1400 and 1500-2000 m

  24. PCA – vessel and particle size

  25. Toffee Coffee Raisin Malteser Chocolate Orange Revels

  26. AE spectra

  27. AE spectra

  28. 2.83 g Coffee Malteser Orange 1.75-2.45 g PCA - Revels Chocolate Raisin Toffee

  29. Conclusions • Transducer response dictates shape of spectrum • Signal amplitude/area sensitive to impact position, particle size and impact velocity • Emission frequency sensitive to particle size and impact velocity • Vessel shape and size affects amplitude and frequency of acoustic emission • Different models needed for process scale up • Understanding of broadband acoustic emission signals  design of measurement system to obtain information of interest • Currently, not possible to differentiate coffee Revel from orange or Malteser!

  30. Acknowledgements • Manuel Tramontana (CUE/CPACT, University of Strathclyde) • Gillian Carson and Dr Tony Mulholland (Department of Maths, University of Strathclyde) • Yvonne Nordon • EPSRC and DTI • Royal Society

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