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3D Image Analysis Systems
Versus Sieving
For particle size measurement
Sieving
Sieving is an ancient size measurement technique dating
back to Roman times.
It has a number of disadvantages when compared to a
modern 3D image analysis system.
• Sieves are 1 dimensional: i.e. only measure 1 parameter
which is width/length in a specific orientation
• Results are also given in a single distribution of mass %
• Sieve analysis is time consuming – 15 to 30 minutes
(Not including result calculation)
• Operator error is common with such a repetitive task
– Sieve fractions not being collected correctly
– Misweighing of size fractions
– Data transposition errors
– Miscalculating of size distribution
• Sieves are unreliable – worn sieves result in finer
distributions
– Certification and/or replacement can be costly and is seldom
done in the recommended time frame
3D Image Analysis
• 3D Image Analysis is a fast and efficient method of
measuring particle size distribution, and has a number of
key advantages over sieving.
• Huge range of particle sizes can be measured visually
– 4 microns up to well over 120mm
• Shape parameters are recorded in addition to size
– 32 different parameters recorded in total
– Previously run samples can be remeasured with different
parameters
• 3D measurement gives length, width and thickness
• It is possible to do online analysis
• System is extremely reliable due to simple construction
• Slurries and wet suspensions are also able to be analysed
• Analysis is typically 5 to 10x faster than sieving
• Full automation ensures little to no operator error
• Automatic calibration is performed to ensure good
results
• Every particle is measured separately
• Data is easily correlated and displayed as sieve fractions
if required
• Data reporting can be customised for size and shape
parameters, for example:
– Sintered pellets: Need sphericity in addition to size
– Granular fertiliser: Need sphericity and surface roughness in
addition to size
– Reflective glass beads – Needs circularity, transparency, and
curvature in addition to very accurate size classes.
Go to
www.impautomation.com
For more information

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Advantages of 3D vision systems over sieving for particle size measurement

  • 1. 3D Image Analysis Systems Versus Sieving For particle size measurement
  • 3. Sieving is an ancient size measurement technique dating back to Roman times. It has a number of disadvantages when compared to a modern 3D image analysis system.
  • 4. • Sieves are 1 dimensional: i.e. only measure 1 parameter which is width/length in a specific orientation • Results are also given in a single distribution of mass % • Sieve analysis is time consuming – 15 to 30 minutes (Not including result calculation)
  • 5. • Operator error is common with such a repetitive task – Sieve fractions not being collected correctly – Misweighing of size fractions – Data transposition errors – Miscalculating of size distribution • Sieves are unreliable – worn sieves result in finer distributions – Certification and/or replacement can be costly and is seldom done in the recommended time frame
  • 7. • 3D Image Analysis is a fast and efficient method of measuring particle size distribution, and has a number of key advantages over sieving.
  • 8. • Huge range of particle sizes can be measured visually – 4 microns up to well over 120mm • Shape parameters are recorded in addition to size – 32 different parameters recorded in total – Previously run samples can be remeasured with different parameters • 3D measurement gives length, width and thickness
  • 9. • It is possible to do online analysis • System is extremely reliable due to simple construction • Slurries and wet suspensions are also able to be analysed
  • 10. • Analysis is typically 5 to 10x faster than sieving • Full automation ensures little to no operator error • Automatic calibration is performed to ensure good results • Every particle is measured separately
  • 11. • Data is easily correlated and displayed as sieve fractions if required • Data reporting can be customised for size and shape parameters, for example: – Sintered pellets: Need sphericity in addition to size – Granular fertiliser: Need sphericity and surface roughness in addition to size – Reflective glass beads – Needs circularity, transparency, and curvature in addition to very accurate size classes.
  • 12.