The use of automated image analysis can provide actual sieve size results on a large aliquot of powder without any prior correlation with actual sieve data.
Functioning automated image analyzer for measuring sieve sizes.
Sieve size analysis is a well-known and important tool for
the characterization of powders over a wide range of materials and
applications. Everything from ground coffee to abrasive material is priced and
sold based on measured sieve fractions, and many reference methods require the
use of sieves.
Though sieve size analysis has been around
for thousands of years, it is still in wide use for a number of reasons. First,
it is a simple and inexpensive tool. No complicated sample preparations are
needed beyond simply pouring the powder into the top sieve. Secondly, sieves
can test large amounts of powder-literally hundreds of grams. In contrast, many
of the more modern and high-tech particle sizing methods, like laser light
scattering, might ascertain particle size from just micrograms or milligrams of
material. The statistical accuracy of sieve data will therefore be much better.
Finally, sieves directly provide mass-weighted particle size distributions,
something that no other technique can do.
Unfortunately, the use of sieves is very labor-intensive and involves long
measurement times (after the powder is added, vibratory energy must be applied
and each sieve has to be reweighed, cleaned
and dried). In addition, sieving can be very problematic for fragile powders
because the vibratory energy required to separate the particles can also
fracture them and cause the size distribution to change. Another disadvantage
with sieve size analysis is that the sieving time is one of several factors
that can significantly affect the final results and must be controlled. As a
result, the accuracy of sieving results can be dependent on the skills of the
operator. Furthermore, the long measurement times preclude the use of sieve
size analysis as a process monitoring tool.
With the development of digital image capture technology and inexpensive and
fast desktop computing, a new instrumental solution now exists that enables
statistically accurate and fast sieve size measurements. Process engineers can
monitor powder particle size on- or at-line and obtain much-improved control
over the specifications of their final powder product.
Figure 1. Air flow carries particles past the camera
in a controlled orientation.
Developing an Automated Solution
When properly implemented, the use of automated image
analysis (IA) can provide actual sieve size results on a large aliquot of
powder without any prior correlation with actual sieve data. Three issues had
to be addressed when determining how to implement this solution. The first
challenge was introducing the powder particles to the camera in a way that was
fast and produced images of the particles in controlled orientations.
It is important to know that automated image analysis tools have two common
The first configuration, dynamic image
analysis (DIA), uses a conveyor belt or vibratory feeder to drop powder in
front of the camera. Because the particles are under the control of gravity,
only a moderate amount of material can be imaged and the orientation of the
particles cannot be controlled as they fall. Thus, it is possible for
flake-like particles that might normally be captured in a smaller (larger-sized)
mesh sieve to be imaged from a dimension that would suggest a smaller size. The
second configuration is that of static image analysis (SIA), where particles
are introduced to the camera after dispersal on an optical surface. While this
method provides exact orientation control, only a minute amount of material is
The new solution combines these two
configurations to capitalize on their individual advantages. The powder is
introduced to the camera by a laminar horizontal air flow that passes between
two closely spaced glass windows (see Figure 1). The air flow is produced by a
simple vacuum pump. Due to the laminar flow conditions and significant
acceleration, particles are oriented with their largest surface facing the
camera at the instant of image capture. The use of a telecentric lens produces
a large depth of field that aids in keeping all of the particles in focus,
thereby maximizing detail. The particle containment design ensures that the
electronics, optics and other components are not contaminated, and allows the
operator to run hundreds of analyses without any cleaning. In addition, the
particles achieve such a speed that up to 500 g of material can be imaged per
The second issue was to define a size parameter that would produce results that
match with sieve size analysis. It may come as a surprise to those unfamiliar
with particle size analysis that particle size or particle diameter is a not a
well-defined parameter (except for spherical particles); in reality, many definitions
Most particle size analyzers do not measure
particle size directly. Instead, they measure a physical property of the
particle that is related to size, like sedimentation in a liquid, the
scattering of light, and so on. Particle size is then defined relative to the
measured physical property, so a particle might sediment like a 60-micron
sphere, scatter light like an 80-micron sphere, or fit through a 300-mesh
2. Particle size can be defined in different ways, including A, maximum size;
B, equivalent disc diameter; and C, sieve diameter.
Unlike most other particle sizing technologies, image
analysis provides a direct measure of particle size. It is similar in this
regard to sieve size analysis, which also selects directly based on size. All
that is required to generate sieve-type data through image analysis is to
correctly define the size of the particle based on its image. As can be seen in
Figure 2, once one has a picture of the particle, the size of that particle can
be defined in a variety of ways. For example, size can be defined as the
greatest distance between two points on the particle perimeter, the so-called
maximum size or maximum distance. One can also define particle size as the
diameter of a sphere that has the same area as the imaged particle, the equivalent
disc diameter, and so on.
If we think about how sieves actually select for size, we can conceive of a
particle diameter that is equal to the size of the largest sphere that fits
within the measured perimeter of the particle (see C in Figure 2). We can call
this the sieve diameter. It is easy to see that this size, directly measured
from the image data, can provide a well-defined particle size that will produce
data that should match sieve size analysis.
The final piece of the puzzle was to properly estimate the particle volume in
order to infer a mass distribution. In sieve size analysis, this is done
directly by weighing the amount of material in each sieve fraction. It presents
a special problem for image analysis, however, as only two dimensions of each
particle are measured. From stereological theory, we know that the volume of an
object is proportional to its projected area. Though it cannot help us measure
the absolute particle volume, we can use this information to determine the
relative volume of the particles, which in turn allows us to produce a mass
distribution (assuming uniform density). The volume estimator is based on the
measured area of the particle and a specially defined mean diameter.
Table 1. Mass distribution certified by sieve size analysis for BCR-sand 68 (100 grams).
Achieving Accurate Data
How does this combination of fast and oriented particle
introduction to the digital camera, carefully
selected definition of particle size, and volume fraction estimator work in
terms of producing accurate sieve size data? A working version of the device is
shown in the lead image. Powder is loaded into the vibratory feeder on the
left. The powder drops into the air stream, which moves through the
rectangular-shaped pipe. The light source (monochromatic collimated blue light
for best resolution) is mounted underneath the pipe and protected by a
removable glass window. The digital camera and telecentric lens, positioned above
the light source, are also protected by a removable glass window.
To determine whether the method would provide accurate and precise sieve data,
a 100-g aliquot of BCR 68 (a quartz material distributed by the Community
Bureau of Reference for use as a sieve size analysis standard) was tested. The
mass distribution was certified by sieve size analysis at five separate
laboratories and can be seen in Table 1.
Figure 3. Comparison of image analysis and sieve size
analysis on BCR 68.
Figure 3 contains the
results from each of the five sieve analyses, along with the IA results. The
agreement is excellent and within the certified standard deviation. Again, it
should be emphasized that the IA data was derived directly from the images of
the particles; the measured sizes were not re-calibrated. Furthermore, the
measurement was made over several minutes, less time than it would take just to
clean a comparable set of sieves.
4. Comparison of multiple runs of an alumina powder.
analysis is repeatable as well. Two 150-g aliquots of a refined alumina powder
were tested next, and the results are graphed in Figure 4. The data demonstrate
that, if done properly, image analysis can provide both accurate and precise
sieve results-and much more quickly than actual sieve size analysis. With image
analysis, engineers can access real-time sieve results for use in process
For more information, contact Particle Sizing Systems, 8203 Krystel
Circle, Port Richey, FL 34668; (727) 846-0866; fax (727) 846-0865; e-mail firstname.lastname@example.org; or visit www.pssnicomp.com.