Factors Affecting Air Classifier Efficiency

It is also fairly well-known, that it is by far much more difficult to achieve high efficiency with dry classifying than with wet. Hence, it is highly desirable to create conditions for improving the dry air classifying methods, so that the high energy consumption associated with producing fine dry powders can be minimized.

Particle Size Distribution: The classifier feed particle size distribution has a very strong influence on the efficiency. In general, if the size cut is coarser than about 40 microns, classification is relatively easy. For size separation below 40 microns, there can be great differences in performance depending on the classifier design and construction. If particle trajectories are crossing over or interfere with each other for other reasons, a poor classification will result.

Should the amount of finished fine size product in the feed be relatively small, some classifiers will have difficulty in recovering this fraction. For example, if the portion of fines is on the order of 20 to 25% below 10 microns, many classifiers would be too inefficient to recover a -10 micron product. This is one of the distinct differences between the new classifier and other types. The INPROSYS classifier provides a high classification efficiency even in such cases.

As an example, in a cement grinding application, where the classifier feed contained 25% -10 micron, the INPROSYS classifier was able to produce a -10 micron product at 65% efficiency. The level of efficiency decreases with the desired cut point, of course. Even in an extreme case, such as producing feldspar with 3 micron top size and only 10% of this fraction in the feed, the INPROSYS classifier operated at 35% efficiency, considerably higher than any other device tried for this application.

Particle Density Distribution: A majority of industrial mineral fine classifying applications have particle densities in the range 2.5 – 3.0 g/cc. There are some metal compound applications with greater particle densities and the classifying efficiency will be then be affected as discussed below.

Let us first consider the two dominant force factors involved: the inertia force called the centrifugal force and the air drag force. The centrifugal force (Fc) is defined by:

Fc = m x v²/r = Vp x Pp x v²/r……………………………………………….(A.2.1)

where:

Vp – volume of the particle
Pp – density of the particle
m – mass of the particle
v – peripheral speed of the rotor
r – rotor radius

The air drag force (Fd) can be defined from the formula:

Fd = cx x γ x A x va²/2………………………………………………………(A.2.2)

where:

cx – resistance coefficient
γ – fluid density (combination of air and material density)
A – cross section area of the particle
va – air velocity

As can be seen, the centrifugal force is proportional to the square of the rotor rotational velocity and the air drag force is proportional to the square of the air flow velocity. Since the centrifugal force is directly proportional to the particle density, it has less effect on the separation force than the other factors. Only when very heavy or very light materials are involved, would there be a significant factor to consider. For example, for nickel powder (8.9 g/cc), tungsten carbide (about 14 g/cc), iron powder (7.8 g/cc) and other heavy materials, the classification cut point can be much lower than for low-density materials (most in the range 2.5-3.0 g/cc, carbon 1.3 g/cc).

In some special cases, separation between different density materials may be achieved, if the feed size is in a narrow range. In practice, the difference in density would need to be at least a factor of 2:1 in order to achieve a gravity separation in a classifier.

Particle Shape: The factor cx is dependent on the particle shape. Therefore, the air drag force will be affected by the particle shape. As the factor can range from 0.1 for oval particles, 0.5 for spherical and up to 1.1 for flaky materials [1], it is clear that the shape has very significant effect. In addition, the cx factor is also dependent on the Reynold’s number (Re), which is determined by the gas velocity, viscosity and particle size.

For flaky materials, the effect is also dependent on their orientation in the gas flow. As such particles can behave rather erratically when dispersed in air, different cx values will result even though the particle shape is the same. If two-dimensional particles are oriented along the flow direction, the tendency would be for such particles to report to the coarse fraction. If the particle is oriented perpendicular to the air stream, it would tend to report to the fine fraction.

Electrostatic Forces: Triboelectric charging occurs when the materials are conveyed to and from the classifiers. Some materials charge more easily than others, for example mica and silicon carbide. By ensuring that conveying surfaces are conductive and by keeping the paths of the feed stream and product streams well separated, as in the case of the INPROSYS classifier, the interference due to electrostatic charging can be minimized. Antistatic treatment of the feed can also substantially assist in reducing the agglomerating effect of extreme fines.

Surface Properties: The condition of particle surfaces is directly related to electrostatic charging and other phenomena affecting agglomeration. Surface modifiers including organic substances and moisture can control the degree of electrostatic charging and the level of free surface energy.

Moisture: High level of moisture (over 1%) will inevitably cause agglomeration of fine particles. If there is residual moisture in the material after grinding, pneumatic transport into the classifier can reduce the potentially adverse effect. This is an advantage of the new classifier compared to gravity fed classifiers.

Moisture levels below 0.5% usually do not cause a problem. Dry grinding generates friction heat in the mill, which reduces the moisture level. Of course, care must be taken to avoid condensation in the classifier and conveying system at start-up from cold temperatures.

 

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new air classifier increases milling capacity and reduces cost
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