Carolyn Wightman

A quantitative image analysis method for characterizing mixtures of granular materials

Abstract Automated image analysis is used to characterize the structure of undisturbed granular mixtures. These mixtures, produced from small-scale mixing experiments, are preserved using solidification techniques, sliced, and scanned using a video camera to produce a digital image. Image analysis is used to determine the mean, mode, standard deviation, variance, and skewness of local composition for a large number of locations in the mixtures, providing an effective method for performing a detailed quantitative characterization of the mixture structure. The digital data are then used to simulate random sampling from a powder blender. Sampling parameters, such as number of samples, sample size, and location of the samples, are varied to assess their effect on the descriptive statistics. For partially mixed systems such as those examined here, results depend strongly on the number of samples used in the analysis, but they are largely independent of sample size. The solidification techniques, image analysis methods, and numerical algorithms for quantifying features of the partially mixed structures are described in detail.

Mixing of granular material in a drum mixer undergoing rotational and rocking motions I. Uniform particles

Abstract The effects of flow perturbations on the extent of mixing vs. time are examined in a cylindrical vessel partially filled with uniform-sized powder mixture. Mixtures produced by pure rotational motion are compared to those undergoing rotational motion supplemented by rocking. Characterization of the mixing experiments is conducted using solidification and image analysis methods, affording visual inspection of the internal mixing patterns and evaluation of the composition distributions. Pure rotational motion causes slow axial mixing. When rotational motion is supplemented by a rocking perturbation, mixing time is greatly accelerated.

The structure of mixtures of particles generated by time-dependent flows

Abstract A computer-controlled mixing apparatus has been used to investigate the mixing of glass beads in a cylindrical vessel rotating about its axis and rocking in the vertical direction. The structures of mixtures generated in these experiments are preserved in an undisturbed state using a solidification technique. Experiments show that the motion of particles is strongly affected by end-wall effects. Mixing patterns at internal cross-sections differ significantly from patterns observed at end walls, indicating that observations at exposed surfaces are not representative of mixing processes inside the powder bed. Solidified structures are also used to compare the mixing effectiveness of different motion protocols such as varying the number of revolutions and rocking frequency. Structures generated solely by steady rotational motion exhibit very slow mixing while structures produced with simultaneous rotational and rocking motions reveal that significant mixing enhancements can be achieved when the time-periodicity of the rotational and rocking flows is disrupted.

Using flow perturbations to enhance mixing of dry powders in V-blenders

Experiments were conducted to compare mixing performance in a conventional V-blender and in a V-blender that incorporates perturbations of the particle flow by rocking the mixing vessel during rotation. Mixing was investigated using glass beads with sizes from 40 to 800 μm in vessels of approximately one liter volume. Mixture uniformity was assessed qualitatively using two different methods. One method used a transparent mixing vessel to visualize particle flow patterns and assess the state of homogeneity at the mixtures surface during the entire experiment. The second method involved solidification of the mixture by infiltration with a binder inside disposable aluminum mixing vessels. Using this method, it was possible to assess the state of the entire mixture, including its interior structure, by slicing the solidified structure after completion of each experiment. Mixture uniformity was also assessed quantitatively using image analysis to determine the composition of the solidified samples. In all cases, mixing was greatly enhanced in the rocking V-blender compared to the conventional V-blender.

Mixing of granular material in a drum mixer undergoing rotational and rocking motions : II. Segregating particles

Abstract This study examines mixtures of particles of unequal sizes in a cylindrical drum both for pure rotation and rotation with vertical rocking. These motions generate mixtures with complex patterns. Such structures are frozen in situ, sliced, and characterized quantitatively using image analysis. For short times, segregation patterns observed in these experiments differ from those anticipated from previous studies in the literature; the large particles tend to concentrate in segregated cores. For long times, the larger particles migrate to the ends of the cylinder, approaching the more commonly observed banding segregation patterns. Under some conditions, near-homogeneous structures are generated, but such systems are meta-stable; additional mixing time results in a more strongly segregated system.

Machine-vision-based evaluation of mixture percentages for powder blending processes

Quantitative analysis of the powder blending process is important in many industries, e.g. pharmaceutical, glass, food products. Inefficient blending can lead to inhomogeneous powder mixtures and unacceptable product variability. A new method has been devised by F.J. Muzzio and his students to characterize the uniformity of powder mixtures by solidifying samples of the mixtures without disturbing their structure, and subjecting them to machine vision analysis. The key components of the mixture are colored and, with appropriate illumination, the mixture percentage is directly related to video signal intensity. This paper reviews the machine vision algorithms required to perform the analysis, focussing in particular on the real-time hardware configurations that enable significant amounts of data to be collected for use in evaluation of the integrity of the blending process.