Inferential Online Measurement of 3D Fractal Dimension of Spray Fluidized Bed Agglomerates

In this work, a model-based approach to inferentially obtaining information about the 3D fractal dimension of agglomerates produced in spray fluidized beds is presented. The method utilizes high-detail but scarce offline information from X-ray microcomputed tomography for establishing and training an inferential relationship with online information that is easy and fast to obtain. The online measurement information is the geometric roundness of the single agglomerate. To investigate the interpolation capability of the inferential approach, three different strategies are evaluated: correlation with individual process conditions; correlation with parameters adjusted to process parameters; and correlation with respect to a range of process conditions. It is shown that the approach incorporating process conditions provides sufficient accuracy over a wide range of conditions. The inferential evaluation of single agglomerate 3D fractal dimension is achieved in 5 ms on average. This enables the measurement of the distribution of 3D fractal dimension in an online setting for product quality monitoring and control. Several examples illustrate the capabilities of the approach, as well as current limitations.