Quantitative Evaluations with 2d Electrical Resistance Tomography in the Low-Conductivity Solutions Using 3d-Printed Phantoms and Sucrose Crystal Agglomerate Assessments

Abstract

Crystallization is a significant procedure in the manufacturing of many pharmaceutical and solid food products. In-situ electrical resistance tomography (ERT) is a novel process analytical tool (PAT) to provide a cheap and quick way to test, visualize, and evaluate the progress of crystallization processes. In this work, the spatial accuracy of the nonconductive phantoms in low-conductivity solutions was evaluated. Gauss–Newton, linear back projection, and iterative total variation reconstruction algorithms were used to compare the phantom reconstructions for tap water, industrial-grade saturated sucrose solution, and demineralized water. A cylindrical phantom measuring 10 mm in diameter and a cross-section area of 1.5% of the total beaker area was detected at the center of the beaker. Two phantoms with a 10-mm diameter were visualized separately in noncentral locations. The quantitative evaluations were done for the phantoms with radii ranging from 10 mm to 50 mm in demineralized water. Multiple factors, such as ERT device and sensor development, Finite Element Model (FEM) mesh density and simulations, image reconstruction algorithms, number of iterations, segmentation methods, and morphological image processing methods, were discussed and analyzed to achieve spatial accuracy. The development of ERT imaging modality for the purpose of monitoring crystallization in low-conductivity solutions was performed satisfactorily.

Monitoring and Visualization of Crystallization Processes Using Electrical Resistance Tomography: CaCO3 and Sucrose Crystallization Case Studies

“…Effective use of such images is critically reliant on the choice of reconstruction parameters and the flexibility to change them quickly. We systematically studied such parameters for analyzing non-conductive materials in the low conducting media [25]. For cylindrical chemical batch crystallization reactors, a conventional parameterization approach relies on testing and comparing the number of iterations, finite element model mesh structure, hyperparameter values, and tolerances, using simulations and phantoms.…”

“…The final results determining accurate yield estimation and solid concentration distributions within the region of interest can be affected by variation in the parameters for image reconstruction or image segmentation. The quantitative evaluation of the crystallization progress and the factors affecting crystallization monitoring using ERT have been discussed extensively [24,25]. It was shown that multiple factors such as sensor size, reconstruction technique, conductivity of the solution under evaluation, elements in the Finite Element Model (FEM) mesh, and the image processing method utilized all affected the quantitative evaluation of the non-conductive regions.…”

A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows

“…Both speed and spatial resolution are important to capture the relevant dynamics of the separation inside ISS in real time. Previous works based on the correction of the lightphase core size measured by the sensor via calibration against a camera were successful in increasing the accuracy of the ERT system for non-iterative schemes [30,31], and approaches relying on artificial intelligence and machine learning are also present in literature [32]. However, there is still a mismatch between the flow time scales and the temporal resolution of the ERT with the correction.…”

Real-Time Fault Detection and Diagnosis of CaCO3 Reactive Crystallization Process by Electrical Resistance Tomography Measurements

“…Electrical resistance tomography (ERT) is one of the fast-evolving tomographic modalities used to characterize a process through quantifying the electrical field of the medium. The fast growth of ERT is mostly due to the economic aspects, the relative simplicity of implementation, and the potential for sub-millisecond temporal resolution [16]. On the other hand, among the main disadvantages is the data acquisition rate, which affects the image reconstruction time; noise generation is highly correlated to measurement speed, therefore, undesirably impacting the image quality [17].…”

“…On the other hand, among the main disadvantages is the data acquisition rate, which affects the image reconstruction time; noise generation is highly correlated to measurement speed, therefore, undesirably impacting the image quality [17]. Furthermore, the inherent nonlinearity of both the conductivity measurement and the inverse algorithms limits the spatial resolution of the electrical tomography technique to approximately 2-5% of the reactor diameter [13,16].…”