Imaging Fluid Mixing

Wang, Mi

doi:10.1002/9781118682692.ch16

Cited by 1 publication

(1 citation statement)

References 94 publications

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“…Tomographic measurements in chemical engineering processes can generate a large amount of data from process parameters and facilitate the route towards developing: (i) pattern recognition for fault detection via machine learning algorithms and data fusion strategies [12], (ii) data-driven behavior characterization in batch processes, and (iii) humanmachine interfaces and volumetric visualization [13]. Even though the adoption of new digital and data-driven technologies has become a common practice in the aerospace and automotive industries, its pragmatic implementation in chemical processing manufacturing has not been broadly observed [14]; hence, process tomography has the potential to initiate the transition from point-based measurements to graphical visualization via big data analytics [15].…”

Section: Introductionmentioning

confidence: 99%

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

Aghajanian

Rao

Ruuskanen

et al. 2021

Sensors

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In the present research work, an electrical resistance tomography (ERT) system is utilized as a means for real-time fault detection and diagnosis (FDD) during a reactive crystallization process. The calcium carbonate crystallization is part of the carbon capture and utilization scheme where process monitoring and malfunction diagnostics strategies are presented. The graphical logic representation of the fault tree analysis methodology is used to develop the system failure states. The measurement consistency due to the use of a single electrode from a set of ERT electrodes for malfunction identification is experimentally and quantitatively investigated based on the sensor sensitivity and standard deviation criteria. Electrical current measurements are employed to develop a LabVIEW-based process automation program by using the process-specific knowledge and historical process data. Averaged electrical current is correlated to the mechanical failure of the stirrer through standard deviation evaluation, and slopes of the measured data are used to monitor the pump and concentrations status. The performance of the implemented methodology for detecting the induced faults and abnormalities is tested at different operating conditions, and a basic signal-based alarming technique is developed.

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