Date of Graduation
Statler College of Engineering and Mineral Resources
Chemical and Biomedical Engineering
Charter D Stinespring
Stephen E Zitney
The goal of this work is to help synthesize a sensor network to detect and diagnose faults and to monitor conditions of the key equipment items. The desired algorithm for sensor network design would provide information about the number, type and location of sensors that should be deployed for fault diagnosis and condition monitoring of a plant. In this work, the focus was on the integrated gasification combined cycle (IGCC) power plant where the faults at the equipment level and the plant level are considered separately. At the plant level, the objective is to observe whether a fault has occurred or not and identify the specific fault. For component-level faults, the objective is to obtain quantitative information about the extent of a particular fault. For the model-based sensor network design, high-fidelity process model of the IGCC plant is the key requirement.;For component level sensor placement, high-fidelity partial differential algebraic equation (PDAE)-based models are developed. Mechanistic models for faults are developed and included in the PDAE-based models. For system-level sensor placement, faults are simulated in the IGCC plant and the dynamic response of the process is captured. Both the steady-state and dynamic information are used to generate markers that are then utilized for sensor network design.;Whether faults in a particular equipment item should be considered at the unit level or system level depend on the criticality of the equipment item, its likelihood to failure, and the resolution desired for specific faults. In this work, the sour water gas shift reactor (SWGSR) and the gasifier are considered at the unit level. Fly ash may get deposited on the SWGSR catalyst and in the voids in the SWGSR resulting in decreased conversion of carbon monoxide. A MATLAB-based PDAE model of the SWGSR has been developed that considers key faults such as changes in the porosity, surface area, and catalyst activity. In a slagging gasifier, the molten slag that flows along the inner wall can penetrate into the refractory layer, and due to chemical corrosion and thermal and mechanical stress eventually result in thinning or spalling of the refractory. Extent of penetration of slag into the refractory wall and the spalling of the refractory are considered to be important variables for condition monitoring of the gasifier. In addition, as an increasing slag layer thickness can eventually lead to shutdown of the gasifier yet the slag layer thickness cannot be directly measured using the current measurement technology, slag layer thickness is also considered to be an important variable for condition monitoring. For capturing the slag formation, and detachment phenomena accurately, a novel hybrid shrinking core-shrinking particle (HSCSP) model is developed. For tracking the detached slag droplets and the char particles along the gasifier, a particle model is developed and integrated with the HSCSP model. A slag model is developed that captures the process of the detachment of the slag droplets from the char surface, transport of the droplets towards the wall, deposition of a fraction of the droplets on the wall and formation of a slag layer on the wall. Finally, a refractory degradation model is developed for calculating the penetration of the slag inside the wall and the size and time for a spall to occur due to the combined effects of volume change as a result of slag penetration as well as thermal and mechanical stresses.;System-level models are enhanced and faults are simulated spanning across various sections of the IGCC plant. For example, in the SELEXOL-based acid gas removal unit the available area in the trays of distillation columns may get reduced due to deposition of solids. This can result in loss of efficiency. Leakages in heat exchangers in this unit can result in the loss of expensive solvent or hazardous gases. In the combined cycle section, faults such as leakages and fouling in the heat exchangers, increased loss of heat through the combustor insulation that can result in loss of efficiency are simulated.;Sensor placement using a "two-tier" approach is also performed by developing a sensor network for a combined system that includes unit level as well as system level faults. A model of the gasification island is developed by integrating the SWGSR model developed in MATLAB with the model of the rest of the plant developed in Aspen Plus Dynamics. Since the two models are developed using different software platforms, an integration framework is developed that couples and synchronizes the two dynamic models. The sensor network obtained using the models developed in this work is found to be effective in observing and resolving faults both at the unit level as well as the plant level. (Abstract shortened by UMI.).
Pednekar, Pratik, "Modeling and Simulation of Components in an Integrated Gasification Combined Cycle Plant for Developing Sensor Networks to Detect Faults" (2016). Graduate Theses, Dissertations, and Problem Reports. 6393.