Development of a Framework to Control and Model Based Fault Diagnosis of a Gas Transmission Network, M.Sc. Thesis Sharif University of Technology ; Bozorgmehry, Ramin (Supervisor)
Abstract
In this project a framework for Model Based Fault Diagnosis (MBFD) in a Gas Transmission Network (GTN) was developed. A black-box linear state-space model was used to capture dynamic behavior of an industrial benchmark for GTN. A full fledge commercial network simulator were used to obtain the required data for process identification. In order to check the robustness of the model zero mean white noise was imposed on various output obtained by the commercial simulator. Kalman filter was used to estimate the states of the GTN. These estimated states along with the measured output (all obtained from the commercial simulator) are almost similar to their corresponding estimated signal. This shows...
Cataloging briefDevelopment of a Framework to Control and Model Based Fault Diagnosis of a Gas Transmission Network, M.Sc. Thesis Sharif University of Technology ; Bozorgmehry, Ramin (Supervisor)
Abstract
In this project a framework for Model Based Fault Diagnosis (MBFD) in a Gas Transmission Network (GTN) was developed. A black-box linear state-space model was used to capture dynamic behavior of an industrial benchmark for GTN. A full fledge commercial network simulator were used to obtain the required data for process identification. In order to check the robustness of the model zero mean white noise was imposed on various output obtained by the commercial simulator. Kalman filter was used to estimate the states of the GTN. These estimated states along with the measured output (all obtained from the commercial simulator) are almost similar to their corresponding estimated signal. This shows...
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