Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/16341
Title: Fault detection and forecast in dynamical systems
Authors: LEE SOO GUAN GIBSON
Keywords: fault detection, fault diagnosis, fault isolation, log-periodic formula, early warning system, stock market crash
Issue Date: 14-Aug-2009
Source: LEE SOO GUAN GIBSON (2009-08-14). Fault detection and forecast in dynamical systems. ScholarBank@NUS Repository.
Abstract: This thesis is divided into two parts. In the first part of the thesis, we will be looking at fault detection and diagnosis in an F-16 aircraft. Two systems are simulated: the F-16 plant to simulate a real F-16 aircraft with noise and possible actuator faults and the F-16 model to simulate an F-16 aircraft operating in the absence of noise and fault. Residual characteristics are extracted using the output of the two systems. These residual characteristics are processed to identify faults in the system.In the second part of the thesis, crashes in the stock markets are studied. Two different approaches for crash forecast are proposed: the technical approach and the indicator approach. The technical approach involves using a log-periodic formula to determine the crash time of a stock index. The indicator approach involves determining the relevance of various economic, real sector and commodity indicators to stock market crashes.
URI: http://scholarbank.nus.edu.sg/handle/10635/16341
Appears in Collections:Master's Theses (Open)

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