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Time misalignments in fault detection and diagnosis

The design of control, estimation or diagnosis algorithms most often assumes that all available process variables represent the system state at the same instant of time, However, this is never true, because of the time misalignments. Time misalignment is the unmatching of two signals due to a distortion in the time axis of one or both signals. Potential sources of time misalignments are: different time response among sensors, data communication problems, analog to digital conversion, sensor location, and so on. Fault Detection and Diagnosis (FDD) deals with the timely detection, diagnosis and correction of abnormal conditions of faults in a process. The methodology used in FDD is clearly dependent on the process and the sort of available information and it is divided in two categories: model-based techniques and non-model based techniques. This doctoral dissertation deals with the study of time
misalignments effects when performing FDD. Our attention is focused on the analysis and design of FDD systems in case of data communication problems, such as data dropout and time delays due to data transmission. Techniques based on dynamic programming and optimisation are proposed to deal with these problems. Numerical validation of the proposed methods is performed on different dynamic systems: a control position for a DC motor, a the laboratory plant and an electrical system problem known as voltage sag.