Fdi of Abrupt Faults with Combined Statistical Detection and Estimation and Qualitative Fault Isolation
نویسندگان
چکیده
We present a novel approach for model-based FDI of abrupt faults in process components of continuous dynamic systems. Abrupt faults refer to parameter value changes that occur much faster than the nominal process dynamics, and component faults refer to faults that correspond to physical parameters in the bond graph model of a system. These faults cause transients in system behavior. We analyze this transient response by combining statistical detection and estimation with a model-based qualitative fault isolation engine. Detection uses the discrete wavelet transform in combination with a statistical decision function. Fault isolation is based on analysis of fault signatures in a qualitative framework. We demonstrate robust detection for small faults, and robust fault isolation that becomes more precise for larger faults. Copyright c 2003 IFAC
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