Input reconstruction for statistical-based fault detection and isolation



In this work, an input reconstruction scheme for detecting and isolating sensor, actuator, and process faults is proposed. The scheme uses model-based and statistical-based FDI methods, which yields an improved analysis of abnormal operation conditions in chemical processes. The main advantage of the proposed approach over existing works lies in the reconstruction of system inputs and the subsequent estimation of fault signatures. This advantage is demonstrated through simulation examples and the analysis of recorded process data from a reactive batch distillation column. © 2011 American Institute of Chemical Engineers AIChE J, 2012