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Aim of this study is to propose fault detection and diagnosis (FDD) algorithm based on input and output residuals that consider both sensor and actuator faults separately. The existing methods which have capability of fault diagnosis and its magnitude estimation suffer from great computational complexity, so they would not be suitable for the real-time applications. The proposed method in this paper...
This paper presents a new methodology to design an instrumentation sensor network for nonlinear processes. The goal is to design a high performance and low price sensor network. The proposed approach utilizes constrained state estimation based on the unscented Kalman filter (UKF) approach to cater for some known signal information which is often either ignored or dealt with heuristically. The approach...
This paper presents an integrated design framework to utilize multi-sensor data fusion (MSDF) techniques for process monitoring enhancement to detect and diagnose sensor and process faults. Two different distributed and centralized architectures are presented to integrate the multi-sensor data based on extended Kalman filter (EKF) data fusion algorithm. The distributed integration architecture uses...
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