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Online Model Based Fault Diagnosis with a Case Study of Belt Conveyor System

In this paper, some recent advancement made in the field of model based fault identification are elucidated and shown that bond graph modeling is well suited to solve fault detection and isolation problems in automated real time process engineering supervision systems. We present a case study and implement an online fault diagnosis scheme through parameter estimation to a belt conveyor system. Bond graph modeling, which is a unified tool for multi-energy domain system representation, is used to model the belt conveyor system. Moreover, the fault indicators are derived from the bond graph model and fault signatures are obtained by direct exploitation of causal path information from the bond graph model. Thereafter, the model simulation with a fault is carried out in MATLAB-Simulink environment to study the inverse dynamics and estimation of parameters. A singularity problem in estimation of belt stiffness coefficient is addressed and solved with pragmatic assumption.