References of "Frisk, Erik"
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See detailFault Diagnosis Based On Causal Computations
Rosich, Albert UL; Frisk, Erik; Åslund, Jan et al

in IEEE Transactions on Systems, Man & Cybernetics : Part A (2011), 42(2), 371-381

This paper focuses on residual generation for model-based fault diagnosis. Specifically, a methodology to derive residual generators when nonlinear equations are present in the model is developed. A main ... [more ▼]

This paper focuses on residual generation for model-based fault diagnosis. Specifically, a methodology to derive residual generators when nonlinear equations are present in the model is developed. A main result is the characterization of computation sequences that are particularly easy to implement as residual generators and that take causal information into account. An efficient algorithm, based on the model structure only, which finds all such computation sequences, is derived. Furthermore, fault detectability and isolability performances depend on the sensor configuration. Therefore, another contribution is an algorithm, also based on the model structure, that places sensors with respect to the class of residual generators that take causal information into account. The algorithms are evaluated on a complex highly nonlinear model of a fuel cell stack system. A number of residual generators that are, by construction, easy to implement are computed and provide full diagnosability performance predicted by the model. [less ▲]

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Full Text
Peer Reviewed
See detailSensor Placement for Fault Diagnosis Based On Causal Computations
Rosich, Albert UL; Frisk, Erik; Åslund, Jan et al

in Fault Detection, Supervision and Safety of Technical Processes (2009)

This work develops a methodology to solve the sensor placement problem for fault detection and isolation. The proposed methodology is suitable to handle highly non-linear and large scale systems since it ... [more ▼]

This work develops a methodology to solve the sensor placement problem for fault detection and isolation. The proposed methodology is suitable to handle highly non-linear and large scale systems since it is based on structural models. Furthermore, causality is assigned in those variable-equation relations that the variable can be computed from the equation in order to guarantee the computability of the unknown variables in the residual generation design. Finally, the developed methodology is applied on an air compressor model. [less ▲]

Detailed reference viewed: 93 (1 UL)