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Furthermore, the causal and structural properties of the bond graph model are used not only for system dynamics simulation but also to design Fault Detection and Isolation (FDI) algorithms (i.e. the generation of formal fault indicators) for online supervision of faults affecting sensors, actuators, physico-chemical components and phenomena.
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Some parameters affecting sensor response were optimized and then a calibration curve plotted.
Some parameters affecting sensor response were optimized, and a calibration curve was then plotted.
Some parameters affecting sensor response were optimized and a calibration curve was plotted.
Some parameters affecting sensor response were optimized, and a calibration curve was then plotted using differential pulse voltammetric (DPV) technique.
The simulation illustrated the impact of rogue signals negatively affecting sensor reputations which, in severe cases, shows roughly 40% of sensors penalized and eventually ignored in the shared spectrum sensing process.
A sensor failure can affect sensors in its neighborhood and compromise the network data communication.
In all the examined systems, steam content does not affect sensors' behavior and high operating temperatures (850 °C) increase the range of sensors' hydrogen measuring concentration capacity.
The residuals switch depending on the sources coupling so that the proposed FDI method is robust to the mode commutations and sensible to the offset faults that affect sensors.
This suggests that a continuous passivation is needed to protect the surface from further degradation of the passivating monolayer a problem that does not appear to appreciably affect sensors on the macroscale.
Figure 1 illustrates how directional sensing and visual occlusion can affect sensor clustering in a VSN.
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