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Fault detection for linear parameter varying systems under changes in the process noise covariance
(2020)
Detecting changes in the eigenstructure of linear systems is a comprehensively investigated subject. In particular, change detection methods based on hypothesis testing using Gaussian residuals have been developed previously. In such residuals, a reference model is confronted to data from the current system. In this paper, linear output-only systems depending on a varying external physical parameter are considered. These systems are driven by process noise, whose covariance may also vary between measurements. To deal with the varying parameter, an interpolation approach is pursued, where a limited number of reference models – each estimated from data measured in a reference state – are interpolated to approximate an adequate reference model for the current parameter. The problem becomes more complex when the different points of interpolation correspond to different noise conditions. Then conflicts may arise between the detection of changes in the eigenstructure due to a fault and the detection of changes due to different noise conditions. For this case, a new change detection approach is developed based on the interpolation of the eigenstructure at the reference points. The resulting approach is capable of change detection when both the external physical parameter and the process noise conditions are varying. This approach is validated on a numerical simulation of a mechanical system.
Alkali-activated materials are ideal for the repair of concrete structures in harsh environmental conditions due to their high durability in chemically aggressive environments. However, slag-based mortars, in particular, are prone to shrinkage and associated cracks. In this respect, the application of steel fibres is one solution to reduce the formation of shrinkage induced cracks and to improve post cracking behaviour of these mortars. This study investigated the influence of two different types of steel fibres on the tensile properties of two alkali-activated mortars. Direct tensile tests and single fibre pull-outs were performed to analyse the determining failure modes both on macro and micro scale. Mechanical testing was accompanied by non-destructive testing methods such as digital image correlation and acoustic emission for a detailed analysis of the fracture process.