Adaptive structures are able to react to environmental impacts and have become a promising approach in civil engineering to improve the load-bearing behavior of buildings. Since reliability and safety of building structures are major concerns, the detection and isolation of faults are essential. In this work, the data-based distributed fault diagnosis of sensor and actuator faults in an adaptive high-rise truss structure is investigated and compared to a centralized approach. The decomposition of the different subsystems is given by the hardware layout of the different sensor systems and actuators. The mechanical structure is modeled and extended by dynamic sensor and actuator models containing different faults. Based on the simulation model, different fault scenarios are generated and used for training a convolutional neural network with dropout regularization. It is shown that the distributed approach needs less training data and yields better classification results than the centralized approach due to a significant reduction of the complexity and dimensionality.
The consumption of construction materials and the pollution caused by their production can be reduced by the use of reliable adaptive load-bearing structures. Adaptive load-bearing structures are able to adapt to different load cases by specifically manipulating internal stresses using actuators installed in the structure. One main aspect of quality is reliability. A verification of reliability, and thus the safety of conventional structures, was a design issue. When it comes to adaptive load-bearing structures, the material savings reduce the stiffness of the structure, whereby integrated actuators with sensors and a control take over the stiffening. This article explains why the conventional design process is not sufficient for adaptive load-bearing structures and proposes a method for demonstrating improved reliability and environmental sustainability. For this purpose, an exemplary adaptive load-bearing structure is introduced. A linear elastic model, simulating tension in the elements of the adaptive load-bearing structure, supports the analysis. By means of a representative local load-spectrum, the operating life is estimated based on Woehler curves given by the Eurocode for the critical notches. Environmental sustainability is increased by including reliability and sustainability in design. For an exemplary high-rise adaptive load-bearing structure, this increase is more than 50%.
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