Tuned mass dampers (TMD) have been widely used in passive vibration control, but their main disadvantage is that the vibration reduction effect may be greatly affected by the natural frequency of the main structure. In order to solve this limitation, we designed a frequency adjustable tuned mass damper (FATMD) based on a magneto rheological elastomer (MRE), which is a new type of magneto rheological smart material, with adjustable stiffness, obtained by changing the magnetic induction. We used MRE to change the stiffness of FATMD to track the natural frequency of the main structure. However, adding TMD will change the natural frequency of the system. Therefore, we combined Hilbert–Huang transform (HHT) and a natural excitation technique (NExT), with Simulink/dSPACE, to identify the natural frequency of the system in real time, and then calculated the natural frequency of the main structure through the TMD optimal design theory. This can help adjust FATMD to its optimum tuning state. To verify the applicability and effectiveness of FATMD, this paper compares the FATMD and traditional TMD experimental results. The natural frequency of steel beams can be changed by adding mass blocks. The experimental results indicate that FATMD, using the frequency tracking method, can effectively track the natural frequency of the main structure to ensure that the system is always in the optimum tuning state. In addition, FATMD can still achieve a good vibration reduction effect when the natural frequency of the main structure changes.
Due to the difficulty in adopting the conventional centralized control method for seismic response control of high-rise buildings with complex structures and large sizes, the decentralized control method is applied. The challenge is that the control model of the high-rise structure divided into multiple subsystems changes as large nonlinear deformation under strong earthquakes. Therefore, with an application of the long short-term memory neural network, the long short-term memory intelligent decentralized control method is proposed for seismic response control of high-rise buildings. On the basis of the decentralized control theory for high-rise buildings, a long short-term memory network deep-learning framework is established to construct different types of decentralized controllers, and to determine the sufficient conditions for the stability of the decentralized controllers using the Lyapunov stability theory. The long short-term memory intelligent decentralized control system of a 20-story benchmark building mode is simulated, and its fault tolerance is studied. The simulation results show that the decentralized control method can reduce the complexity of the structure model by dividing the high-rise building structure into multiple subsystems. Compared with the centralized control method, the long short-term memory intelligent decentralized control method can effectively avoid the overall failure of the control system. The long short-term memory intelligent decentralized control method can still have a satisfactory performance under sensor noise and control devices failures. This verifies that the long short-term memory intelligent decentralized control system has a better fault tolerance and can provide an innovative solution for the decentralized control of high-rise buildings.
With the increase in traffic volume and overweight vehicles, fatigue problems are highlighted. Especially for the orthotropic steel deck, the premature cracks seriously affect the service performance, operation, and service quality of the bridge. In this paper, the steel box-girder segment model and deck substructure model considering several typical fatigue cracks were established to reveal the variation law of fatigue cracks on vibration frequency and deflection under vehicle traveling load. A natural frequency analysis was performed to evaluate the change in the vibration characteristics due to localized damage, together with a dynamic analysis that considered a vehicle traveling on the bridge. The results show that the initiation and propagation of several typical cracks have little influence on the lower modes of the overall structure and great influence on the high-order modes of the substructure. The dynamic deflection response of the bridge changed under vehicle load as damage progressed. Therefore, it was possible to identify cracks of the orthotropic steel bridge deck and to provide guidance for fatigue crack detection and repair.
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