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In this paper, the development of non-linear building isolation systems is overviewed. The study summarizes commonly used linear building isolation systems in two categories, which are building base isolation systems and building inter-storey isolation systems. Typical isolators including Lead-Rubber Bearings Friction Pendulum Bearings inter-storey viscous damper and Tuned Mass Damper are reviewed. The analysis and design of linear building isolation systems are also reported. After that, non-linear building isolation systems are introduced from two aspects based on their dynamic characteristics. They are (i) non-linear stiffness isolators including Quasi-Zero Stiffness isolators and Non-linear Energy Sink and (ii) non-linear damping isolators including power-law viscous dampers and magnetorheological dampers. Practical implementations of these non-linear isolators are introduced. Finally, the analysis and design of non-linear building isolation systems are discussed. Traditional equivalent linearization approaches and advanced non-linear frequency design approaches are introduced. The promising applications of the non-linear frequency design approaches to building isolation systems are also demonstrated in this review paper.

Fault detection based on data from the supervisory control and data acquisition (SCADA) system, which has been installed in most MW-scale wind turbines, has brought significant benefits for wind farm operators. However, the changes in the features of hardware sensor measurements, which are used in current SCADA systems, often cannot provide reliable early alarms. In order to resolve this problem, in this paper, a novel dynamic model sensor method is proposed for the SCADA data based wind turbine fault detection. A dynamic model representing the relationship between the generator temperature, wind speed, and ambient temperature is derived following the first principles and used as the basic structure of the model sensor. When the model sensor is applied for fault detection, its parameters are updated regularly using the generator temperature, wind speed, and ambient temperature data from the SCADA system. Then, from the updated model, the fault sensitive features of wind turbine system are extracted via performing system frequency analysis and used for the turbine fault detection. This novel model sensor method is applied to the SCADA data of a wind farm of 3 wind turbines currently operating in Spain. The results show that the proposed method can not only detect the turbine generator fault but also reveal the trend of ageing with the wind turbine generator, demonstrating its capability of failure prognosis for wind turbine system and components.

The convergence of the Volterra series representation of nonlinear systems is the fundamental requirement for the\ud analysis of nonlinear systems in the frequency domain. In the present study, a new criterion is derived to determine the\ud convergence of the Volterra series representation of nonlinear systems described by a NARX (Nonlinear Auto Regressive\ud with eXegenous input) model. The analysis is performed based on a new function known as Generalized Output Bound\ud Characteristic Function (GOBCF), which is defined in terms of the input, output and parameters of the NARX model of\ud nonlinear systems. Compared to the existing results, the new criterion provides a much more rigorous and effective\ud approach to the analysis of the convergence conditions and properties of the Volterra series representation of nonlinear\ud systems. Two case studies have been used to demonstrate the effectiveness of the new convergence analysis criterion and\ud the advantages of the new analysis over those produced by existing approaches.

This work investigates a vibration isolation energy harvesting system and studies its design to achieve an optimal performance. The system uses a combination of elastic and magnetic components to facilitate its dual functionality. A prototype of the vibration isolation energy harvesting device is fabricated and examined experimentally. A mathematical model is developed using first principle and analyzed using the output frequency response function method. Results from model analysis show an excellent agreement with experiment. Since any vibration isolation energy harvesting system is required to perform two functions simultaneously, optimization of the system is carried out to maximize energy conversion efficiency without jeopardizing the system’s vibration isolation performance. To the knowledge of the authors, this work is the first effort to tackle the issue of simultaneous vibration isolation energy harvesting using an analytical approach. Explicit analytical relationships describing the vibration isolation energy harvesting system transmissibility and energy conversion efficiency are developed. Results exhibit a maximum attainable energy conversion efficiency in the order of 1%. Results suggest that for low acceleration levels, lower damping values are favorable and yield higher conversion efficiencies and improved vibration isolation characteristics. At higher acceleration, there is a trade-off where lower damping values worsen vibration isolation but yield higher conversion efficiencies.