A review of electro-hydraulic servovalve research and development

This paper provides a review of the state of the art of electro-hydraulic servovalves, which are widely used valves in industrial applications and aerospace, being key components for closed loop electrohydraulic motion control systems. The paper discusses their operating principles and the analytical models used to study these valves. Commercially available units are also analysed in detail, reporting the performance levels achieved by current servovalves in addition to discussing their advantages and drawbacks. Adetailed analysis of research that investigates these valves via computational fluid dynamic analysis is also provided. Research studies on novel control systems and novel configurations based on the use of smart materials, which aim to improve performance or reduce cost, are also analysed in detail.</p

A review of electro-hydraulic servovalve research and development

This paper provides a review of the state of the art of electro-hydraulic servovalves, which are widely used valves in industrial applications and aerospace, being key components for closed loop electrohydraulic motion control systems. The paper discusses their operating principles and the analytical models used to study these valves. Commercially available units are also analysed in detail, reporting the performance levels achieved by current servovalves in addition to discussing their advantages and drawbacks. Adetailed analysis of research that investigates these valves via computational fluid dynamic analysis is also provided. Research studies on novel control systems and novel configurations based on the use of smart materials, which aim to improve performance or reduce cost, are also analysed in detail.</p

Optimal Material Selection for Transducers

When selecting an active material for an application, it is tempting to rely upon prior knowledge or commercial products that fit the design criteria. While this method is time effective, it does not provide an optimal selection. The optimal material selection requires an understanding of the limitations of the active material, understanding of the function, constraints and objectives of the device, and rigorous decision making method to ensure rational and clear material selection can be performed. Therefore, this work looks into the three most researched active materials (piezoelectrics, magnetostrictives and shape memory alloys) and looks at how they work and their difficulties. The field of piezoelectrics is vast and contains ceramics, plastics and cellular structures that couple the mechanical and electrical domain. The difficulty with piezoelectric ceramics is their small strains and the dependence of their coefficients on the ferroelectric domains. Giant magnetostrictives materials couple the mechanical and magnetic domains. They are generally better suited for low-frequency operations since they properties deteriorate rapidly with heat. Shape memory alloys are materials that couple thermal and mechanical domains. They have large strain but are limited in their force output, fatigue life and cycle frequency. Optimal material selection requires a formalized material selection method. In mechanical material selection, the formal material selection method uses function, constraints and objectives of the designer to limit the parameter space and allow better decisions. Unfortunately, active materials figures of merit are domain dependent and therefore the mechanical material selection method needs to be adapted. A review of device selection of actuators, sensors and energy harvesters indicates a list of functions, constrains and objectives that the designer can use. Through the analysis of these devices figures of merit, it is realized that the issue is that the simplification that the figures of merit perform does not assist in decision making process. It is better to use decision making methods that have been developed in the field of operational research which assists complex comparative decision making. Finally, the decision making methods are applied to two applications: a resonant cantilever energy harvester and an ultrasound transducer. In both these cases, a review of selection methods of other designers provides guidance of important figures of merit. With these selection methods in consideration, figures of merit are selected and used to find the optimal material based upon the designer preference

Smart Materials and Devices for Energy Harvesting

This book is devoted to energy harvesting from smart materials and devices. It focusses on the latest available techniques recently published by researchers all over the world. Energy Harvesting allows otherwise wasted environmental energy to be converted into electric energy, such as vibrations, wind and solar energy. It is a common experience that the limiting factor for wearable electronics, such as smartphones or wearable bands, or for wireless sensors in harsh environments, is the finite energy stored in onboard batteries. Therefore, the answer to the battery “charge or change” issue is energy harvesting because it converts the energy in the precise location where it is needed. In order to achieve this, suitable smart materials are needed, such as piezoelectrics or magnetostrictives. Moreover, energy harvesting may also be exploited for other crucial applications, such as for the powering of implantable medical/sensing devices for humans and animals. Therefore, energy harvesting from smart materials will become increasingly important in the future. This book provides a broad perspective on this topic for researchers and readers with both physics and engineering backgrounds

From data acquisition to data fusion : a comprehensive review and a roadmap for the identification of activities of daily living using mobile devices

This paper focuses on the research on the state of the art for sensor fusion techniques, applied to the sensors embedded in mobile devices, as a means to help identify the mobile device user’s daily activities. Sensor data fusion techniques are used to consolidate the data collected from several sensors, increasing the reliability of the algorithms for the identification of the different activities. However, mobile devices have several constraints, e.g., low memory, low battery life and low processing power, and some data fusion techniques are not suited to this scenario. The main purpose of this paper is to present an overview of the state of the art to identify examples of sensor data fusion techniques that can be applied to the sensors available in mobile devices aiming to identify activities of daily living (ADLs)