With the increasing move to more electric systems in aircraft, ships and automobiles, there is a need to ensure that electromechanical actuators are designed to satisfy the conflicting specifications of low cost, low volume/weight, high performance and requiring little maintenance. The conclusion of the more for less design philosophy is that power electronic motor drives will be work harder, in harsher environments, for longer periods of time. Scheduled maintenance periods will be longer, and therefore it is imperative that drives, especially those used for safety critical applications will employ prognosis and diagnosis algorithms as part of their basic control structure, to predict and prevent in-service failure. The work proposed here will investigate the production of new signatures for indicating the condition of a motor drive and its load, and also determine how these signatures can be used to determine the type and severity of a fault. The aim is to embed the condition monitoring into the normal operation of an electromechanical actuator, in order to detect and distinguish between faults in the electrical machine, the power converter and the mechanical system.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Autonomous robots, capable of independent and intelligent navigation through unknown environments, have the potential to significantly increase human safety and security. They could replace people in potentially hazardous tasks, for instance search and rescue operations in disaster zones, or surveys of nuclear/chemical installations. Vision is one of the primary senses that can enable this capability, however, visual information processing is notoriously difficult, especially at speeds required for fast moving robots, and in particular where low weight, power dissipation and cost of the system are of concern. Conventional hardware and algorithms are not up to the task. The proposal here is to tightly integrate novel sensing and processing hardware, together with vision, navigation and control algorithms, to enable the next generation of autonomous robots. At the heart of the system will be a device known as a 'vision chip'. This bespoke integrated circuit differs from a conventional image sensor, including a processor with each pixel. This will offer unprecedented performance. The massively parallel processor array will be programmed to pre-process images, passing higher-level feature information upstream to vision tracking algorithms and the control system. Feature extraction at pixel level results in an extremely efficient and high speed throughput of information. Another feature of the new vision chip will be the measurement of 'time of flight' data in each pixel. This will allow the distance to a feature to be extracted and combined with the image plane data for vision tracking, simplifying and speeding up the real-time state estimation and mapping capabilities. Vision algorithms will be developed to make the most optimal use of this novel hardware technology. This project will not only develop a unique vision processing system, but will also tightly integrate the control system design. Vision and control systems have been traditionally developed independently, with the downstream flow of information from sensor through to motor control. In our system, information flow will be bidirectional. Control system parameters will be passed to the image sensor itself, guiding computational effort and reducing processing overheads. For example a rotational demand passed into the control system, will not only result in control actuation for vehicle movement, but will also result in optic tracking along the same path. A key component of the project will therefore be the management and control of information across all three layers: sensing, visual perception and control. Information share will occur at multiple rates and may either be scheduled or requested. Shared information and distributed computation will provide a breakthrough in control capabilities for highly agile robotic systems. Whilst applicable to a very wide range of disciplines, our system will be tested in the demanding field of autonomous aerial robotics. We will integrate the new vision sensors onboard an unmanned air vehicle (UAV), developing a control system that will fully exploit the new tracking capabilities. This will serve as a demonstration platform for the complete vision system, incorporating nonlinear algorithms to control the vehicle through agile manoeuvres and rapidly changing trajectories. Although specific vision tracking and control algorithms will be used for the project, the hardware itself and system architecture will be applicable to a very wide range of tasks. Any application that is currently limited by tracking capabilities, in particular when combined with a rapid, demanding control challenge would benefit from this work. We will demonstrate a step change in agile, vision-based control of UAVs for exploration, and in doing so develop an architecture which will have benefits in fields as diverse as medical robotics and industrial production.

Wireless sensor networks are more and more seen as a solution to large-scale tracking and monitoring applications. The deployment and management of these networks, however, is handled by a central controlling entity and the sensor network is often dedicated to a single application. We argue that this is due to the fact that we do not yet have the means to deal with a secure multi-purpose federated sensor network, running different applications in parallel and able to reconfigure dynamically to run others.The communication paradigms which have been usually devised for small and single owner sensor networks simply do not have the right scalability, security, reconfigurability characteristics required for this environment.With FRESNEL we aim to build a large scale federated sensor network framework with multiple applications sharing the same resources. We want to guarantee a reliable intra-application communication as well as a scalable and distributed management infrastructure. Orthogonally, privacy and application security should also be maintained.We evaluate our proposal though a large scale federation of sensor networks over the Cambridge campus. The sensors monitor different aspects (temperature, pollution, movement, etc) and the network will be running various applications belonging to different authorities in the city.

BAE Systems with the support of EPSRC have launched a challenge to universities to develop novel technologies that can be applied to new and aspirational aircraft programmes. In particular, the Persistent Green Air Vehicle (PERGAVE) concept is a future unmanned air vehicle (UAV), not yet an aircraft design, which can sustain missions of at least months' and ultimately more than a year's duration. In this respect, PERGAVE is a highly flexible HALE (High Altitude Long Endurance) aircraft, with vibration and aeroelastic characteristics specific to each PERGAVE design concept. Methodologies have been developed by NASA to predict flight dynamics of HALE aircraft. An operational profile such as this will require extremely low energy demands from on-board systems to meet both the endurance and environmental targets. It will also require comprehensive condition monitoring of structures and systems (e.g. vibration and loading) as well as environmental parameter measurement (e.g. temperature, ionizing radiation levels and doses) to allow operators to assess the viability of the aircraft at every stage of its mission. This project will respond to the PERGAVE challenge by developing energy harvesting powered wireless data links and real time condition and environmental sensor nodes in an integrated smart composite airframe structure for monitoring. The nodes will operate in an energy autonomous manner, without the need for power supplies or batteries and therefore it is truly energy autonomous. The research has the following five work packages: WP1: Requirement capture and study of the system design specifications and architecture WP2: Integration of the energy harvesting element into the composite structure WP3: Multiphysical modelling and simulation for optimisation of the whole system WP4: Development of low power consumption wireless sensor nodes WP5: Testing of the technology demonstrator The WPs will specifically target design and demonstration of a deployable real time energy autonomous wireless sensing communication systems that can be used for structural health monitoring and environmental parameter measurement aligned to the next generation, unmanned air vehicle programme in BAE Systems. Uniquely in the UK, this work will take a system level specification and design approach combining optimisation with novel energy harvesting technology designed for flexible deployment in manufactured composite structures with wireless sensing, which are all integrated in a novel energy and power management architecture. This provides end-to-end capability that will be suitable not only for the PERGAVE vehicle but also for other applications requiring remote asset condition monitoring in harsh environments (e.g. off-shore wind farms). The principal novelty of the project lies in the implementation of combined materials and structures design, optimisation and manufacturing processes, our enhanced energy harvesting technology and efficient energy-aware and energy-flow control mechanism, which has the potential to be prototyped as a self-powered, light weight and wireless health monitoring system for future air vehicles. The research will build on investigator track records on energy harvesting with wireless sensing, sensors and aerospace monitoring, and composite manufacturing at Cranfield University, aircraft and composite structural modelling and optimization at Lancaster University, and ionizing radiation monitoring at the University of Central Lancashire to undertake this timing and challenging project. The project partners are BAE Systems in Military Air&Information and Advanced Technology Centre, AgustaWestland Ltd, TRW, dstl, EPSRC National Centres for Innovative Manufacturing in Through-life Engineering Services. These partners represents aerospace, defence and automotive sectors. There are Aerospace, Aviation & Defence KTN and Zartech organisations as dissemination partners to support the impact activities.