Novel Sensing Networks for Intelligent Monitoring (Newton)

This proposal seeks funding for a four-year research programme to develop an autonomous, intelligent system to obtain a revolutionary solution for condition/structural health intelligent monitoring, with specific applications in condition monitoring of railways and in-service Non-Destructive Evaluation (NDE) for nuclear applications. This project addresses important goals: low cost and low power consumption sensor networks, sensor exploration, software architectures, autonomous data fusion and intelligent system management, spectrally efficient and reliable communications with novel approaches of radio frequency identification (RFID) based passive sensing networks, non-linear feature extraction and model based fusion, compressed sensing, cloud-based computing and decision making. The research will extend our knowledge in several complementary areas: low cost sensor technologies, wireless sensor network (WSN) for NDE and structural health monitoring (SHM), feature extraction and fusion, robust communication, and software architectures. The work will be undertaken jointly by cross-disciplinary research teams from Newcastle, Sheffield and York Universities, in collaboration with industrial strategic partners.

The project aims to provide a step change in condition, health and environmental monitoring by developing and applying novel intelligent autonomous technologies, in order to reduce the risk of structural failure and to achieve advanced Operation and Maintenance (O&M) strategies. The impacts of this project can be assessed in the four aspects of knowledge, economy, society, and people as outlined below.
Knowledge - The project will deliver new autonomous monitoring systems with intelligent information and infrastructure management. This will achieve scientific advances in a range of areas including sensor and WSNs, NDE and SHM, digital signal processing, and software architecture etc., which all fit in the new EPSRC's investment plan. The fundamental topics to be addressed by the project will be of interest to academics working in the priority areas of renewable energy (tidal/wave/wind), water management, and automotive/aerospace where reliability and fault diagnosis are of prime concerns.
Economy - The project addresses a number of fundamental technology development areas which are critical in the scenarios identified in the call. As a direct benefit, a demonstration system for condition monitoring of railway or nuclear plants will be established near the end of project. The research outcomes will yield knowledge transfer into other scenarios and sectors. These include, for example, the use of 'sensor-on-board' to monitor fatigue cracks, stress, and hidden corrosion in aircrafts for BAE systems and the condition monitoring of offshore wind farms. Based on the results achieved in this project, the consortium will seek further funding from TSB, ETI, and EU for further demonstration projects. Structural system developers will benefit from the project when determining their preventative and predictive O&M strategies. This is very important for the UK to lead in high value service and manufacturing in the world.
Society - The safety and reliability of industrial plants and processes will improve as the result of the introduction of SHM. Long term deployment strategies for O&M will benefit from the application of intelligent condition & health monitoring techniques developed in this project. This will lead to a safe and healthy environment so as to bring benefits to society. The improved O&M strategies also have an impact on sustainability.
People - The PDRAs and academic investigators will benefit from the research studies, obtaining new experience and knowledge, as will the industrial collaborators who will have the opportunity to become closely involved in world leading research studies. Researchers outside the consortium will also benefit from the outcomes through the project's dissemination activities. This is essentially a 'Shaping Capability' project with defined research scenarios and in close collaboration with industrial partners. Through the project and associated industrial collaborations, research 'leaders' will be 'sharper' in focus. Many emerging areas such as cloud computing and Internet of Things (IoT) will reach to a better developed states. Some PDRAs in this project may work as academics after the project finishes. This will enhance the UK academic capacity in these areas.