The growing demand and diversity in the application of industrial composites and the current inability of present non-destructive evaluation (NDE) methods to perform detailed inspection of these composites has motivated this comprehensive review of sensing technologies. NDE has the potential to be a versatile tool for maintaining composite structures deployed in hazardous and inaccessible areas, such as offshore wind farms and nuclear power plants. Therefore, the future composite solutions need to take into consideration the niche requirements of these high-value/critical applications. Composite materials are intrinsically complex due to their anisotropic and non-homogeneous characteristics. This presents a significant challenge for evaluation and the associated data analysis for NDEs. For example, the quality assurance, certification of composite structures, and early detection of the failure is complex due to the variability and tolerances involved in the composite manufacturing. Adapting existing NDE methods to detect and locate the defects at multiple length scales in the complex materials represents a significant challenge, resulting in a delayed and incorrect diagnosis of the structural health. This paper presents a comprehensive review of the NDE techniques, that includes a detailed discussion of their working principles, setup, advantages, limitations, and usage level for the structural composites. A comparison between these techniques is also presented, providing an insight into the future trends for composites’ prognostic and health management (PHM). Current research trends show the emergence of the non-contact-type NDE (including digital image correlation, infrared tomography, as well as disruptive frequency-modulated continuous wave techniques) for structural composites, and the reasons for their choice over the most popular contact-type (ultrasonic, acoustic, and piezoelectric testing) NDE methods is also discussed. The analysis of this new sensing modality for composites’ is presented within the context of the state-of-the-art and projected future requirements.
In this paper, the results and methodology of a framework to enable run-time safety compliance and self-certification of robotics is presented. This transferable framework is verified within a practical demonstration scenario, based on asset inspection within a confined space, and representing a Beyond Visual Line of Sight (BVLOS) use case. The methodology of the framework is based on computationally efficient analysis to support run-time, front-end, data analysis and adaptive decision-making. Utilizing the Husky A200 platform, manufactured by Clearpath, front-end datasets on the mission status and diagnostics of critical sub-systems within the Husky platform are used to update run-time system ontologies. The holistic and hierarchical- relational model of the robot integrates the automata of the sensed and some non-sensed components, using prior knowledge, such as risk assessments and offline reliability data, to support run-time analysis, such as fault prognosis, detection, isolation and diagnosis. These computationally efficient data and system analyses then enable faults to be translated into failure modes that can affect decision making during the mission. With respect to challenges of a dynamic environment, namely ambient conditions or the presence of unexpected people, Frequency Modulated Continuous Wave (FMCW) sensing is integrated onto the husky platform. The FMCW supports localization in opaque environments and detection of people within and out-with of the confined space, as well as enabling integrity analysis of the infrastructure. The framework presents its results within a symbiotic digital twin of the infrastructure and robotic platform. With fully synchronized communication and data streams, the interactive digital twin provides operational decision support and trust for human in the loop operators of varying skill levels. The presentation of actionable information to the end user is used to support improvements in productivity associated with asset integrity as well as supporting user trust in safety during a BVLOS mission.
Mixed reality opens new ways of connecting users to virtual content. With simulation-based education and training (SBET), mixed reality offers an enriched environment to experience digital learning. In turn, learners can develop their mental models to process and connect 2D/3D information in real-world settings. This paper reports on the use of the Microsoft HoloLens to create a mixed reality SBET environment. The challenges of this investigation are harmonising augmented real-world content, including the use of real-time, low-latency tracking of tangible objects and the interaction of these with the augmented content. The research emphasis is on technology-mediated affordances. For example, what affordance does the HoloLens provide the leaner in terms of interactive manipulation or navigation in the virtual environment? We examine this through control-display (CD) gain in conjunction with cyber-physical systems (CPS) approaches. This work builds on previously attained knowledge from the creation of an AR application for vocational education and training (VET) of stonemasonry.
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