4 resultados para flaw detection techniques
em CORA - Cork Open Research Archive - University College Cork - Ireland
Resumo:
Various techniques and devices have been developed for the purpose of detecting wildlife but many only provide optimum results in particular habitats, for certain species or under ideal weather conditions. It is therefore advantageous to understand the efficiency and suitability of techniques under different scenarios. The effectiveness of methods for detecting rural Irish hedgehogs was investigated as part of a larger study in April 2008. Road kill sightings and questionnaires were employed to locate possible hedgehog sites. Six sites were subsequently selected, and in these areas trapping, spotlighting and foot print tunnels were employed to investigate whether hedgehogs were indeed in the surrounding landscape. Infrared thermal imagery was examined as a detection device. Trapping and infrared imagery failed to detect hedgehogs in areas where they had previously been recorded. Footprint tunnels proved to be unsuccessful in providing absolute proof of hedgehogs in an area. No single method of detection technique could be relied upon to conclude the presence of hedgehogs in an area. A combination of methods is therefore recommended. However, spotlighting was the most effective method, taking a mean of 4 nights to detect a hedgehog, in comparison to 48 nights if footprint tunnels were used as a sole method of detection. This was also suggested by rarefaction curves of these two detection techniques, where over a 48 night period hedgehogs were expected to be recorded 27 times through spotlighting and just 5 times in an equivalent period of footprint tunnel nights.
Resumo:
This paper presents an image processing based detection method for detecting pitting corrosion in steel structures. High Dynamic Range (HDR) imaging has been carried out in this regard to demonstrate the effectiveness of such relatively inexpensive techniques that are of immense benefit to Non – Destructive – Tesing (NDT) community. The pitting corrosion of a steel sample in marine environment is successfully detected in this paper using the proposed methodology. It is observed, that the proposed method has a definite potential to be applied to a wider range of applications.
Resumo:
The importance of non-destructive techniques (NDT) in structural health monitoring programmes is being critically felt in the recent times. The quality of the measured data, often affected by various environmental conditions can be a guiding factor in terms usefulness and prediction efficiencies of the various detection and monitoring methods used in this regard. Often, a preprocessing of the acquired data in relation to the affecting environmental parameters can improve the information quality and lead towards a significantly more efficient and correct prediction process. The improvement can be directly related to the final decision making policy about a structure or a network of structures and is compatible with general probabilistic frameworks of such assessment and decision making programmes. This paper considers a preprocessing technique employed for an image analysis based structural health monitoring methodology to identify sub-marine pitting corrosion in the presence of variable luminosity, contrast and noise affecting the quality of images. A preprocessing of the gray-level threshold of the various images is observed to bring about a significant improvement in terms of damage detection as compared to an automatically computed gray-level threshold. The case dependent adjustments of the threshold enable to obtain the best possible information from an existing image. The corresponding improvements are observed in a qualitative manner in the present study.
Resumo:
The use of structural health monitoring of civil structures is ever expanding and by assessing the dynamical condition of structures, informed maintenance management can be conducted at both individual and network levels. With the continued growth of information age technology, the potential arises for smart monitoring systems to be integrated with civil infrastructure to provide efficient information on the condition of a structure. The focus of this thesis is the integration of smart technology with civil infrastructure for the purposes of structural health monitoring. The technology considered in this regard are devices based on energy harvesting materials. While there has been considerable focus on the development and optimisation of such devices using steady state loading conditions, their applications for civil infrastructure are less known. Although research is still in initial stages, studies into the uses associated with such applications are very promising. Through the use of the dynamical response of structures to a variety of loading conditions, the energy harvesting outputs from such devices is established and the potential power output determined. Through a power variance output approach, damage detection of deteriorating structures using the energy harvesting devices is investigated. Further applications of the integration of energy harvesting devices with civil infrastructure investigated by this research includes the use of the power output as a indicator for control. Four approaches are undertaken to determine the potential applications arising from integrating smart technology with civil infrastructure, namely • Theoretical analysis to determine the applications of energy harvesting devices for vibration based health monitoring of civil infrastructure. • Laboratory experimentation to verify the performance of different energy harvesting configurations for civil infrastructure applications. • Scaled model testing as a method to experimentally validate the integration of the energy harvesting devices with civil infrastructure. • Full scale deployment of energy harvesting device with a bridge structure. These four approaches validate the application of energy harvesting technology with civil infrastructure from a theoretical, experimental and practical perspective.