Abstract
This section describes novel methods of electromagnetic wave nondestructive visualization (NDV) for assessing qualification and durability of concrete and wooden structures, which involves devices, systems, and image processing. As the first, the basic knowledge and principles on dielectric properties of materials, wave propagation in media involving plane waves in vacuum and in non-conducting and non-magnetic dielectric media were introduced. As the second, the dielectric properties of concrete and NDV techniques for concrete structures were introduced. After the introduction of conventional methods to detect internal cracks in concrete structures, a novel development of a millimeter wave scanner for NDV of concrete was introduced where the performance of the scanner to detect surface cracks covered by other sheet materials was discussed. Miscellaneous image processing techniques to recognize the target using pattern recognition methods were also introduced. Wood is a material made of the plant cells of trees. Wood shows anisotropy in physical and mechanical properties, such as elastic moduli, strength, and dielectric constants. In addition, wood is deteriorated by biological agents such as insects and fungi, and these deterioration often generate in inner or hidden areas of wood and wooden construction. The deterioration is closely associated with moisture content of wood. In this section, the feasibility of technologies using electromagnetic waves for the nondestructive evaluation of properties and deterioration of wood and wooden construction, is introduced. The reaction of wood to electromagnetic wave such as transmission and reflection of millimeter wave through and from wood was discussed. The development of wooden wall scanner for nondestructive diagnoses of wooden houses using FMCW radar was introduced.
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Togo, H., Oka, S., Fujii, Y., Fujiwara, Y. (2015). Nondestructive Visualization Using Electromagnetic Waves for Real and Practical Sensing Technology for Robotics. In: Liu, Z., Ukida, H., Ramuhalli, P., Niel, K. (eds) Integrated Imaging and Vision Techniques for Industrial Inspection. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-6741-9_14
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DOI: https://doi.org/10.1007/978-1-4471-6741-9_14
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