Deep Foundation Testing using Immunity-based Displacement Measurement in Successive-Sparse Images

KSCE Journal of Civil Engineering(2019)

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摘要
This paper presents a new immunity-based approach to measure the displacement of nodes (or points of interest) in successive-yetsparse images, in order to measure the settlement of deep-foundations under heavy loads. It is developed as a close-range photogrammetric technique to search the nodes, similar to immune-cells searching bacteria in their vicinity. The immunological concepts of chemotaxis, biased random walk, diffusion and inflammation are implemented herein to accomplish the task. The technique greatly reduces the errors and is also validated on site of a mega project to record the settlements in deep foundations. The accuracy levels are found to be conforming to ASTM’s standards for static load testing, including both compression and lateral-load tests. Unlike other techniques, such as particle image velocimetry, this approach is able to handle successive-images with varying Δ T between them. Furthermore, the technique is completely autonomous and does not require any embedded instrumentation.
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关键词
deep foundation testing, close range photogrammetry, artificial immune system, bio-inspired image processing, chemotaxis
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