Laser-based sensing for assessing and monitoring civil infrastructures

Yu, Tzuyang

doi:10.1533/9780857099136.327

Cited by 3 publications

(1 citation statement)

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“…In the two-step process, a digital holographic interference pattern is generated and split into a reference beam and a measurement beam, and then the beams returned from the target surface is merged and recorded simultaneously. The recorded hologram of the target surface carries both the amplitude and phase of the returned beam, and the surface can be reconstructed based on it [45,46]. Because LHI relies on the phase shift measurement, it can only achieve vertical resolution at hundreds of nanometers and lateral resolution at micrometers.…”

Section: Lhimentioning

confidence: 99%

Data-Driven Intelligent 3D Surface Measurement in Smart Manufacturing: Review and Outlook

et al. 2021

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High-fidelity characterization and effective monitoring of spatial and spatiotemporal processes are crucial for high-performance quality control of many manufacturing processes and systems in the era of smart manufacturing. Although the recent development in measurement technologies has made it possible to acquire high-resolution three-dimensional (3D) surface measurement data, it is generally expensive and time-consuming to use such technologies in real-world production settings. Data-driven approaches that stem from statistics and machine learning can potentially enable intelligent, cost-effective surface measurement and thus allow manufacturers to use high-resolution surface data for better decision-making without introducing substantial production cost induced by data acquisition. Among these methods, spatial and spatiotemporal interpolation techniques can draw inferences about unmeasured locations on a surface using the measurement of other locations, thus decreasing the measurement cost and time. However, interpolation methods are very sensitive to the availability of measurement data, and their performances largely depend on the measurement scheme or the sampling design, i.e., how to allocate measurement efforts. As such, sampling design is considered to be another important field that enables intelligent surface measurement. This paper reviews and summarizes the state-of-the-art research in interpolation and sampling design for surface measurement in varied manufacturing applications. Research gaps and future research directions are also identified and can serve as a fundamental guideline to industrial practitioners and researchers for future studies in these areas.

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Section: Lhimentioning

confidence: 99%