Smarter Lens Beneath the Surface: Cloud-Based Ultrasonic Analysis for Concrete Inspection

This is a browser-based software platform that transforms raw ultrasonic tomography scans of concrete into depth-calibrated subsurface images and an automatic quality score, with no local installation required. By replacing a fragile, single-channel velocity measurement with a more robust, multi-channel estimation method, it delivers sharper, more trustworthy images and lets non-experts batch-process entire field surveys into shareable inspection reports in minutes.A example of the software's output:

Description

The platform ingests proprietary raw acquisition files from an ultrasonic shear-wave tomography instrument and runs them through a four-stage processing chain: parsing the data into per-channel readings, estimating shear-wave velocity in the concrete, reconstructing a depth-calibrated subsurface image using a synthetic aperture focusing technique, and computing a multi-metric quality index from the reconstructed image. The core innovation lies in the velocity estimation step, which uses a semblance-based method that searches for coherent signal agreement across many sensor-pair channels simultaneously, in a velocity-by-intercept-time space, rather than depending on one reflector or one channel. Because every depth measurement and every reconstructed image depends on this velocity value, this change propagates into a more reliable result across the board. The platform also displays a confidence map so an operator can see at a glance how well-supported a given measurement is, and it retains the legacy single-channel estimator as a selectable option so that new results remain comparable to historical data.

Applications

- Bridge deck, pavement, and runway condition assessment for transportation infrastructure owners and contractors
- Concrete quality assurance and defect detection (rebar, voids, delaminations) for construction and structural inspection firms
- Field inspection services for infrastructure maintenance and asset management programs
- Cloud-based data platforms for engineering firms needing multi-user, account-controlled access to inspection data
- Academic and research collaboration tools for advancing nondestructive testing methods on ultrasonic tomography data

Advantages

- More robust velocity estimation, validated to produce more consistent results across multiple real datasets, not just in theory
- Automatic, multi-metric subsurface quality scoring that lets non-experts trust a per-scan grade without interpreting raw imagery
- Zero-install, browser-based deployment of a reconstruction pipeline that historically required desktop software, enabling instant updates and secure, account-controlled multi-user access
- Native batch processing of up to 100 files per pass, matching real field-survey volumes versus single-file desktop workflows
- Backward compatibility with the legacy velocity estimator, keeping new results directly comparable with prior work, plus one-click generation of shareable, archivable PDF inspection records

Invention Readiness

The software exists as a working platform, and its core velocity-estimation method has had its performance validated across multiple real datasets rather than on a purely theoretical basis. Supporting data has been generated and published in a peer-reviewed article on ultrasonic tomography and multi-metric quality scoring for concrete pavement assessment. Further work would focus on continued field deployment, broader validation across additional dataset types and operating conditions, and incorporation of ongoing refinements through collaborative use of the platform.

IP Status

Related Publication(s)

Quantitative Assessment of Concrete Pavement Subsurface Quality Using Ultrasonic Tomography: Development and Initial Validation of a Multi-Metric Scoring System. https://doi.org/10.3390/app16052233

Hoegh, Kyle, Lev Khazanovich, and H. Thomas Yu. "Ultrasonic tomography for evaluation of concrete pavements." Transportation Research Record 2232.1 (2011): 85-94. https://doi.org/10.3141/2232-09

Hoegh, Kyle, Lev Khazanovich, and H. Thomas Yu. "Concrete pavement joint diagnostics with ultrasonic tomography." Transportation Research Record 2305.1 (2012): 54-61. https://doi.org/10.3141/2305-06