Stereo Line-Scan Camera System For Surface Distress Identification

Description:

TECHNOLOGY AREA(S): Ground Sea

OBJECTIVE: Develop a near real time pavement imaging system, using a line-scan camera stereo pair which measures deflection depth trailing, and leads a moving wheel load on concrete & asphalt surfaces.

DESCRIPTION: The military pavements community is lacking in detail the true effects of vehicle-pavement interaction necessary to adequately adapt and validate more complex finite element models in the development of next generation combat vehicles (NGCV’s) and assessment of aging and contingency infrastructure.In assessing the physical influence of a tire moving along a pavement surface, research has centered on the measurement of stresses beneath a static or moving wheel load, and determining an assumed deflection basin surrounding the tire-pavement contact location based on pavement model parameters [1].To advance the knowledge of how distresses are imparted to the pavement surface from vehicle or aircraft tires at varying loads, speeds, and pressures, current imaging techniques involve either the use of light detection and ranging systems (LiDAR), or line-scan laser systems, both of which have significant cost, and are complex to operate and interpretdata [2].Of interest to the Army and the broader commercial and academic sector is the potential of introducing the technology of low-cost line-scan camera pairs to create similar data quality of the laser systems, but adopting the more approachable photogrammetry point cloud development commonly used in modern full frame image processing [3].Line-scan cameras have a long history of use in the manufacturing and food handling industries being utilized to rapidly detect defects in metal objects, food products, or other fast moving, repetitive objects.Further, newer color based line-scan cameras work effectively at imaging long continuous objects that are otherwise cumbersome to capture with a single photograph or scan, this technology is an ideal candidate for adaptation to rail or pavement systems [4].Line-scan cameras can produce very detailed, sub-millimeter point clouds in real time, and combining two cameras in a stereo pair can create a depth map to coincide with the real time scan [5].It is anticipated that this approach can achieve faster and more accurate point cloud rendering of the pavement surface than traditional photogrammetry and at a comparable accuracy to that of laser based systems, all in a more deployable and price-competitive system.

PHASE I: This research will involve demonstration of a stereo color-line-scan camera system that can measure surface deflection near a wheel load.The investigators will confirm whether smooth asphalt and concrete pavements provide sufficient point correspondences at line-scanner resolutions for photogrammetric reconstruction.Whether the introduction of red green blue (RGB) pixels in place of grey-scale pixels influences feature detection should be investigated.Further, the influence of changing lighting conditions must be quantified and addressed.This research will require development of algorithms that should provide depth data sufficient for determining deflections at every line-scan frame within a highly accurate (sub-cm) local or global reference frame.Algorithms produced from this effort should be deployable to a Windows (.NET) platform and should be written in an open-source, widely-used programming language.

PHASE II: Research at this phase will involve development of a deployable system that must include a stereo-pair of line-scan cameras for both the trailing and leading side of a moving wheel load.The reconstructed data from each stereo-pair should be fused for accuracy determination as well as to measure deflection differences in leading and trailing loading conditions. It is desired that the vertical and horizontal resolution of the developed line-scan camera system be tunable to match a variety of loading systems without excess data to accommodate variable tire configurations present within the military inventory.It is intended that during the Phase II effort, a demonstration of the system capability will include mounting of the stereo-pair system on the U.S. Army Engineer Research and Development Center (ERDC) Heavy Vehicle Simulator (a unique testing apparatus to the military pavements community) to capture pavement distresses on a moving aircraft wheel load.

PHASE III: The development of a stereo line-scan camera system that is deployable either on a fixed or moving data collection system will support a number of commercial and military evaluation efforts.The military has interest in evaluation of pavement surfaces undergoing novel tire loading from newly developed vehicle prototypes to determine the impact of NGCV’s.A deployable system would also support evaluation of standard or prototype vehicles on novel pavement designs to assess real-time constitutive pavement behavior.From a commercial standpoint, Federal or State Departments of Transportation would find relevance in such an inexpensive pavement evaluation technology for assessing pavement condition for routine maintenance inspections and institutional pavement research on the national transportation infrastructure.

KEYWORDS: line-scan; light detection; ranging systems; LiDAR; photogrmmetric

References:

[1] Tarefder, R.A. and Ahmed, M.U., “Modeling of the FWD Deflection Basin to Evaluate Airport Pavements,” Intl. J. of Geomechanics 14(1), April, 2014.; [2] Wang, K., Gong. W., Tracy, T. and Nguyen V., “Automated Survey of Pavement Distress based on 2D and 3D Laser Images,” Univ. of Arkansas Mack-Blackwell Rural Transportation Center Report, MBTC DOT 3023, Nov. 2011.; [3] Westoby, M.J., Brasington, J., Glasser, N.F., Hambrey, M.J., and Reynolds, J.M., "Structure-from-Motion Photogrammetry: A low-cost effective tool for geoscience applications," Geomorphology, Vol. 179, Dec. 2012.; [4] Deutshl, E., Gasser, C., Neil, A., Werschonig, J., “Defect detection on rail surfaces by a vision based system,” IEEE Intellingent Vehicles Symposium, Oct. 2008.; [5] Valentín, Reinhold Huber-Mörk, Svorad Štolc, “Binary descriptor-based dense line-scan stereo matching,” J. Electron. Imaging 26(1), 013004 (2017).

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