Machine vision based concrete surface quality assessment

Manually inspecting concrete surface defects (e.g., cracks and air pockets) is not always reliable. Also, it is labor-intensive. In order to overcome these limitations, automated inspection using image processing techniques was proposed. However, the current work can only detect defects in an image without the ability of evaluating them. This paper presents a novel approach for automatically assessing the impact of two common surface defects (i.e., air pockets and discoloration). These two defects are first located using the developed detection methods. Their attributes, such as the number of air pockets and the area of discoloration regions, are then retrieved to calculate defects’ visual impact ratios (VIRs). The appropriate threshold values for these VIRs are selected through a manual rating survey. This way, for a given concrete surface image, its quality in terms of air pockets and discoloration can be automatically measured by judging whether their VIRs are below the threshold values or not. The method presented in this paper was implemented in C++ and a database of concrete surface images was tested to validate its performance. Read More: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CO.1943-7862.0000126?journalCode=jcemd4

Detecting air pockets for architectural concrete quality assessment using visual sensing

Air pockets, one kind of concrete surface defects, are often created on formed concrete surfaces during concrete construction. Their existence undermines the desired appearance and visual uniformity of architectural concrete. Therefore, measuring the impact of air pockets on the concrete surface in the form of air pockets is vital in assessing the quality of architectural concrete. Traditionally, such measurements are mainly based on in-situ manual inspections, the results of which are subjective and heavily dependent on the inspectors’ own criteria and experience. Often, inspectors may make different assessments even when inspecting the same concrete surface. In addition, the need for experienced inspectors costs owners or general contractors more in inspection fees. To alleviate these problems, this paper presents a methodology that can measure air pockets quantitatively and automatically. In order to achieve this goal, a high contrast, scaled image of a concrete surface is acquired from a fixed distance range and then a spot filter is used to accurately detect air pockets with the help of an image pyramid. The properties of air pockets (the number, the size, and the occupation area of air pockets) are subsequently calculated. These properties are used to quantify the impact of air pockets on the architectural concrete surface. The methodology is implemented in a C++ based prototype and tested on a database of concrete surface images. Comparisons with manual tests validated its measuring accuracy. As a result, the methodology presented in this paper can increase the reliability of concrete surface quality assessment

Defects Detection and Assessment in Concrete Surfaces

Aside from cracks, the impact of other surface defects, such as air pockets and discoloration, can be detrimental to the quality of concrete in terms of strength, appearance and durability. For this reason, local and national codes provide standards for quantifying the quality impact of these concrete surface defects and owners plan for regular visual inspections to monitor surface conditions. However, manual visual inspection of concrete surfaces is a qualitative (and subjective) process with often unreliable results due to its reliance on inspectors’ own criteria and experience. Also, it is labor intensive and time-consuming. This paper presents a novel, automated concrete surface defects detection and assessment approach that addresses these issues by automatically quantifying the extent of surface deterioration. According to this approach, images of the surface shot from a certain angle/distance can be used to automatically detect the number and size of surface air pockets, and the degree of surface discoloration. The proposed method uses histogram equalization and filtering to extract such defects and identify their properties (e.g. size, shape, location). These properties are used to quantify the degree of impact on the concrete surface quality and provide a numerical tool to help inspectors accurately evaluate concrete surfaces. The method has been implemented in C++ and results that validate its performance are presented.

Control of material transport through pulse shape manipulation-a development toward designer pulses

The variety of laser systems available to industrial laser users is growing and the choice of the correct laser for a material target application is often based on an empirical assessment. Industrial master oscillator power amplifier systems with tuneable temporal pulse shapes have now entered the market, providing enormous pulse parameter flexibility in an already crowded parameter space. In this paper, an approach is developed to design interaction parameters based on observations of material responses. Energy and material transport mechanisms are studied using pulsed digital holography, post process analysis techniques and finite-difference modelling to understand the key response mechanisms for a variety of temporal pulse envelopes incident on a silicon (1/1/1) substrate. The temporal envelope is shown to be the primary control parameter of the source term that determines the subsequent material response and the resulting surface morphology. A double peak energy-bridged temporal pulse shape designed through direct application of holographic imaging data is shown to substantially improve surface quality. © 2014 IEEE.

Coupling model uncertainty for coupled rainfall/runoff and surface water quality models in river problems

Coupled hydrology and water quality models are an important tool today, used in the understanding and management of surface water and watershed areas. Such problems are generally subject to substantial uncertainty in parameters, process understanding, and data. Component models, drawing on different data, concepts, and structures, are affected differently by each of these uncertain elements. This paper proposes a framework wherein the response of component models to their respective uncertain elements can be quantified and assessed, using a hydrological model and water quality model as two exemplars. The resulting assessments can be used to identify model coupling strategies that permit more appropriate use and calibration of individual models, and a better overall coupled model response. One key finding was that an approximate balance of water quality and hydrological model responses can be obtained using both the QUAL2E and Mike11 water quality models. The balance point, however, does not support a particularly narrow surface response (or stringent calibration criteria) with respect to the water quality calibration data, at least in the case examined here. Additionally, it is clear from the results presented that the structural source of uncertainty is at least as significant as parameter-based uncertainties in areal models. © 2012 John Wiley & Sons, Ltd.

Post-processing of vertical-cavity surface-emitting lasers for transverse mode and polarization control

The operation on how high quality single-mode operation can be readily attained on etching circles in multimode devices is discussed. Arrays of such spots can also be envisaged. Control of the polarization state is also achieved by use of deep line etches. The output filaments and beam shapes of the conventional multimode vertical cavity surface emitting lasers (VCSEL) is shown to be engineered in terms of their positions, widths, and polarizations by use of focused ion beam etching (FIBE). Several GaAs quantum well top-emitting devices with cavity diameters of 10 μm and 18 μm were investigated.

20 Gb/s QPSK transmission using an electro-optically modulated vertical-cavity surface-emitting laser

20 Gb/s QPSK transmission over 100 m of OM3 fibre using an EOM VCSEL under QPSK modulation is reported. Bit-error-ratio measurements are carried out to express the quality of the transmission scheme. © 2011 OSA.

Kinetic control of catalytic CVD for high-quality graphene at low temperatures.

Low-temperature (∼600 °C), scalable chemical vapor deposition of high-quality, uniform monolayer graphene is demonstrated with a mapped Raman 2D/G ratio of >3.2, D/G ratio ≤0.08, and carrier mobilities of ≥3000 cm(2) V(-1) s(-1) on SiO(2) support. A kinetic growth model for graphene CVD based on flux balances is established, which is well supported by a systematic study of Ni-based polycrystalline catalysts. A finite carbon solubility of the catalyst is thereby a key advantage, as it allows the catalyst bulk to act as a mediating carbon sink while optimized graphene growth occurs by only locally saturating the catalyst surface with carbon. This also enables a route to the controlled formation of Bernal stacked bi- and few-layered graphene. The model is relevant to all catalyst materials and can readily serve as a general process rationale for optimized graphene CVD.

20 Gb/s QPSK transmission using an electro-optically modulated vertical-cavity surface-emitting laser

20 Gb/s QPSK transmission over 100 m of OM3 fibre using an EOM VCSEL under QPSK modulation is reported. Bit-error-ratio measurements are carried out to express the quality of the transmission scheme. © 2011 Optical Society of America.

Growth mechanism of graphene on platinum: Surface catalysis and carbon segregation

A model of the graphene growth mechanism of chemical vapor deposition on platinum is proposed and verified by experiments. Surface catalysis and carbon segregation occur, respectively, at high and low temperatures in the process, representing the so-called balance and segregation regimes. Catalysis leads to self-limiting formation of large area monolayer graphene, whereas segregation results in multilayers, which evidently "grow from below." By controlling kinetic factors, dominantly monolayer graphene whose high quality has been confirmed by quantum Hall measurement can be deposited on platinum with hydrogen-rich environment, quench cooling, tiny but continuous methane flow and about 1000°C growth temperature. © 2014 AIP Publishing LLC.