Fair-faced concrete surface pore analysis method based on convolutional neural network
A convolutional neural network and fair-faced concrete technology, applied in the field of materials engineering, can solve problems such as low efficiency and large human error, achieve high efficiency, stable image quality, and fill in the lack of acceptance quality standards.
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[0035] Aiming at the problems that the existing clear-water concrete surface pore analysis relies on manual prior knowledge, low efficiency, and large human error, the present invention provides a method for analyzing the surface pores of clear-water concrete based on convolutional neural networks. The analysis method is as follows: using volume A neural network algorithm is used to establish a recognition and analysis model of pores on the surface of fair-faced concrete; the image of the appearance of clear-water concrete to be recognized is taken, input into the model, and the image of recognized and calibrated pores is output, as well as three pore analysis metrics: pore area ratio , stomatal pore size distribution, stomatal distribution uniformity.
[0036] Wherein, the establishment of described fair-faced concrete surface pore identification calibration model comprises the following steps:
[0037] (s1) collecting the image of the fair-faced concrete on the construction ...
Embodiment 2
[0045] figure 1 Shown is the overall block diagram of the air hole analysis method on the surface of fair-faced concrete based on convolutional neural network of the present invention, comprising the following steps:
[0046] 101. Establish a calibration model for the recognition and calibration of pores on the surface of clear-water concrete: use the convolutional neural network to conduct deep learning on the feature information of the surface image of clear-water concrete, and establish a recognition and calibration model for pores on the surface of clear-water concrete. Specifically include the following steps:
[0047] 1011. Fair-faced concrete image acquisition: Under different on-site construction conditions, use drones to take aerial photos of the clear-faced concrete on the construction site to obtain comprehensive, full-coverage, high-definition and high-stable images; for enclosure structures and walls that are too close, human Neither drones nor drones can enter t...
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