58results about How to "With connectivity" patented technology

The invention provides a method for manufacturing an autoclaved aerated concrete heterogeneous wall component by partitioning an inner cavity of a mould, belonging to the technical field of energy-saving building walls. The method comprises the following steps of: confirming the proportion of the corresponding slurry and a mould separating component according to the design requirement of the wall component; manufacturing the separating component, and placing the separating component into the inner cavity of the mould by a positing strip to form a subarea; pouring the corresponding slurry, and growing a green body; vertically raising the separating component after the green body is grown to the semi-solid state or the initial solid state, and maintaining to form the green body; and demoulding, cutting into semi-finished products, inserting an accessory into a specified position on the component as required, and maintaining into the heterogeneous wall component. According to the method for manufacturing the autoclaved aerated concrete heterogeneous wall component by partitioning the inner cavity of the mould provided by the invention, various autoclaved aerated concrete components with different functions can be developed and manufactured, and the wall can be built by the components without local cast-in-place and pre-casting and without needing to construct an additive layer on a wall surface, so that the wall structure can be simplified, and the building construction can be simplified as well.

The invention discloses a preparation method of hollow titanium dioxide millimeter spheres consisting of nanoparticles and relates to the preparation method of the hollow titanium dioxide millimeter spheres. The invention aims to solve the technical problems that the existing TiO2 nano materials are difficult to separate and are low in recovery rate in photocatalysis or environmental pollution control system. The preparation method comprises the following steps: firstly, weighing a titanium source, an aqueoussolution of tetrapropylammonium hydroxide, deionized water and anion exchange resin; secondly, mixing the aqueoussolution of the tetrapropylammonium hydroxide with the deionizedwater, and then adding the titanium source and the anion exchange resin and stirring to obtain a mixture; thirdly, filling a reaction still with the mixture; fourthly, pouring out supernatant liquor to obtain small solid-phase spheres, and drying after washing the small solid-phase spheres; fifthly, placing the dried small spheres into a tube furnace to obtain small carbonized spheres; sixthly, placing the small carbonized spheres into a mufflefurnace for roasting to obtain the titanium dioxide millimeter spheres. The titanium dioxide millimeter spheres prepared through adopting the preparation method disclosed by the invention are easily separated and are high in recovery rate in the photocatalysis or environmentalpollution control system. The preparation method is used for preparing the hollow titanium dioxide millimeter spheres.

The invention discloses an automatic identification method and system for road surface disease images. The method includes: preprocessing the captured road surface image, including Gamma grayscale correction, Gaussian filter enhancement and local adaptive binarization; performing edge detection on the binarized image; performing connected domain contour detection on the image after edge detection , to obtain the number of connected domains and the circumscribed rectangle of the connected domain outline; judge the area where the road surface crack is located according to the shape of the circumscribed rectangle of the connected domain outline; extract the image of the crack area from the image after edge detection according to the location information of the area where the pavement crack is located , and superimposed the black template to form a crack feature image with the same size as the original image; the crack feature image is classified based on the convolutional neural network. Compared with the prior art, the present invention has very excellent detection efficiency for crack location in pavement disease, and has good robustness performance for crack images with different characteristics.