Steel bar corrosion rate intelligent detection device
A technology for intelligent detection and steel corrosion, which is applied in measuring devices, optical testing for flaws/defects, image enhancement, etc. It can solve the difficulties in standardizing the production of sleeves, the reliability of heating wires, and the production of strip thermal imagers. and other problems, to achieve the effect of realizing intelligent rapid measurement, avoiding irregular operation behavior, and fast measurement speed
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Embodiment 1
[0056] Such as figure 1 with figure 2 As shown, the present invention discloses an intelligent detection device for the corrosion rate of steel bars, including: a camera 4 and a corrosion detection host, wherein the corrosion detection host stores the cross-sectional corrosion pixels of steel bars trained by the classification convolutional neural network Determining the network model; and, the corrosion cross section of the measured steel bar that needs to be measured is placed within the shooting range of the camera 4;
[0057] Such as image 3 As shown, the rust detection host can communicate with the camera 4, and measure the steel bar under test in the following manner:
[0058] Step S1, the operator controls the camera 4 to take a sampling image through the rust detection host, so that the rust detection host can automatically judge whether the shooting angle of the sampling image meets the qualification condition; wherein, the qualification condition is : The perpen...
Embodiment approach
[0067] Such as Figure 4 with Figure 5 As shown, the intelligent detection equipment for steel bar corrosion rate also includes a calibration device provided with a target plane 1, three saddle circles 2 are arranged on the target plane 1, and the saddle points of the three saddle circles 2 are in the form of an isosceles right triangle Distribution, the saddle point at the right angle position is marked as the reference saddle point A, and the other two saddle points are marked as the second saddle point B and the third saddle point C, wherein the saddle circle 2 is a circle pattern whose interior is divided into four equal parts, and the The four equal parts are alternately filled with two different colors clockwise, and the saddle point is the center of the saddle circle 2; see Figure 5 , the four equal parts are preferably filled with black and white;
[0068] Moreover, the calibration device is relatively fixed to the steel bar under test, and the target plane 1 is copl...
Embodiment 3
[0092] On the basis of the above-mentioned embodiment 1 or embodiment 2, this embodiment 3 also adopts the following preferred implementation modes:
[0093] The network model for determining the rusted pixels of the steel bar cross section is obtained by training the classification convolutional neural network with the model training data set;
[0094] Wherein, the model training data set includes a sufficient number of data groups, and each group of the data groups includes one of the qualified captured images, the classification and marking data of the qualified captured images obtained by manual marking, and obtained through actual measurement. The rusted pixel area of the qualified captured image (for example: Figure 7 The total pixel area of all the solid boxes in the box is the rusted pixel area), the classification mark data includes the classification mark of each pixel in the qualified captured image, and the classification mark is divided into two types: 1 and ...
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