Bridge deck crack supervision method and system based on binocular vision
A binocular vision and crack technology, applied in neural learning methods, electrical digital data processing, biological neural network models, etc., can solve problems such as spending a lot of manpower and material resources
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[0043] The following is attached Figure 1-3 The application is described in further detail.
[0044] The embodiment of the present application discloses a binocular vision-based bridge deck crack supervision method, see figure 1 , the method includes the following steps:
[0045] S100: Obtain in real time the crack depth information and crack width data information about bridge deck cracks transmitted by the crack detection device 2 set at a fixed point.
[0046] In this embodiment, the crack detection device 2 refers to a detection instrument for detecting bridge deck cracks;
[0047] Specifically, the crack detection device 2 is installed at the fixed-point detection position of the bridge deck, so that the crack detection device 2 detects the cracks to obtain detection data related to the cracks, and stores the detected data into the system.
[0048] S200: Extract crack depth information and crack width information related to bridge deck cracks from bridge deck historical...
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