Modular demolding equipment based on image recognition and working method thereof
A technology of image recognition and recognition module, which is applied in the field of demoulding, which can solve problems such as inability to come out, improper mold temperature control, mold wear, etc., and achieve image decomposition and accurate recognition, avoid shaking up and down, and precise position.
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Embodiment 1
[0054] Such as Figure 1-4 As shown, this embodiment provides a modular demoulding device based on image recognition, including a housing 1, a conveyor belt 2, a workbench 3, a demoulding mechanism and a control mechanism, and the control mechanism includes a processor 4 and a driving device 5. The processor 4 is connected to the driving device 5, the processor 4 includes a scanning module 6 and an identification module 13, the scanning module 6 is connected to the identification module 13, and the scanning module 6 is arranged on the The interior of the casing 1 is used to obtain the scanned image of the mold under the same background environment and send the scanned image to the recognition module 13. The scene characteristics of the scanning environment and the demoulding environment are the same, and the recognition module 13 utilizes Zero-paradigm sparse representation establishes a model for recognizing image sparsity constraints, obtains the correlation between pixels o...
Embodiment 2
[0072] Such as Figure 5 As shown, the present embodiment provides a working method of a modular demoulding device based on image recognition, including the following working steps:
[0073] S101: The processor 4 outputs a transmission signal to the driving device 5, and the driving device 5 drives the conveyor belt 2 to start.
[0074] S102: The camera device 7 acquires an image inside the casing 1 and sends the image to the processor 4 .
[0075] S103: The processor 4 determines whether the mold is located on the workbench 3.
[0076] S104: If yes, the processor 4 outputs an ascending signal to the driving device 5, and the driving device 5 drives the elevator 15 to ascend.
[0077] S105: The processor 4 outputs a first rotation signal to the driving device 5, and the driving device 5 drives the rotating device 9 to rotate 90 degrees in a first preset direction.
[0078] S106: The processor 4 outputs a descending signal to the driving device 5, and the driving device 5 dr...
Embodiment 3
[0101] Such as Figure 7 As shown, the demoulding method based on the edge position recognition of the mold core also includes:
[0102] The processor 4 compares the image sent by the camera 7 with the scanned image, and judges whether there is a gap between the L-shaped clamp arm and the mold according to the height of the mold core.
[0103] If so, the processor 4 outputs a shortening signal to the driving device 5, and the driving device 5 drives the first telescopic rod to shorten.
[0104] Such as Figure 8 As shown, the demoulding method based on the edge position of the mold core and the identification of the connection position also includes:
[0105] The processor 4 compares the image sent by the camera 7 with the scanned image, and judges whether the L-shaped clamp arm overlaps with the edge position in the longitudinal direction according to the edge position of the mold core.
[0106] If not, the processor 4 calculates the offset angle between the L-shaped clamp...
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