To solve the problem in the process of weld seam tracking, a new prediction model for welding deviation based on the weld pool image centroid has been proposed in the paper. First, some weld images under different weld currents were captured by a vision sensor. A composite filter system, which is composed of narrow-band and neutral filters, is used to reduce the disturbance of weld arc. So, several clear weld pool images can be obtained. Then a frontier of weld pool is chosen to be the processing region. Median filter and gray transformation operations are used to enhance the contrast of processing region. On this basis, the variation trend of centroid difference [Formula: see text] and welding deviation [Formula: see text] were analyzed. The centroid difference value [Formula: see text] and the weld current [Formula: see text] were determined to be welding status parameters. Moreover, a BP neural network was set up, which was composed of three layers. Next, elastic gradient descent method was used to be the training function. So a prediction model between the welding status parameters [Formula: see text] and [Formula: see text] and the welding deviation [Formula: see text] was set up. In the end of the paper, several experiments were performed to test the accuracy of the setup prediction model. The results showed that prediction values of welding deviation calculated by the vision model are fit to the real measured values. The final errors of the vision model under the weld current 70[Formula: see text]A and 73[Formula: see text]A were 0.033[Formula: see text]mm and 0.027[Formula: see text]mm, which showed excellent accuracy, environmental suitability and intelligence of the model.
In order to extract the character of weld pool, a new method for weld pool image procession based on the Fourier-DNA low-pass filtering is proposed. Firstly, the TIG welding technique is chosen to be the researched object. The welding experimental system is setup, which is used to capture weld pool images in real time. On this basis, Fourier transformation is performed to weld pool image, and changed the space domain to frequency domain. Then the DNA low-pass filtering is constructed. The DNA intelligent algorithm is used to obtain the optimum low-pass cut-off frequency, and the low-pass filtering can be obtained. The binaryzation operation by the optimum low-pass filtering method and the traditional otsu method have been done. The results show that the method proposed in the paper has a better binaryzation performance. In the end, canny edge extract operation are performed. So the weld pool image edge can be obtained, which has made some basis for the extraction of weld pool character latter on.
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