The unstable quality of 3D printing products is one of the obstacles that hinder the popular application of 3D printing technology. In this paper, we propose a novel mask projection 3D printing scheme with visual surveillance. We introduce a vision system to monitor the gray level variation, so that two kinds of problems could be detected in time: 1. the printed objects are stuck on the bottom of the tank. 2. the printed objects are stretched out and part of objects are stuck on the bottom of the tank. The normal and abnormal printing procedures correspond to different gray level variation curves, which can be discriminated by classify algorithms. By the computing capability of our computer, we could monitor gray level variation curves at 470 points in real time. If 95 % curves are normal, the layer is thought successfully printed, the next layer will be printed continuously. Otherwise, this layer is abnormal, and the printing will be stopped. The experiment show that the proposed scheme can stop the abnormal printing in time. it can improve the production rate of the finished products and reduce the material waste.
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