Approach to online defect monitoring in fused deposition modeling based on the variation of the temperature field

Abstract

According to the surface state of the product, a process quality monitoring technology based on a Qualitative Trend Analysis method is proposed. The construction of the product surface defect knowledge base provides a basis for online monitoring of the nozzle status of the fused deposition modeling (FDM) machine. Ten workpieces are designed in all, and each one conducts two prints which are normal and abnormal, respectively. An infrared thermal imager is used to obtain the temperature image of each layer of the workpiece surface; the feature values are extracted, and the difference between the feature values in the two kinds of printing is calculated. The Qualitative Trend Analysis method is used to analyze the difference in order to obtain the corresponding sensitive feature parameters corresponding to the starting points in different phases of the product printing. The change rules of the sensitive feature values are summarized, and the threshold of each starting point is solved. Base on that, the knowledge rules are defined and the defect knowledge base is constructed. Finally, a new experiment is designed to obtain the theoretical starting point of each state of the product surface in the building process. By comparing the theoretical starting point with the actual starting point, the feasibility of the knowledge rules in monitoring the nozzle working state is verified.