A method of laser point temperature detection based on CNN
Ruidong Xie, Haichuan Yang, Yingmin Yi, Qimeng Shi, Keying Wang, Jia‐Bin Huang · 2020
There has been a direct relationship between the temperature of the laser point and the quality of the casting in the process of the 3D printing. In the paper, a method based on convolutional neural network (CNN) was proposed to estimate the temperature of the laser point. The collected temperature data used were trained by the deep-learning method. A new structure of the model was proposed on the part of the CNN model, which improved from original LeNet. The process of the prediction for the testing set was carried out through the new model. The unknown temperature in the testing set can be estimated. The experimental result illustrates that the proposed method is satisfactory.