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공정 매개변수 및 열화상 이미지를 기반으로 한 다공성 결함감지를 위한 고압 다이캐스팅 결함 예측 딥러닝 알고리즘에 관한 연구
김재선,박춘우,박원석,박영현,조창현,김동주 한국CDE학회 2023 한국CDE학회 논문집 Vol.28 No.3
Existing analysis methods have limitations in identifying the exact cause of defects because sev- eral variables cause defects in a complex manner in the high-pressure die-casting process. How- ever, as data processing speeds increase and analysis technologies advance, research activities are progressing on techniques to analyze complex manufacturing processes. In this study, numerical and image data were collected for the main variables that cause porosity defects in the die-casting process. Based on this, we intend to design a failure prediction algorithm using the HP-GAN(Hypothesis Pruning Generative Adversarial Network) algorithm and verify the algorithm. The HP-GAN algorithm is a combination of CNN(Convolutional Neural Network) and GAN algorithms. The raw data used in HP-GAN are line data derived from the die-casting equipment PLC and thermal images taken before and after spraying on the mold work surface through a thermal imaging camera. data, porosity defect data. To strengthen the algorithm, we used the Mean Squared Error (MSE) formula and the Gradient Decent Algorithm (GDA) to modify the weights of the algorithm to increase the prediction accuracy.
김재선,박성열,차승봉,주민호 한국농·산업교육학회 2017 농업교육과 인적자원개발 Vol.49 No.2
Social network services(SNSs) have impacted various aspects of education because they are considered helpful to students’ learning. Several studies verified their effects on learning outcomes. However, there is still a lack of empirical evidence on the significance of SNS use. We conducted an online survey of 543 university students in Seoul, South Korea. Several multiple regression analyses were carried out to test hypotheses after two factor analyses to verify construct validities. According to the results of factor analysis, students’ learning outcomes fall into the following domains: social domain(SD), cognitive domain(CD), affective domain(AD), and psychomotor domain(PD). Students’ participation in SNSs(SP) and their social acceptance in SNSs(SA) influenced learning outcomes based on SNS. Unlike in previous study results, attitude towards school life(AT) was not significantly related to all learning outcomes. SP was identified as a key variable because it has effects on all learning outcomes.