A study on shape of electromagnetic guideway for continuous steel plates by analysis of multi-body dynamics

Narawa, Yasuhiro; Ishihara, Sora; Yamaguchi, Ryo; Bessho, Takahiko; Liu, Xiaojun; Kato, Takuya; Ikeda, Keigo; Endo, Ayato; Narita, Toshio; Kato, Hideaki

doi:10.3233/jae-209461

Cited by 1 publication

(2 citation statements)

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“…In (6),l is the number of convolutional layers in the model,k l ij is the number of convolution kernels,b l j is the additive bias,f is the activation function, and M j is the input image. The convolutional collection layer is defined as:…”

Section: Deep Learning Neural Networkmentioning

confidence: 99%

“…The quality of the steel plate determines the quality of downstream products. However, while producing the steel plates, impurities, scratches, and cracks often appear on the surface of the steel plates due to raw materials, production equipment, and production processes [6]. Usually, welding technology is utilized for connection and repair.…”

Section: Introductionmentioning

confidence: 99%

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Weld Defect Detection and Image Defect Recognition Using Deep Learning Technology

Deng

Feng

et al. 2021

Preprint

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Welding defects not only bring several economic losses to enterprises and individuals but also threatens peoples lives. We propose a deep learning model, where the data-trained deep learning algorithm is employed to detect the weld defects, and the Convolutional Neural Networks (CNNs) are utilized to recognize the image features. The Transfer Learning (TL) is adopted to reduce the training time via simple adjustments and hyperparameter regulations. The designed deep learning-based model is compared with other classic models to prove its effectiveness in weld defect detection and image recognition further. The results show this model can accurately identify weld defects and eliminates the complexity of manually extracting features, reaching a recognition accuracy of 92.54%. Hence, the reliability and automation of detection and recognition is improved signifificantly. Actual application also verififies the effectiveness of TL in weld defect detection and image defect recognition. Therefore, our research results can provide theoretical and practical references for effificient automatic detection of steel plates, cost reduction, and the high-quality development of iron and steel enterprises.Index Terms - convolutional neural network, deep learning, image detect recognition, transfer learning, weld defect detection

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Section: Deep Learning Neural Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%