Technical Code Analysis of Geomagnetic Flaw Detection of Suppression Rigging Defect Signal Based on Convolutional Neural Network DOI Creative Commons
Gang Zhao, Changyu Han,

Zhongxiang Yu

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 11852 - 11852

Published: Dec. 18, 2024

In this paper, technical code analysis and recognition of the defect signal suppression rigging based on a convolutional neural network are carried out given difficulty low rate detection rigging. Firstly, magnetic induction defects is collected using CM-801 (Anshan, China), Kalman filtering used to screen pre-process data, noise reduction data presented in form cloud image. The pressed set constructed, region broken wire stress image calibrated. single-stage object algorithm YOLOv5 (You Only Look Once) model calculation used, scale layer positioning loss function improved optimized, for experiments. experimental results show that accuracy convolution can reach 97.1%, which effectively identify suppressed

Language: Английский

Technical Code Analysis of Geomagnetic Flaw Detection of Suppression Rigging Defect Signal Based on Convolutional Neural Network DOI Creative Commons
Gang Zhao, Changyu Han,

Zhongxiang Yu

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 11852 - 11852

Published: Dec. 18, 2024

In this paper, technical code analysis and recognition of the defect signal suppression rigging based on a convolutional neural network are carried out given difficulty low rate detection rigging. Firstly, magnetic induction defects is collected using CM-801 (Anshan, China), Kalman filtering used to screen pre-process data, noise reduction data presented in form cloud image. The pressed set constructed, region broken wire stress image calibrated. single-stage object algorithm YOLOv5 (You Only Look Once) model calculation used, scale layer positioning loss function improved optimized, for experiments. experimental results show that accuracy convolution can reach 97.1%, which effectively identify suppressed

Language: Английский

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