Identification of Crack-like Defects Based on Methods of Magnetic Inspection and Neural Networks Technologies

اسناد مشابه

• Double Cracks Identification in Functionally Graded Beams Using Artificial Neural Network

  مقاله۲۰۱۳Journal of Solid MechanicsF Nazari, M.H Abolbashari

  This study presents a new procedure based on Artificial Neural Network (ANN) for identification of double cracks in Functionally Graded Beams (FGBs). A cantilever beam is modeled using Finite Element Method (FEM) for analyzing a double-cracked FGB and evaluation of its first four

• Customized Convolutional Neural Networks Technology for Machined Product Inspection

  مقاله‌ی دسترسی آزاد۲۰۲۲Applied sciences['Yi-Cheng Huang', 'Kuo-Chun Hung', 'Chun‐Chang Liu', 'Ting-Hsueh Chuang', 'Shean-Juinn Chiou', '']

  Metal workpieces are an indispensable and important part of the manufacturing industry. Surface flaws not only affect appearance, but also efficiency workpiece reduce safety product. Therefore, appearance product needs to be inspected determine if there surface defects, such as s

• Defects Identification in Textile by Means of Artificial Neural Networks

  سند علمی۲۰۰۸ICICVitoantonio Bevilacqua, Lucia Cariello, Giuseppe Mastronardi, Vito Palmieri

  In this paper we use a neural network approach for defects identification in textile. The images analyzed came from an artificial vision system that we used to acquire and memorize them in bitmap file format. The vision system is made of two grey scale line scan camera arrays and

• IDENTIFICATION OF DEFECTS IN A COATING WEDGE BASED ON ULTRASONIC NON-DESTRUCTIVE TESTING METHODS AND CONVOLUTIONAL NEURAL NETWORKS

  مقاله‌ی دسترسی آزاد۲۰۲۳??????? ????????? ????????????? ?????????????????? ???????????????? ????????????['A. N. Soloviev', 'B. V. Sobol', 'P. V. Vasiliev', 'A. V. Senichev', 'A. I. Novikova', '']

  The paper deals with the identification of a crack-like defect in coated wedge based on ultrasonic nondestructive testing. authors propose an approach followed by determination its geometrical parameters. is shadowed testing method combined deep machine learning technologies. A w

• A Novel Classification Method using Effective Neural Network and Quantitative Magnetization Transfer Imaging of Brain White Matter in Relapsing Remitting Multiple Sclerosis

  مقاله۲۰۱۸Journal of Biomedical Physics and EngineeringM Fooladi, H Sharini, S Masjoodi, E Khodamoradi

  Background: Quantitative Magnetization Transfer Imaging (QMTI) is often used to quantify the myelin content in multiple sclerosis (MS) lesions and normal appearing brain tissues. Also, automated classifiers such as artificial neural networks (ANNs) can significantly improve the i

• Inspection System for Vehicle Headlight Defects Based on Convolutional Neural Network

  مقاله‌ی دسترسی آزاد۲۰۲۱Applied sciences['Chang-bae Moon', 'Jong-Yeol Lee', 'Dong-Seong Kim', 'Byeong-Man Kim', '']

  This paper proposes a method to detect the defects in region of interest (ROI) based on convolutional neural network (CNN) after alignment (position and rotation calibration) manufacturer’s headlights determine whether vehicle are defective. The results were compared with an exis