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  • Open Access

    ARTICLE

    Deep Learning Model for Identifying Internal Flaws Based on Image Quadtree SBFEM and Deep Neural Networks

    Hanyu Tao1,2, Dongye Sun1,2, Tao Fang1,2, Wenhu Zhao1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 521-536, 2025, DOI:10.32604/cmes.2025.072089 - 30 October 2025

    Abstract Structural internal flaws often weaken the performance and integral stability, while traditional nondestructive testing or inversion methods face challenges of high cost and low efficiency in quantitative flaw identification. To quickly identify internal flaws within structures, a deep learning model for flaw detection is proposed based on the image quadtree scaled boundary finite element method (SBFEM) combined with a deep neural network (DNN). The training dataset is generated from the numerical simulations using the balanced quadtree algorithm and SBFEM, where the structural domain is discretized based on recursive decomposition principles and mesh refinement is automatically… More >

  • Open Access

    ARTICLE

    Detection of Cracks in Aerospace Turbine Disks Using an Ultrasonic Phased Array C-scan Device

    Qian Xu1,*, Haitao Wang1,2, Zhenhua Chen3, Zhigang Huang3, Pan Hu1

    Structural Durability & Health Monitoring, Vol.15, No.1, pp. 39-52, 2021, DOI:10.32604/sdhm.2021.014815 - 22 March 2021

    Abstract Crack detection in an aerospace turbine disk is essential for aircraft- quality detection. With the unique circular stepped structure and superalloy material properties of aerospace turbine disk, it is difficult for the traditional ultrasonic testing method to perform efficient and accurate testing. In this study, ultrasound phased array detection technology was applied to the non-destructive testing of aviation turbine disks: (i) A phased array ultrasonic c-scan device for detecting aerospace turbine disk cracks (PAUDA) was developed which consists of phased array ultrasonic, transducers, a computer, a displacement encoder, and a rotating scanner; (ii) The influence… More >

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