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Related Concept Videos

Ultrasonography01:17

Ultrasonography

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Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called...
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Bolt Anchorage Defect Identification Based on Ultrasonic Guided Wave and Deep Learning.

Hui Xing1, Weiguo Di1, Xiaoyun Sun2

  • 1School of Electrical and Electronic Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China.

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Summary

This study introduces a novel method using guided wave time-frequency spectrum and a gated attention residual network (GA-ResNet) for non-destructive testing of bolt anchorages. The approach accurately identifies defects, enhancing structural safety in geotechnical engineering.

Keywords:
anchorage recognitioncontinuous wavelet transformdeep learningnon-destructive testingultrasonic guided wave

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Area of Science:

  • Geotechnical Engineering
  • Non-Destructive Testing
  • Signal Processing

Background:

  • Bolt anchorage quality is crucial for the safety of geotechnical structures like bridges and tunnels.
  • Ultrasonic guided wave testing is a common non-destructive method, but faces challenges from environmental noise, modal mixing, and dispersion.
  • Extracting defect features from guided wave signals in traditional domains is difficult.

Purpose of the Study:

  • To develop an effective method for non-destructive testing of anchorage quality using ultrasonic guided waves.
  • To overcome limitations of traditional signal processing in identifying defects.
  • To improve the structural safety assessment of geotechnical engineering components.

Main Methods:

  • Utilized the time-frequency spectrum of guided wave signals as input features.
  • Developed and applied a gated attention residual network (GA-ResNet) for anchorage model type recognition.
  • GA-ResNet incorporates a gating mechanism to balance spatial and channel attention for improved feature extraction.

Main Results:

  • The proposed GA-ResNet method demonstrated high effectiveness in predicting anchorage bolt defect types.
  • Experiments on four different anchorage models validated the method's performance.
  • The approach successfully addressed challenges posed by complex signal characteristics.

Conclusions:

  • The combination of guided wave time-frequency spectrum and GA-ResNet offers a robust solution for non-destructive evaluation of anchorage quality.
  • This method can significantly enhance the safety of geotechnical structures by enabling early detection of defects.
  • The study provides a valuable tool for preventing potential safety accidents in civil engineering.