Damage identification for mining wire rope based on continuous wavelet transform and convolutional neural network-Reference-Cited by-同舟云学术

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Damage identification for mining wire rope based on continuous wavelet transform and convolutional neural network

Published:2024-07-24 Issue: Volume: Page:1-23
ISSN:1058-9759
Container-title:Nondestructive Testing and Evaluation
language:en
Short-container-title:Nondestructive Testing and Evaluation

Author:

Tian Jie¹²,Zhao Chun¹²,Wang Hongyao¹²

Affiliation:

1. School of Mechanical and Electrical Engineering, China University of Mining and Technology, Beijing, China

2. Key Laboratory of Coal Mine Intelligence and Robot Innovative Application, Ministry of Emergency Management, China University of Mining and Technology, Beijing, China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10589759.2024.2383790

Reference45 articles.

1. A novel texture-based damage detection method for wire ropes

2. Wire Rope Defect Recognition Method Based on MFL Signal Analysis and 1D-CNNs

3. Highly Stabilized Phase-Shifted Fiber Bragg Grating Sensing System for Ultrasonic Detection

4. Combination of in-situ diffraction experiments and acoustic emission testing to understand the compression behavior of Mg-Y-Zn alloys containing LPSO phase under different loading conditions

5. Quantitative non-destructive evaluation of drilling defects in SiCf/SiC composites using low-energy X-ray imaging technique

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