Yifeng Zhang 
- : Deep hybrid neural network-aided electromechanical impedance method for automated damage detection of lining concrete under freeze-thaw cycling. Dans: Structural Health Monitoring.
- (2024): Nondestructive detection of fiber content in steel fiber reinforced concrete through percussion method coordinated with a hybrid deep learning network. Dans: Journal of Building Engineering, v. 86 (juin 2024).
- (2023): Intelligent monitoring of concrete-rock interface debonding via ultrasonic measurement integrated with convolutional neural network. Dans: Construction and Building Materials, v. 400 (octobre 2023).
- (2023): A comparison of ultrasonic temperature monitoring using machine learning and physics-based methods for high-cycle thermal fatigue monitoring. Dans: Structural Health Monitoring, v. 23, n. 3 (septembre 2023).
- (2023): An innovative deep neural network coordinating with percussion-based technique for automatic detection of concrete cavity defects. Dans: Construction and Building Materials, v. 400 (octobre 2023).
- (2022): Co-located dual-wave ultrasonics for component thickness and temperature distribution monitoring. Dans: Structural Health Monitoring, v. 22, n. 2 (mai 2022).
- (2022): Damage Detection of Bridge Structures Under Vehicle Loads Using Moving-Window Correlation Coefficient of Signals with Limited Sensors. Dans: International Journal of Structural Stability and Dynamics, v. 22, n. 9 (mars 2022).
- (2023): Damage detection for bridge structures under vehicle loads based on frequency decay induced by breathing cracks. Dans: Structure and Infrastructure Engineering, v. 19, n. 6 (septembre 2023).
- (2021): Damage identification for bridge structures based on correlation of the bridge dynamic responses under vehicle load. Dans: Structures, v. 33 (octobre 2021).
- (2020): Ultrasonic monitoring of pipe wall interior surface temperature. Dans: Structural Health Monitoring, v. 20, n. 5 (décembre 2020).
- (2019): Damage Detection in Bridge Structures under Moving Vehicle Loads Using Delay Vector Variance Method. Dans: Journal of Performance of Constructed Facilities (ASCE), v. 33, n. 5 (octobre 2019).
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