专题：Non-Destructive Testing Techniques

This cluster of papers focuses on non-destructive techniques based on eddy current testing, including pulsed eddy current and magnetic flux leakage methods. The papers cover topics such as defect detection, sensor design, feature extraction, and material characterization using advanced signal processing and machine learning techniques.
最新文献
Magnetic Barkhausen Noise Sensor: A Comprehensive Review of Recent Advances in Non-Destructive Testing and Material Characterization

article Full Text OpenAlex

Defect Depth Quantification Method Under Unknown Lift-Off Based on Time-Domain Magnetic Flux Leakage Signal Features

article Full Text OpenAlex

An Eddy Current Method for Electromagnetic Property and Diameter Measurements of Metallic Rods Immune to Sensor Offset

article Full Text OpenAlex

Accelerated corrosion mechanism of AA5083 coupled with Al-Zn-In anodes: An impedance analysis

article Full Text OpenAlex

Advanced prediction of pipeline vertical deformation and axial strain via multi-source data fusion and multi-task deep learning

article Full Text OpenAlex

Integrated Finite Element Neural Network (IFENN) for phase-field fracture with minimal input and generalized geometry-load handling

article Full Text OpenAlex

Discovery of fatigue strength models via feature engineering and automated eXplainable machine learning applied to the welded transverse stiffener

article Full Text OpenAlex

A physics-informed residual neural network in the meta-learning framework with non-proportionality measurement for multiaxial fatigue life prediction

article Full Text OpenAlex

Transformer vs Classical Machine Learning: Harnessing Normalization for Enhanced Asset Life Prediction

article Full Text OpenAlex

An integrated in-situ micro-electrochemical investigation on the corrosion mechanism of stress corrosion crack in X80 pipeline steel

article Full Text OpenAlex

近5年高被引文献
Loss of Life Transformer Prediction Based on Stacking Ensemble Improved by Genetic Algorithm By IJISRT

article Full Text OpenAlex 1320 FWCI294.2789

YOLO-v1 to YOLO-v8, the Rise of YOLO and Its Complementary Nature toward Digital Manufacturing and Industrial Defect Detection

article Full Text OpenAlex 999 FWCI205.1139

A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations (SHAP)

article Full Text OpenAlex 436 FWCI47.5156

A Systematic Review of Advanced Sensor Technologies for Non-Destructive Testing and Structural Health Monitoring

review Full Text OpenAlex 372 FWCI48.9305

Domain generalization for cross-domain fault diagnosis: An application-oriented perspective and a benchmark study

article Full Text OpenAlex 343 FWCI115.8795

Analyses of internal structures and defects in materials using physics-informed neural networks

article Full Text OpenAlex 326 FWCI36.875

Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges

article Full Text OpenAlex 296 FWCI34.625

Physics-Informed Residual Network (PIResNet) for rolling element bearing fault diagnostics

article Full Text OpenAlex 279 FWCI51.8941

Finite basis physics-informed neural networks (FBPINNs): a scalable domain decomposition approach for solving differential equations

article Full Text OpenAlex 274 FWCI43.1547

A review on physics-informed data-driven remaining useful life prediction: Challenges and opportunities

review Full Text OpenAlex 267 FWCI58.3522