Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization

This study addresses the critical challenge of insufficient classification accuracy for different defect signals in rail magnetic flux leakage (MFL) detection by proposing an enhanced intelligent classification framework based on particle swarm optimized radial basis function neural network (PSO-RBF...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:Sensors
المؤلفون الرئيسيون: Kailun Ji, Ping Wang, Yinliang Jia
التنسيق: مقال
اللغة:الإنجليزية
منشور في: MDPI AG 2025-06-01
الموضوعات:
rail defect detection
magnetic flux leakage (MFL) testing
feature selection
intelligent classification
model optimization
imbalanced data
الوصول للمادة أونلاين:https://www.mdpi.com/1424-8220/25/13/3962

الانترنت

https://www.mdpi.com/1424-8220/25/13/3962

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