Related Experiment Video
Updated: Feb 10, 2026

A Polymer-based Piezoelectric Vibration Energy Harvester with a 3D Meshed-Core Structure
Published on: February 20, 2019
Effective Crack Detection in Railway Axles Using Vibration Signals and WPT Energy
María Jesús Gómez1, Eduardo Corral2, Cristina Castejón3
1Universidad Carlos III de Madrid, Mechanical Engineering Department, 28911 Madrid, Spain. mjggarci@ing.uc3m.es.
Abstract:
Crack detection for railway axles is key to avoiding catastrophic accidents. Currently, non-destructive testing is used for that purpose. The present work applies vibration signal analysis to diagnose cracks in real railway axles installed on a real Y21 bogie working on a rig. Vibration signals were obtained from two wheelsets with cracks at the middle section of the axle with depths from 5.7 to 15 mm, at several conditions of load and speed. Vibration signals were processed by means of wavelet packet transform energy. Energies obtained were used to train an artificial neural network, with reliable diagnosis results. The success rate of 5.7 mm defects was 96.27%, and the reliability in detecting larger defects reached almost 100%, with a false alarm ratio lower than 5.5%.
Related Concept Videos
Effects of Temperature on Free Energy
Energy and Power Signals
What is Energy?
Energy Basics
Effects of EDTA on End-Point Detection Methods
In the visual method, metal-ion indicators (metallochromic dyes), which have distinct colors in their free and complex forms, are added to the mixture to signal the titration's end point. They form stable complexes with metal ions, but these complexes are weaker than the corresponding metal–EDTA complexes. As a...
Vibrating Concrete

