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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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A Rail Fault Diagnosis Method Based on Quartic C2 Hermite Improved Empirical Mode Decomposition Algorithm.

Hanzhong Liu1,2, Chaoxuan Qin3, Ming Liu4

  • 1School of Automation, Nanjing Institute of Technology, Nanjing 211167, China.

Sensors (Basel, Switzerland)
|July 31, 2019
PubMed
Summary
This summary is machine-generated.

An improved empirical mode decomposition (EMD) method enhances high-speed rail fault diagnosis. This novel approach significantly boosts accuracy in detecting compound faults using vibration signals.

Keywords:
Hermite interpolationapproximate entropyempirical mode decomposition (EMD)fault diagnosiskurtosis

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Area of Science:

  • Mechanical Engineering
  • Signal Processing
  • Artificial Intelligence

Background:

  • Compound fault detection in high-speed rail (HSR) systems is crucial for safety and reliability.
  • Traditional methods struggle with the complexity of HSR vibration signals, necessitating advanced diagnostic techniques.

Purpose of the Study:

  • To develop an improved empirical mode decomposition (EMD) algorithm for early fault diagnosis of HSR vibration signals.
  • To enhance the accuracy and reliability of compound fault detection in HSR.

Main Methods:

  • An improved EMD algorithm utilizing quartic C² Hermite interpolation was employed to decompose HSR vibration signals into intrinsic mode functions (IMFs).
  • Singular value decomposition (SVD) was applied to IMF components to identify principal components for signal reconstruction.
  • Fault diagnosis was performed using support vector machines (SVM) based on calculated kurtosis and approximate entropy values as eigenvalues.

Main Results:

  • The improved EMD method successfully decomposed complex HSR vibration signals.
  • Reconstructed signals using principal components yielded distinct eigenvalues (kurtosis and approximate entropy) for fault identification.
  • Experimental validation demonstrated superior performance compared to the traditional EMD algorithm in compound fault diagnosis.

Conclusions:

  • The proposed quartic C² Hermite interpolation-based improved EMD algorithm offers a robust solution for early fault diagnosis in high-speed rail.
  • This method significantly improves the accuracy of compound fault detection, surpassing conventional EMD techniques.