Spectral Fault Receptive Fields

Version 1.0.0 (9.92 MB) by Stan
Spectral Fault Receptive Fields are intended for analyzing spectral features in signals to support condition monitoring and prognosis.
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Updated 11 Dec 2025

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Spectral Fault Receptive Fields (SFRFs) are a biologically inspired computational framework for analyzing vibration and spectral signals. They act as optimized contrast filters that emphasize characteristic fault frequencies, making degradation patterns more detectable and interpretable.
This toolbox implements the complete SFRF workflow, including:
  • Bearing geometry modelling
  • Automatic computation of characteristic fault-frequency bands
  • Center–surround receptive-field gain functions
  • SFRF computation from temporal or spectral data
  • Parallel-ready FFT and SFRF ensemble processors
SFRFs strengthen the link between spectral patterns and machine condition, enabling early fault detection and diagnosis-informed prognosis for rotating machinery.

Cite As

Muñoz Gutiérrez, Stan, and Franz Wotawa. SFRFs: A MATLAB Toolbox for Health Monitoring of Rotating Machinery. Zenodo, 2025, https://doi.org/10.5281/ZENODO.17631784.

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MATLAB Release Compatibility
Created with R2025b
Compatible with R2014b to R2025b
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.0