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Anisotropic Magnetoresistive Sensors: Dynamic Modeling and Characterization for Blade Tip-Timing Measurements.

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Updated: Aug 7, 2025

A Rapid Method for Modeling a Variable Cycle Engine
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State-Space Model for Arrival Time Simulations and Methodology for Offline Blade Tip-Timing Software

Tommaso Tocci1, Lorenzo Capponi1, Gianluca Rossi1

  • 1Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy.

Sensors (Basel, Switzerland)
|March 11, 2023
PubMed
Summary

This study introduces a mathematical model to create synthetic blade tip-timing signals for testing vibration analysis software. This helps quantify software uncertainty and improve data accuracy in turbine and compressor testing.

Keywords:
aeromechanicsarrival timeblade vibrationdiagnosticsstate-spacetip-timingturbomachinery

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Area of Science:

  • Mechanical Engineering
  • Aerospace Engineering
  • Vibration Analysis

Background:

  • Blade tip-timing is a crucial non-contact technique for measuring blade vibrations in turbomachinery.
  • Accurate characterization of dynamic behaviors relies on signal processing and parameter sensitivity analysis.
  • Existing methods lack controlled inputs for rigorous software validation.

Purpose of the Study:

  • To develop a mathematical model for generating synthetic tip-timing signals under specific test conditions.
  • To provide a controlled input for characterizing the performance of tip-timing post-processing software.
  • To establish a foundation for quantifying uncertainty in tip-timing data analysis.

Main Methods:

  • A mathematical model was developed to synthesize realistic tip-timing signals.
  • Synthetic signals were used as input for post-processing software.
  • The software's response to controlled inputs was analyzed to assess its characterization capabilities.

Main Results:

  • The study successfully generated synthetic tip-timing signals representative of actual test scenarios.
  • The generated signals enabled a detailed characterization of tip-timing analysis software.
  • This work is the first step in quantifying software-induced uncertainty in measurements.

Conclusions:

  • The proposed synthetic signal generation methodology is effective for validating tip-timing analysis software.
  • This approach aids in understanding and quantifying measurement uncertainty.
  • The methodology supports further sensitivity studies to enhance data analysis accuracy in turbomachinery testing.