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Identification of Blade Vibration Parameters Based on Improved Composite Reference Blade Tip-Timing Method.

Liang Zhang1,2, Xue Hu1, Yitong Zheng1

  • 1Faculty of Mechanical Engineering and Automation, Liaoning University of Technology, Jinzhou 121001, China.

Sensors (Basel, Switzerland)
|April 12, 2025
PubMed
Summary

This study enhances engine blade vibration monitoring by improving the blade tip timing (BTT) method. The new approach accurately measures blade vibration displacement, crucial for engine stability and lifespan.

Keywords:
blade vibrationcompound referenceinstantaneous angular positionnon-OPR BTTstraight line fitting

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Area of Science:

  • Mechanical Engineering
  • Aerospace Engineering
  • Vibration Analysis

Background:

  • Engine blade vibration is critical for stability and lifespan.
  • Accurate monitoring of blade vibration is essential.
  • Conventional blade tip timing (BTT) methods have limitations in accounting for instantaneous rotor speed variations.

Purpose of the Study:

  • To improve the composite reference-based blade tip timing (BTT) method.
  • To enhance the accuracy of blade vibration displacement identification.
  • To address the limitations of constant rotor speed assumptions in BTT.

Main Methods:

  • Derived and solved state space equations for rotor instantaneous angular velocity and position using a Kalman filter.
  • Rectified rotor's instantaneous speed for improved accuracy.
  • Enhanced the composite reference method with multi-sensor straight line fitting (SLF) for all sensors.

Main Results:

  • Successfully rectified rotor's instantaneous speed.
  • Significantly enhanced the precision of blade vibration displacement identification.
  • Validated the improved BTT method's efficacy through simulation experiments.

Conclusions:

  • The improved BTT method provides more accurate blade vibration displacement measurements.
  • Accurate vibration monitoring contributes to improved engine stability and extended lifespan.
  • The enhanced composite reference method with SLF offers a robust solution for engine health monitoring.