0
research-article

Identification of Asynchronous Blade Vibration Parameters by Linear Regression of Blade Tip Timing Data

[+] Author and Article Information
Abbas Rohani Bastami

Assistant Professor, Faculty of Mechanical and Energy Systems Engineering, Abbaspour School of Engineering, Shahid Beheshti University, Tehran, Iran
a_rohani@sbu.ac.ir

Pedram Safarpour

Assistant Professor, Faculty of Mechanical and Energy Systems Engineering, Abbaspour School of Engineering, Shahid Beheshti University, Tehran, Iran
p_safarpour@sbu.ac.ir

Arash Mikaeily

Faculty of Mechanical and Energy Systems Engineering, Abbaspour School of Engineering, Shahid Beheshti University, Tehran, Iran
arashmikaily@gmail.com

Mohammad Mohammadi

Faculty of Mechanical and Energy Systems Engineering, Abbaspour School of Engineering, Shahid Beheshti University, Tehran, Iran
mohammadmec69@gmail.com

1Corresponding author.

ASME doi:10.1115/1.4038880 History: Received March 29, 2017; Revised December 07, 2017

Abstract

Fracture of blades is usually catastrophic and creates serious damages in the turbomachines. Blades are critical components which are subjected to high centrifugal force, oscillating stresses and high temperature. Therefore, blades life is limited and they should be replaced or repaired at appropriate times to prevent their breakdown. Crack detection by non-destructive tests can only be performed during machine overhaul which is not suitable for monitoring purposes. Blade tip timing (BTT) method as a non-contact monitoring technique is spreading for health monitoring of the turbine blades. One of the main challenges of BTT method is identification of vibration parameters from one per revolution samples which is quite below Nyquist sampling rate. In this study, a new method for derivation of blade asynchronous vibration parameters from BTT data is proposed. The proposed method requires only two BTT sensors and applies least mean square algorithm to identify frequency and amplitude of blade vibration. These parameters can be further used as blade health indicators to predict defect growth in the blades. The efficiency of the method is examined by numerical simulation of vibrations in presence of noise. An experimental test was conducted on a bladed disk to show efficiency of the proposed method.

Copyright (c) 2017 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In