Bladed Disk Crack Detection through Advanced Analysis of Blade Passage Signals

7/29/2019 Bladed Disk Crack Detection through Advanced Analysis of Blade Passage Signals

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Bladed Disk Crack Detection

through

Advanced Analysis of Blade Passage Signals

Ottawa- Carleton Institute for Mechanical Engineering

Ottawa, Canada

Fall 2012

By: Elhamosadat Alavi Foumani


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2

Outline

Introduction

Measurements and Experimental set up

Tip Clearance and Time of Arrival Preprocessing Analysis

Statistical Wavelet Analysis

Conclusions

Future works

Acknowledgement


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Source: http://www.bbc.co.uk/news/world-africa-18831686

http://usatoday30.usatoday.com


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Blade position measurements

Spin pit test facility

Apparatus for predicting failures of spinning disks

Input Data: Tip clearance, and Time of Arrival

Introduction

4


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Crack in hub

Measurements Scheme

5

Asymmetric deformation of a turbo machinery disk due to crack

propagation at the base of a set of blades

Blade length on healthy hub

(including temperature and RPMvariation)

Lengthened blades

* A. Von Flotow, "Apparatus and method for predicting failures of spinning disks in turbo-machinery."

U.S. Patent No. 6,785,635. 31 Aug. 2004.


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Measurements

6

Changes in blade length as a turbo disk is cycled.

Blade length

on healthy hub

Blade length

near hub crack

Elastic deformation increases

with decreasing hub stiffness

Plastic deformation: Blade does not

retract during spin-down cycle

6

A general illustration of sensor response and of identify blade deformation.

* A. Von Flotow, "Apparatus and method for predicting failures of spinning disks in turbo-machinery."

U.S. Patent No. 6,785,635. 31 Aug. 2004.


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Tip Clearance Signal Noise Removal

7

Temperature effect Elastic stretch due to centrifugal force

Disk Imbalance effect

Fourier Series

12 cos sin

=

2

cos 2

=

2 sin 2

=

Demean TC signalbased on cycles


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Disk Imbalance Sinusoidal effect

8

The sinusoidal effects carried by the TC signal and caused by the rotor imbalance:

(a) the sinusoidal effects over 1408 cycles; (b) the magnitude; (c) the phase.

Magnitude

Phase tan( )


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Tip Clearance Preprocessing Analysis

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(a) The localized standard deviation trend of the magnitudes of

the sinusoidal effects carried by the TC signal; and (b) the

localized standard deviation trend of the phases.


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Time of Arrival Preprocessing Analysis

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dt = dy / (R ) = dx / (R tan )Deviation in Time of Arrival is an interpretationof axial displacement of a blade


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11

Angular deformation of rotor shaft causes a harmonic term in Time of Arrival

The shaft bending due to eccentricity which causes an Angular Deflection

and a Radial Displacement dR

dR


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12

The sinusoidal effects carried by the ToA signal and caused by the shaft bending: (a) the

sinusoidal effects over 1408 cycles; (b) the magnitude; and (c) the phase;



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13

The sinusoidal effects carried by the ToA signal and caused by the

shaft bending: (a) the localized standard deviation trend of themagnitudes; and (b) the localized standard deviation trend of the

phases.


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Digital Signal processing Techniques

14

, 1 , , 0+

Time Domain analysis

Frequency domain Analysis

Time-Frequency Domain analysis

Wavelet Transform Analysis

Daubechies 4


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15

0

10

20

30

40

0

20

40

60

0

1

2

3

4

Blade #Scale #

S

TDofWTCoef

The standard deviation of the wavelet coefficients over 48scales for 40 blades based on the Time-of-arrival signal.


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The standard deviation of the wavelet coefficients over 48scales for 40 blades based on the Tip Clearance signal.


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The STD of the wavelet coefficients over 48 scales for1408 cycles based on the Tip Clearance signal.


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Conclusions

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Having proper denoising prior to analyses, application of the wavelet method for

fault detection in bladed discs found to be promising. Results show that the statistical

wavelet analysis technique is capable of providing useful indicative information for

locating the incipient crack that occurs in the bladed disk

The crack initiation time can be determined by using the suggested localized standard

deviation of the sinusoidal effects caused by the rotor imbalance

It was found that the physical based modeling, can effectively characterized the

noises induced by various known factors other than defects such as thermal and

centrifugal expansions, rotor imbalance, and shaft bending effects. These noises

subsequently removed.


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Future works

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The present work is done based on the Tip clearance and Time of arrival data provided

by LPT Inc. The available data may not allow more comprehensive analysis. If

additional data are available in future, further studies in the following directions could

be worth exploring:

Identifying the various stages of damage evolution during its life cycle by

extracting other effective parameters except standard deviation and kurtosis from

wavelet map.

Different wavelets be examined to develop efficient algorithms to identify the

stress levels, crack initiation, crack growth to its final rupture.

The characteristics of the modulation change during the life cycle of the disk spin

rig test should be examined.


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Acknowledgement

21

I would like to acknowledge people who made this work possible:

Prof. Ming Liang, Dept. of Mechanical Engineering, University of

Ottawa

Prof. Jie Liu, Dept. of Mechanical and Aerospace Engineering,

Carleton University

Life Prediction Technologies Inc. (LPTi)


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Thank you for your

attention

22

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Bladed Disk Crack Detection through Advanced Analysis of Blade Passage Signals

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