Reliability Assessment of Automated Eddy Current System for Turbine Blades

8/2/2019 Reliability Assessment of Automated Eddy Current System for Turbine Blades

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RELIABILITY ASSESSMENT OF AUTOMATED EDDY CURRENT

SYSTEM FOR TURBINE BLADES

Yung-How Wu, Chu-Chung Hsiao (Materials Research Laboratories, Industrial Technology

Research Institutes, Taiwan)([email protected])

Abstract

This paper outlines our effort to develop an automated eddy current method assisted by a

self-aligned manipulator scanning along the disk rim of Westinghouse turbine. The

light-weighted manipulator was mainly designed for inspecting blade on L-2 stage disk

where root cracks were most frequently found during ISI. A mock-up with changeable

blades was used to assess the performance of this technique by statistical method.

Experimental results showed that the POD of this technique agreed well with that

originally proposed. The technique was also proved feasible in field trials.

Introduction

Blades and disk rim of turbine were frequently subjected to fatigue cracking and resulted in

unscheduled shutdown and even more a total failure of turbines. Hence, reliable routine

inspection is crucial to operation safety and efficiency of turbines operation. Although

various NDE techniques have been applied in ISI for this region for years, continue

improvement of the inspection techniques is still desired due to the critical role of steam

turbines and the inspection difficulties in this region. Among which, MT and manual ET

have been the favorite methods.[1-8]

There is no statistical data to refer to how small the crack size can be detected by the

current inspection methods. In principle, it was not difficult to detect 0.5mm crack with

fluorescent MT or manual ET methods. In practical cases, since the gap between disks was

quite narrow, it only allowed the inspector to observe the MT results from a distance or to

stretch his arm to scan the hand-held EC probes. Hence, MT will easily miscall the tight

and tiny cracks or those close to the edge of the serration. Inconsistency between MT and

ET results was always found especially for cracks smaller than 1 mm. To minimize the

human error, an automated EC inspection method was then developed as a supplement to

the current ISI. Crack as small as 0.5mm exposed on end face was set as the target to detect

with this method. And, Westinghouse type blade as shown in Fig. 1 was the inspection

target of this research.


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Airfoil-lead EdgeAirfoil-trail Edge

Fig. 1 Westinghouse turbine blade.

Auto Eddy Current Inspection Technique

The main goal of EC inspection automation was to develop a scanner-assisted method to

inspect blade root cracking on L-2 stage of Westinghouse steam turbine. The scanner was

designed to run on the extruded part of disk rim of Westinghouse steam turbine L-2 stage

as its rail, and use L-1 stage disk rim as its supporting face of the scanner. Accordingly, thescanner can run along the disk in circumferential direction between adjacent disks (as

shown in Fig. 2). The scanner could be stopped and locked automatically at proper position

of each blade to perform following inspection by scanning probe along the tangential of

blade root corners where cracks could be present as shown in Fig 3. After the inspection on

each blade, the scanner would be moved to next blade and all the blades will be inspected

in such a process.

Fig. 2 Automated scanner for blade crack inspection.


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Probe : UNIWEST US-686Frequency : 2.0 MHz

Gain X/Y : 15/15 dB

Phase : 183 deg.

Fig. 3 Different scanning routes (left) and relevant signal responses (right).

The probe was specially designed with a set of leaf spring to produce consistent contact

between probe and inspection area of the blade. The coil diameter of probe was of 3mm

with working frequency of 1-2 MHz that proved sensitive enough to obtain the result not

being interfered by accompanying unnecessary signal especially from corners of steeple.

Practical scanning route was adjusted to have the best performance of the inspection signal

during initial setup. Fig. 3 shows an example of signal on impedance plane from various

scanning routes on a real 13mm root crack. Lift-off signal in horizontal direction and crack

signal were almost perpendicular. When the scanning route running further from the

common tangent the crack signal pattern was thin and long which could be easily

differentiated between lift-off signal and noise. When the route running closer to the

groove edge the crack signal was influenced by the edge effect to deform, closer the probe

to the edge more obvious the influence of the edge effect until the crack signal was finally

replaced by the edge and lift-off signal totally.

The Reliability Assessment

Performance demonstration is a crucial procedure for any NDE method to meet theinspection requirements. It was normally carried out on real components or mock-up and,

sufficient number of tests is required to produce a quantitative and objective assessment.

In principle, when a NDE method or personnel is to inspect a defect of critical dimension

not all the defects of the same dimension could be detected. Similarly, repeated inspections

on a specific defect would not detect the defect every time. Although automated inspection

could avoid most of the human errors, statistic assessment is thus required to assure the

performance of the NDE method.

While assessing any NDT system and method statistically, various controllable and


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uncontrollable factors need to be defined. In our inspection method, the controllable factors

include eddy current excitation frequency/ Gain/ Phase/ Filter, probe, scanner initial

setting/ positioning, probe scanning position/ orientation/ speed, defect size/ position/

orientation, whereas main uncontrollable factors include the stability of eddy current

system, probe contact/ wear, circumferential movement of scanner/ positioning/ speed,

blade installation/ surface condition/ defect type and human factors.

The POD has been found properly represented by POD(a) function.[9]

As shown in Fig. 4,

the most common used function was cumulative log normal distribution function or log

odds function and the parameters could be calculated by Maximum likelihood method.

Such a so-called a analysis method could allow fewer samples, says 30 samples is

reasonable. Of course more the sample number higher the confidence level and more the

assessment precision.

Fig. 4 POD curve.

Fig. 5 Example correlation between measured value and defect size a.a


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Basically, analysis method uses a measured value to correlate with real defect size

quantitatively as in Fig. 5. Such a relation requires that:

a a

(a)For any defect with length (or depth) a, the measured value is not unique andcould be modeled with a certain distribution function such as normal distribution.

a

(b)For any defect with length(or depth) a, the POD(a) could be represented by aprobability density function of as)(aga

=deca

a adagaPOD

)()( (1)

(c)The relation between and defect length (or depth) a was normally assumedcorrelated as

)(aga

++= )ln()ln( 10 aa (2)

where,

aln is the relative measured value of defect,

)ln(a is the relative value of defect,

is the random error and is a normal distribution,

)ln(10

a + is the regression of average of each distribution.

(d)Defect is considered present only if , and POD(a) may be written asdecaa >[ ]

[ ]

[

[ ])ln()ln(

)ln()ln(o

)ln()ln(

)(

10

10

aaProb

aabPr

aaProb

aaProbaPOD

dec

dec

dec

dec

>=

>++=

>=

>=

] (3)

Reliability Experiment

To meet the number of defects required for experiment, we used notches as artificial cracks

on blades for evaluation. Fig. 6 showed defect signal of notch and real crack were

recognizable. The only differences between them were phase and amplitude. The signal

characteristic as shown suggested that the notch can be used to simulate crack. To test the

mechanical performance of the scanning system, 9 pieces of cracked blades were used on a

mock up at each experiment as shown on Fig. 7. Scanner was installed on the mock up to

perform simulated scanning, each blade could be replaced easily according to the

requirement of random sampling. The cracks on the blades were simulated by EDM notch

with length between 0.3-2.5mm.


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Probe typeUNIWEST RPDS-12 differential

Parameter Settings Test sampleReal blade with EDM notch

Frequency 2.0 MHz

Bandwidth HF Scanningroot area of bladePreamplifier 6 dB

Gain Y/X 17dB / 17dB

Phase 119 deg

Dot Position Y / X 0 / 0

Filter LP80Hz / HP0.5Hz

Impedance response

Fig. 6 Signal response of 2mm0.3mm (lengthwidth) notch on sample 1.

Fig. 7 Mock-up with 9 blades interchangeable.


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Results

The flowchart of POD analysis was shown in Fig. 8. Relative dimensions (Di) of a certain

notch could be defined with reference to a specific sample with notch 2.5mm in length as

in Eqa (4). The signal amplitude(Ai) of a certain notch on impedance plane (Fig. 9) was

normalized by the maximum defect amplitude(A2.5) of the reference notch.

)5.2(5.2

mmA

AD ii = (4)

To read amplitude

of defect signal

To convert amplitude

to defect size

To use Range & Bartlett test

To verify the similarity of ln distribution

To use linear regression analysis

to find interce t ( 0 & slo e ( 1

To determine

2

21

2

2 )1(

=

sn

To calculate s

1

)(1

2

2

= =

n

xxs

n

i i

no

Retest

Discard

yes

To determine a valuedec

To determine POD curve by

=

aaaPOD dec

lnln1)( 10

Fig. 8 Flow chart of POD determination.


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Defect

Noise

Gain:10dB

Ai

Gain:7dB

A2.5

Fig. 9 To determine defect size from reference signal.

Two charts of distribution of various defect detections were shown in Fig. 10, then totransfer the individual signal by natural log. The range and variance of defect length were

first shown in table 1. Theoretically, all the distributions should be normal which could be

verified by the Bartlett test by confirming that the variance equivalence of various test data

was satisfied where the significance level was assumed as 0.01. Then critical value of

Bartlett distribution (bk(, n1, n2, n3,, nk)) was then found as

)7,13,14,14,14,14,01.0(6b

8014.076

)6410.0(7)8096.0(13)4)(8195.0(14=

++

(5)

The mixed estimate of sample variance was

kN

sns

ii

k

iP

= =

2

12)1(

676

)037.0(6)026.0(12)088.0080.0131.0169.0(13

+++++=

094.0= (6)

b wasfound as

2

)/(11212

2

12

1 ])...()()[(21

P

kNn

k

nn

s

sssb

k

= (7)

Since b > bk, we may assume the variance of all different defect size were equal which

suggested that all distribution were normal.

Distribution of vs. was found as shown in Fig. 11. By regression, it was

found that intercept (

aln )ln(a

0 )= - 0.0299 and slope (1 )= 0.8784. The freedom () for 6 group of


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different defect size was 5. To assume confidence level = 95% and set = 0.025, it was

found that

832.122

21

=

and 037.0

832.12

)094.0)(16()1(2

21

22 =

=

=

Psn

(8)

Furthermore, to assume

69.0)5.0ln()ln( ==deca (9)

It was found that

75.08784.0

)0299.0(69.0)(ln

1

0 =

=

=

dec

a(10)

and,

042.08784.0

037.0

1

===

(11)

The POD curve could be drawn by finding POD(a) of every defect size as shown in Fig.

12.


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Table 1 Experimental data of signal response method.

Defect number 1 2 3 4 5 6Defect Length

(mm)0.3 0.5 1.0 1.5 2.0 2.5

Defect Length

ln a-1.20 -0.69 0.00 0.41 0.69 0.92

0.22 -1.52 0.22 -1.52 0.75 -0.29 0.78 -0.25 1.56 0.45 1.47 0.38

0.22 -1.52 0.25 -1.39 0.84 -0.17 0.81 -0.21 1.78 0.58 1.53 0.43

0.22 -1.52 0.28 -1.27 0.91 -0.10 0.84 -0.17 1.78 0.58 1.63 0.68

0.25 -1.39 0.31 -1.16 0.94 -0.06 0.97 -0.03 1.81 0.59 1.97 0.68

0.28 -1.27 0.34 -1.07 1.03 0.03 1.00 0.00 1.88 0.63 1.97 0.68

0.31 -1.16 0.38 -0.98 1.06 0.06 1.06 0.06 1.88 0.63 2.28 0.82

0.38 -0.98 0.41 -0.90 1.16 0.15 1.22 0.20 1.94 0.66 2.50 0.92

0.47 -0.76 0.44 -0.83 1.28 0.25 1.25 0.22 1.97 0.68

0.50 -0.69 0.47 -0.76 1.47 0.38 1.28 0.25 2.06 0.72

0.53 -0.63 0.50 -0.69 1.53 0.43 1.47 0.38 2.19 0.78

0.56 -0.58 0.53 -0.63 1.59 0.47 1.53 0.43 2.28 0.82

0.59 -0.52 0.59 -0.52 1.63 0.49 1.59 0.47 2.59 0.95

0.59 -0.52 0.63 -0.47 1.66 0.50 1.78 0.58 2.81 1.03

Measured

Length

(mm)

Measured

Length

ln a

0.59 -0.52 0.75 -0.29 1.75 0.56 1.97 0.68

Full Range 0.37 1.00 0.53 1.23 1.00 0.27 1.19 0.93 1.25 0.58 1.03 0.54

Variance (s2

) .024 .169 .024 .131 .117 .080 .138 .088 .122 .026 .152 .037

Variance ( )2

ps

094.0

70

037.6026.12088.13080.13131.13169.13

)1(1

2

2

=

+++++=

==

kN

sns

k

i

ii

p


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0

1

2

3

4

5

6

0~0.15

0.3~

0.45

0.6~0.75

0.9~

1.05

1.2~

1.35

1.5~

1.65

1.8~

1.95

2.1~

2.25

2.4~2.55

2.7~

2.85

Measured Length (mm)

Frequency Actual Length0.5mm

0

1

2

3

4

5

0~0.15

0.3~

0.45

0.6~0.75

0.9~

1.05

1.2~

1.35

1.5~

1.65

1.8~

1.95

2.1~

2.25

2.4~2.55

2.7~

2.85

Measured Length (mm)

Frequency

Actual Length2.0mm

Fig. 10 Measured value distribution of various defects.

-2

-1.5

-1

-0.5

0

0.51

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

aln

aln

y=0.8784x-0.0299

R2=0.7792

Fig. 11 Correlation between measured value and defect size a.


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Defect Length (mm)

Fig. 12 POD curve of automated EC inspection.

Conclusion

The signal response analysis was used to establish the practical reliability analysis method

for this automated eddy current inspection system. The probability of detection curve was

shown as a unit step function which indicated the quality of the system was good enough.

When defect length was greater than 0.5mm the POD was almost 100%, in another word

the defect greater than 0.5mm in length could be detected reliably, which was compliant

with the originally proposed target. However, the result was obtained from a mock up in

a well-controlled experimental environment then further test should be carried out in the

field. Through the result this method could be verified whether or not it could be an

alternative of the current inspection method.

Acknowledgement

The authors gratefully acknowledge all their colleagues in Taipower Company in

supporting this program.

References

(1)E. R. Reinhart, A Study of NDE Methods for Turbine Blades and A Critical Review ofTurbine Spindle Inspection, Nondestructive Evaluation of Turbine and Generators, pp.

3-43 to 3-63, 1980.

(2)Steam Turbine Disc Cracking Experience, Volume 6: Description of Turbine RotorModels, EPRI NP-2429-LD, Vol. 6, Project 1398-5, Final Report, June 1982.


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(3)R. J. Ortolano, The Non-destructive Examination of Steam Turbine Blading,Nondestructive Evaluation of Turbines and Generators, pp. 2-7 to 2-14, 1980.

(4)J. Metala, D. O. Willaman, Field Experience with Remote Turbine Blade EddyCurrent Inspection System, Second EPRI Fossil Plant Inspection Conference, San

Antonio, Texas, 1988.

(5)M. Asano, S. Harada, and M. Goto, Inspection Technique and System for DovetailCracking in Turbine Wheels, Proceedings of the 11th International Conference on

NDE in the Nuclear and Pressure Vessel Industries, pp. 25-30, Albuquerque, New

Mexico, USA, 1992.

(6)M. Asano, S. Harada, and M. Goto, Inspection Technique and System for DovetailCracking in Turbine Wheels, Proceedings of the 11th International Conference on


Mexico, USA, 1992.(7)M. Asano, S. Harada, and M. Goto, Inspection Technique and System for Dovetail

Cracking in Turbine Wheels, Proceedings of the 11th International Conference on


Mexico, USA, 1992.

(8)Y.-H. Wu, C.-C. Hsiao, Recent Advancement of ISI for Attachment Area on SteamTurbines in Taiwan, 4

thInternational Conference on Engineering Structural Integrity

Assessment, Cambridge, UK, Sep. 1998.

(9)P. F. Packman, S. J. Klima, R. L. Davies. Jugal Malpani, Joseph Moyzis, WilliamWalker, B. G. W. Yee and D. P. Johnson, Reliability of Flaw Detection by

Nondestructive Inspection, ASM Metals Handbook, 8th edition, Vol. 11, pp. 414-424,

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Reliability Assessment of Automated Eddy Current System for Turbine Blades

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