E-Journal of Advanced Maintenance Vol.9-2 (2017) 60-65
Japan Society of Maintenology

R&D of Multi-Frequency ECT Algorithms for FBR SG Tubes
Ovidiu MIHALACHE, Toshihiko YAMAGUCHI, Takuma SHIRAHAMA and Masashi
UEDA
Japan Atomic Energy, Sector of Fast Reactor Research and Development, Monju ProjectManagement and Engineering Center,1 Shiraki, Tsuruga-shi, Fukui-ken, 919-1279, Japan
ABSTRACTThe adherence of sodium on the external surface of steam generator tubes of Fast Breeder Reactors adds anadditional level of complexity in the in-service inspection of SGs using eddy current testing. The paper focusses
on research and development of novel multi-frequency algorithms, based on eddy current signals, special
developed and tuned to enhance the signal from defects located on external tube surface and to suppress
electromagnetic noise from the conductive sodium and tube support plates. The application of themulti-frequency algorithm is investigated using both three-dimensional finite element simulations andexperimental measurements from SG tubes soaked and then drained of sodium, in a sodium tank mock-up.
KEYWORDS

ARTICLE INFORMATION

eddy currents, multi-frequency, steam generator, fast breeder reactor, three
dimensional finite element, sodium

Article history:
Received 7 November 2016
Accepted 27 April 2017

1.

Introduction

One of the techniques used in FBR in the in-service inspection of steam generator tubes (SG) isthe eddy current technique (ECT). One of the particularities of SG tubes in FBR is that they aresoaked in sodium during reactor operation. In order to improve the defect detection technique, amulti-frequency ECT technique using the ECT signal at various frequencies is employed to enhance
the signal/noise ratio. For ferromagnetic SG tubes it was shown that the remote field eddy current
technique (RF-ECT) is sensitive to both inner and outer tube defects [1-2]. The application ofmulti-frequency ECT technique for SG tubes of nuclear power plant was also shown to be used for
SG tubes of reactors [3-5], but without sodium and using eddy currents at higher frequencies, above
10 KHz frequency, and using less ECT at lower frequency (lower than 1 KHz) as in the RF-ECT.
Using the RF-ECT, new multi-frequency (MF) algorithms, devised for a bobbin coilconfiguration and named window-MF (WMF) and dynamic-window MF (DWMF), were previously
presented and tested with either signals from two-dimensional or three-dimensional (3D) finite
element (FE) simulations (both with/without sodium) or experimental data, but without sodium
influence when used for helical SG tubes [6-9]. However, because defects are located on the SG tube
outer surface the ECT signal changes due to the influence of the sodium accumulating inside defects.
In the present paper we extend the validation of these algorithms, WMF and DWMF, when using
bobbin coils, with experimental RF-ECT measurements from defects located near the helical tube
support plates in SG tubes similar with FBR tubes, in both cases when sodium covers or does notcover the tube surface. Further application of the method is also extended to the multi-coils detection
units, but using three-dimensional FEM simulations, in order to improve the signal/noise ratio for
detection of smaller outer tube partial defects.

2.

Measurements and 3D FEM simulations of ECT signals for FBR SG tubes

A SG tank mock-up, with three SG tubes attached to large tube support plate (SP), is filled andthen drained of sodium in order to obtain various sodium layers configurations around tube SP andouter tube defects (OD). WMF and DWMF algorithms are investigated and validated on these SG
tubes, before and after sodium adheres to SG tube outer surface.

ISSN-1883-9894/10 © 2010 – JSM and the authors. All rights reserved.

60

F. Lastname, et al./ Title of the Paper

Supportplate(+Defect)

OD20% UP

OD20% MD

OD30% X

SP only

OD30% Y
φ500

a)

b)

c)

Fig. 1. a) SG tubes with three defects (groove OD20%-upper tube, partial OD30%X-middle tube,
partial OD30%-lower tube);b) SG schematics; c) 3D FEM simulation modelFig. 2. RF-ECT system with various detection units: bobbin coil or multi-coils

In a previous paper [7-8], the authors investigated the formation of sodium layers and locationsof sodium drops on the outer SG tube surface, after sodium draining, in a controlled sodium tankmock-up. Three SG tubes similar (geometry and material characteristics: made of Cr-Mo alloy with a
3.8 mm wall thickness) to FBR tubes, as seen in Fig. 1, are inserted through a larger tube SP. The
above configuration rests in a 2 meter diameter larger sodium mockup-tank that surrounds the helicaltubes, tank that is filled with sodium at high temperature (5000C) and then is drained successively, inorder to obtain various sodium configurations. After each sodium drain and cooling down to room
temperature, the ECT signal from detection coils is recorded for various outer tube defects, grooves
OD20%tw (tube wall thickness) and partial OD30%tw on different location of tubes, that are locatednear and under tube SP. The detection unit of the RF-ECT system is presented in Fig. 2 and consists ineither bobbin coil or multi-system coils.

3.

Principles of multi-frequencies algorithms

Multi-frequency (MF) algorithm emphasizes the defect signal and reduces the background noiseby synthesizing the ECT signals at two or more different frequencies. In the standard linear procedure
the combination of two ECT signals is performed by following equation:(1)
S  S1    R( )  S 2
where S1 and S2 are measurement data (real and imaginary components) at two frequencies, while α isthe amplitude coefficient of the signal and R(φ) is the rotation matrix for the Lissajous image in
Fig. 3(left), that rotates the signal with phase φ. Fig. 3(left) shows an example of application of MF
algorithm, where SP measured signal is considered as a noise while the defect signal inthe ”SP+Defect” configuration is the signal that is enhanced by MF algorithm.
In opposition to the MF algorithm that is applied to the all set of data in the Lissajous-form,
the window multi-frequency algorithm sets a window-band and is applied to a reduced window-data[7-9]. Fig. 3(right) shows the principle of WMF. The upper part of the figure shows the arrangementof the SG tube and location of defect under the tube helical support plate. The middle part shows thedefect detection data as it is measured, and how for each subsequently window data, the MF is applied.
The lower part shows the results of the WMF algorithm where the position of S/N ratio localize the61

F. Lastname, et al./ Title of the Paper

150Hz

SP leg 1

450Hz

Connection
plate

Ring

Im [V]Im [V]

SG tubeDefectAmplitudeSP
SP + DefectSP
SP + Defect

Re [V]SP leg 2

Re [V]MF

SP
SP + DefectWindowSP
SP + Defect

WMF (DWMF)
S/N ratio

Im [V]S

N
SP
SP + DefectPosition

Re [V]

Fig. 3. Standard MF algorithm in Lissajous representation using 2 ECT frequencies (left image).
Principle of WMF or DWMF algorithms (right image)defect area with a larger S/N ratio. The parameters of the WMF algorithms are previously determined
and then fixed during scanning window. Therefore, in order to determine the optimum WMF
parameters, it is required to check the results of calculations for various windows size and set one thatis optimum for the particular ECT sensor used to acquire the data. Meanwhile, the dynamic-window
multi-frequency (DWMF) changes its parameters dynamically at each point of the window scan, andsearches the parameters S/N when this ratio is maximized. Consequently, by using DWMF it ispossible to simplify the determination operations of the optimum multi-frequency parameters innormal WMF. These are accomplished by finding the most optimum parameters along the scan anduse their mean value as a starting point for the WMF algorithm.
The dynamical “window” algorithm (see Eq. 2), described also in [8], uses a fixed-size andsmaller subset data of length “w” from signal of length “n” at two frequencies S1(1,n) and S2(1,n).
These signals are combined using a standard MF algorithm for each window “w” resulting in thesignal Si. The DWMF signal Sw (i) at each “i” point of the signal is defined by the maximum ratio
Si/Ni where Ni is the signal of noise.
S i  S1 (i, i  w)    R( )  S 2 (i, i  w), N i  N1 (i, i  w)    R ( )  N 2 (i, i  w),
S w (i )  Max( S i / N i ) when   1 / 10..10,   0..2 , i  1, n  w(2)

4. Validation of WMF with measurements using bobbin-coil system
Because of the sodium high electrical conductivity, after each sodium drain different sodium
layers or sodium filling the defects will add an additional noise ECT signal. In the WMF algorithm
noise is considered the signal from both sodium and tubes SP. The WMF algorithm maximizes thedefect signal against this noise, and in the present paper it is investigated that when using
experimental measurements an optimized solution can be found and validated with a signal/noise ratio
larger than 2.
Fig. 4 and 5 show the result of applying the WMF and DWMF to directly experimental
measurements (150Hz-450Hz) for OD20% groove and OD30% partial described earlier, defects thatare always hidden under SP as in Fig. 1 (right). Each of these figures shows the results of “Nosodium” (that was the configuration of SG tubes before sodium was drained) and also the “1st drain”,(that were configurations of tubes after sodium was drained 1st time). For example, in the “Nosodium” results in Fig. 4, the upper image represents the real ECT measurement data (real component
at 150 Hz), the middle picture shows the WMF analysis, while the lower picture represents the
DWMF results, respectively. The WMF results in Fig. 4,5 were obtained by using the most optimal
MF parameters in equation 2, using a brute force attack where the phase ranged between 0 to 360
degrees with 2 degree step while the amplification factor ranged between 1/10 to 10 with a 0.2 step.
When focusing on the influence of the sodium drain on the MF algorithms, it can be seen thatboth WMF and DWMF are relatively stable, without large reduction in S/N ratio, this being illustrated

62

F. Lastname, et al./ Title of the Paper

with results after each three sodium drains. It was found out that the largest S/N ratio peaks in the area
where the defect is present. Other S/N peak`s ratio larger than 2 were in a zone that corresponds to thestart position of the support plate. This is because a defect influence actually extends up to 80 mm to
the start of SP, but despite this 2nd peak signal, it is considered that there is no significant impact on
the detection defect.
No Sodium
Amplitude [V]

0
‐0.5
‐1
20

S/N ratio

WMF

15
10
5

DWMF

S/N ratio

S/N ratio

0
20
15
10
5
0
0

50

100

150
200
250
position [mm]300

1st drain

1

SP
SP + Defect

0.5

S/N ratio

Amplitude [V]1SP
SP + Defect

0.5
0
‐0.5
‐1
25
20
15
10
5
0
25
20
15
10
5
0

350

WMF

DWMF

0

50

100

150
200
250
position [mm]

300

350

Fig. 4. Result of applying the WMF and DWMF for full circumferential groove OD20%No Sodium
Amplitude [V]

0.5
0
‐0.5
‐1
10
8
6
4
2
0
10
8
6
4
2
0

S/N ratio

WMF

DWMF

0

50

100

150
200
250
position [mm]300

1st drain

1

SP
SP + Defect

S/N ratio

S/N ratio

S/N ratio

Amplitude [V]1SP
SP + Defect

0.5
0
‐0.5
‐1
10
8
6
4
2
0
10
8
6
4
2
0

350

WMF

DWMF

0

50

100

150
200
250
position [mm]

300

350

Fig. 5. Result of applying the WMF and DWMF for partial OD30%
Table 1 Peak S/N ratio of WMF and DWMF for partial OD30%
Peak S/N ratio
Sodium drain

No‐SodiumWMF with multifrequency parameters
ϕ = 184
α = 3.4(2nd‐drain)

ϕ = 192
α = 3.2(3rd‐drain)

ϕ = 193
α = 3.1(Average)

DWMF(No‐sodium)ϕ = 202
α = 2.8(1st‐drain)

5.73

4.42

4.49

4.09

ϕ = 178
α = 3.2

7.70

3.45

1st‐drain

3.71

8.66

4.46

7.81

7.39

4.30

2nd‐drain

5.56

6.06

7.02

5.85

5.70

5.42

3rd‐drain

6.39

5.83

6.64

7.69

7.10

4.36

Table 1 shows S/N peak values of WMF with optimum-find multi-frequency parameters and
DWMF with dynamical parameters. The WMF results are shown with five sets of parameters. The
first four sets correspond to the “no sodium” and after three sodium drains, while the last one is themedium average of all of them. In addition, when applying WMF, with other than the most-optimum
parameter (for example using data from “1st drain” but with parameters of WMF determined at “nosodium” case) the S/N peak is reduced to about 1/5th of maximum value in the worst case, but stillhigh above 2. DWMF algorithms are faster in finding the optimal parameters than WMF, therefore
being more advantageous and easy to detect the defect location.

63

F. Lastname, et al./ Title of the Paper

5.

WMF using 3D FEM simulated data for multi-coil system

DWMF algorithms (window-size equal with 7 mm) were applied to three-dimensional FEM
simulations described previously [7-8] to the multi-coils unit of the RF-ECT device. Fig. 6 shows theC-scan of the outer tube surface near tube support at 60 Hz in the absence or presence of sodium.

Fig. 6. FEM simulations of C-scan of ECT signal at 60Hz using multi-coil unit when defect is empty of
sodium (left image) or filled 100% with sodium (right image)Fig. 7. S/N ratio for various WMF algorithms using multi-coil unit and 100% sodium filling of OD30%

64

F. Lastname, et al./ Title of the Paper
Fig. 8. Application of WMF algorithm (60Hz-150Hz) for multi-coil unit using 3D FEM simulations

While at a single ECT frequency, both defect and support signal are visible on the C-scan
image, in the MF algorithm it is required to suppress any signal but defect signal, independently of
sodium accumulation percentage inside the defect. 3D FEM numerical simulations were conducted atvarious frequencies (60Hz to 450 Hz) to find the optimum DWMF algorithm that is the least sensitive
to the presence of sodium. Results, presented in Fig. 7, show that an algorithm can be found using thefrequency set 60Hz-150Hz, in which the signal/noise ratio changes maximum 30% (0.7 value) whensodium fills 100% the defect. Application of the DWMF for the optimized frequency set (see Fig. 8)
therefore validates the sensitivity of defect detection, even for partial outer defect OD30%tw, with alarge signal/noise ratio up to 15, when defects are filled 100% with sodium.

6.

Conclusions

Windows multi-frequency and dynamic-windows MF algorithms were applied directly toexperimental ECT signals from bobbin coils for FBR SG tubes that were drained of sodium, withouter defects localized near tube support plates. The results confirmed that it can be foundmulti-frequency algorithms at (150Hz-450Hz) that provide a high signal/noise ratio up to 8 (for
WMF) or 5 (for DWMF). These algorithms do not depend by the sodium accumulated near SP or
inside defects volumes. The S/N peak position indicates the location of the defect. While WMF showsslightly better S/N ratio, DWMF is a more convenient and faster algorithm that was proved to beequal stable and insensitive to sodium noise signal.
By using three dimensional FEM simulations it was shown that DWMF algorithm can also be
applied to multi-coils detection units. When choosing the optimized set of frequencies (60Hz-150Hz)in the MF algorithm, large S/N ratio (S/N >15) could be found for detection of both groove OD20%tw
and partial OD30%tw when located under tube SP, even in the presence of sodium that is filling thedefect, confirming DWMF stability.

References[1] D. L. Atherton, S. Sullivan and M. Daly, A remote field eddy current tool for inspecting nuclear reactor
pressure tubes, Br. J. Nondestructive Testing, 30, pp. 22-28, (1988).
[2] H. Fukutomi, T. Takagi and M. Nishikawa, Remote field eddy current technique applied to non-magnetic
steam generator tubes, NDT&E International, 34,pp. 17-23, (2001).
[3] S. Kumano, N. Kawase, K. Kawata and A. Kurokawa, Signal processing of rotating pancake eddy current
signal for steam generator tubes, Proceedings of the 13th International Conference on NDE in the Nuclear
and Pressure Vessel Industries, Kyoto, Japan, 22-25 May, pp. 413-420, (1995).
[4] V. Ganugapati, K. Arunchalam, P. Ramuhalli, L.Udpa and S.Udpa, A polynomial mixing algorithm forsuppressing TSP signals in bobbin coil eddy current data, Electromagnetic Nondestructive Evaluation (VII),
Studies in Applied Electromagnetics and Mechanics 26, (2006), pp. 213-219.
[5] Zhenmao Chen, Naoki Chigusa, Hiromu Isaka and Kenzo Miya, Data processing of corrosion noise
polluted ECT signals for heat exchanger tubes of Cu-Ni alloy, Electromagnetic Nondestructive Evaluation(VIII), Studies in Applied Electromagnetics and Mechanics, 24, (2004), pp 128-135.
[6] O. Mihalache, T. Yamaguchi, M. Ueda , “Computational Challenges in Numerical Simulations of ISI of
Ferritic Steam Generator Tubes in Fast Breeder Reactors using Eddy Currents and Multi-frequency
Algorithms”, E-Journal of Advanced Maintenance, Vol. 3, No. 2, pp. 54-77, August, (2011).
[7] O. Mihalache, T. Yamaguchi, M. Ueda, “Validations of Multifrequency ECT Algorithms for Helical SG
Tubes of FBR”, Electromagnetic Nondestructive Evaluation (XVII), Vol. 39, pp. 109-119, (2014).
[8] O. Mihalache, T. Yamaguchi, M. Ueda, “Multifrequency ECT for Sodium Drained SG Tubes of FBR using
3D Finite Element Simulations”, 17thISEM , Kobe, Sept , (2015).
[9] T. Yamaguchi, O. Mihalache, M. Ueda, “Experimental Measurements and Simulations of ECT Signal for
Ferromagnetic SG Tubes Covered by a Sodium Layer”, Electromagnetic Nondestructive Evaluation,(XVII), Vol 39, pp. 144-154, (2014).

65