GMR-based eddy current probe for weld seam

Nondestructive Testing and Evaluation

ISSN: 1058-9759 (Print) 1477-2671 (Online) Journal homepage: http://www.tandfonline.com/loi/gnte20

GMR-based eddy current probe for weld seam inspection and its non-scanning detection study Peng Gao, Chao Wang, Yang Li, Libin Wang, Zheng Cong & Ya Zhi To cite this article: Peng Gao, Chao Wang, Yang Li, Libin Wang, Zheng Cong & Ya Zhi (2016): GMR-based eddy current probe for weld seam inspection and its non-scanning detection study, Nondestructive Testing and Evaluation, DOI: 10.1080/10589759.2016.1149583 To link to this article: http://dx.doi.org/10.1080/10589759.2016.1149583

Published online: 18 Feb 2016.

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Date: 05 April 2016, At: 02:10

Nondestructive Testing and Evaluation, 2016 http://dx.doi.org/10.1080/10589759.2016.1149583

GMR-based eddy current probe for weld seam inspection and its non-scanning detection study Peng Gaoa,b, Chao Wanga, Yang Lia,c, Libin Wanga, Zheng Conga and Ya Zhia

Downloaded by [Texas A & M International University] at 02:10 05 April 2016

a

School of Electrical Engineering and Automation, Tianjin University, Tianjin, P.R. China; bTianjin Special Equipment Inspection Institute, Tianjin, P.R. China; cHajim School of Engineering and Applied Sciences, University of Rochester, Rochester, NY, USA

ABSTRACT

Eddy current testing is one of the most important non-destructive testing methods for welding defects detection. This paper presents the use of a probe consisting of 4 giant magneto-resistive (GMR) sensors to detect weld defects. Information from four measuring points above and on both sides of the weld seam is collected at the same time. By setting the GMR sensors’ sensing axes perpendicular to the direction of the excitation magnetic field, the information collected mainly reflects the change in the eddy current which is caused by defects. Digital demodulation technology is applied to extract the real part and imaginary part of the GMR sensors’ output signals. The variables containing directional information of the magnetic field are introduced. Based on the data from the four GMR (4-GMR) sensors’ output signals, four values, Ran, Mean, Var and k are selected as the feature quantities for defect recognition. Experiments are carried out on weld seams with and without defects, and the detection outputs are given in this paper. The 4-GMR probe is also employed to investigate non-scanning weld defect detection and the four feature quantities (Ran, Mean, Var and k) are studied to evaluate weld quality. The non-scanning weld defect detection is presented. A support vector machine is used to classify and discriminate welds with and without defects. Experiments carried out show that through the method in this paper, the recognition rate is 92% for welds without defects and 90% for welds with defects, with an overall recognition rate of 90.9%, indicating that this method could effectively detect weld defects.

ARTICLE HISTORY

Received 12 May 2015 Accepted 22 January 2016 KEYWORDS

Defect detection; weld defect; giant magnetoresistive (GMR) sensor; eddy current testing; nonscanning testing

1. Introduction Defects existing in weld seams can seriously influence the reliability of the welding structure. [1] With the advantages such as the fast speed in detection, no use of coupling agent, no radiation or environment pollution, eddy current testing (ECT) has aroused wide interest in the weld detection area.[2–7]

CONTACT Chao Wang © 2016 Taylor & Francis

[email protected]


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Conventional ECT usually estimates damage on the specimen by scanning the surface. In one-dimensional (1D) condition, the complex data from a line scan, in the form of a Lissajous plot, is used to analyse the defect. In two-dimensional (2D) condition, through plane scanning, magnetic field distribution of specimen surface is always employed to analyse the defect. Qualitative and quantitative estimation of the defect can be obtained. [8] Yusa et al. carried out 2D scanning of weld defects, and analysed the impact of different types of probes by the weld surface noise. In the experiment, a welded Inconel plate with thickness of 30 mm was tested. Although the surface of the weld was very rough, the depth of artificial slits can be estimated with the help of the proper probe and simple de-noising process.[9] It is convenient to apply magnetic field sensors, such as giant magneto-resistive (GMR) sensors, to measure magnetic in ECT. Guang Yang et al. analysed magnetic field distribution through 2D scanning. They used image fusion technology to improve the defect detection capability around aircraft rivets.[10] However, it always has the disadvantage of low efficiency, when magnetic field distribution is obtained by plane scanning. Especially in some cases where scanning cannot be carried out, the method is difficult to implement. So the non-scanning mode has important significance and practical value in ECT. Guiyun Tian et al. presented that multiple sensor probe could be applied to evaluate cracks below the surface. It provided an effective approach on locating and sizing of the cracks without using scanning.[11] O. Postolache et al. designed a uniform eddy current probe with multiple GMR sensors that can detect magnetic field at several points, so the detection speed has been improved.[12] A. McNab and J. Thomson designed a multi-element eddy current array for the local testing of ferritic specimens including welds. The eddy current instrument provided a useful method for rapid local inspection of ferritic welds. Improvements over single coil operation were obtained in scanning speed and in the reliability of flaw detection. This was because the electronically scanned array of coils permitted a greater area of the material to be tested and provided a 2D image of the flaw position,[13] but scanning was still needed in the detection process. Owing to the advantage of small size, C. H. Smith et al. designed a multi-element eddy current array using GMR sensors. The array was designed into a GMR chip whose space distances between GMR sensors were 5 μm, which greatly improved the spatial resolution. C.H. Smith’s further studies showed that the image of magnetic field distribution can be gained through the eddy current array.[14–16] In the designs of these eddy current arrays, researchers always reduced dependence on point-by-point scanning detection method by increasing the number of sensors or sensor density.[14] However, for larger detecting area, a larger number of sensors are required, resulting in making the detection system very complex. In this paper, in order to detect the defects in welds in key parts of the equipment, a non-scanning weld quality monitoring method using four GMR sensors is proposed. The combination of the rectangular coil and four GMR (4-GMR) sensors is realised. Information of the magnetic field from four positions around the weld seam is extracted, and signal strength and waveform are used to determine weld quality.


3

(a) Excitation coil GMR sensor Sensing axis 25 mm 2 mm

60 mm

30 mm


(b)

GMR sensors S2 S3 S4

Excitation Coil

S1

Amplifier

Figure 1. 4-GMR probe (a) Schematic diagram indicating probe assembly and dimensions; (b) Photo of the probe.

2. ECT system The ECT system consists of the 4-GMR probe and the data acquisition board. The 4-GMR probe is shown in Figure 1. The excitation coil is a rectangular coil. Four identical GMR sensors are placed on the outside bottom of the rectangular coil and all their sensing axes are perpendicular to the primary field of the excitation coil, which prevents the GMR sensors from the impact of the primary field. In order to assure that the GMR sensors work in their linear range, a permanent magnet is used as bias.[17,18] The schematic diagram of the testing system is shown in Figure 2. The data acquisition board is based on the Xilinx XC3S400 field programmable gate array (FPGA), consisting of the FPGA minimum system, the excitation signal circuitry, the measuring circuitry and the communication circuitry. The schematic graph of excitation signal channel is shown in Figure 3. A set of digital sinusoidal sequence of 14 bits is generated by the DDS module in the FPGA, and transformed to an analogue signal by AD9754. The analogue signal is then passed to a filter circuit and then a power amplifier to generate excitation signal with a high current. A reference voltage is provided by AD7302 to AD9754. The schematic graph of detection channel is shown in Figure 4. The induction voltage signal from the conditioning boards are programmable-amplified by PGA, anti-aliasing filtered, and then converted to digital signal of 14 bits by AD9240. The data are then input to FPGA and demodulated. Through universal serial bus (USB), data are transported into personal computer. The GMR sensors are in different locations on the output characteristic curve due to their distance from the permanent magnets, and during the demodulation the mean value can be automatically eliminated thus the results of the demodulation of the real part and imaginary part are not influenced.

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Data acquisition board FPGA minimum system


Sinusoidal Excitation

Excitation signal circuitry

Measuring circuitry

USB communication circuitry

Response Signal

Amplifier

Figure 2. Schematic graph of eddy current testing system and weld inspection.

AD7302

Reference voltage

DA PORT

DDS

AD9754

Differential Amplification

Filtering

Amplification

Vout

Figure 3. Schematic graph of excitation signal channel.

FPGA

Control Module

AD AD PORT PORT Demo

AD9240

PGA

Amplification

Input signal

Figure 4. Schematic graph of detection channel.

Digital demodulation is realised via FPGA. Orthogonal sequence demodulation is adopted in the system to extract the amplitude and the phase of the signal. The frequency of the input signal is f, while the sampling frequency is fs, and fs = Ns × f (Ns ≥ 2). The number of the sampling period is q, so the total number of the sampled data points are M = Ns × q.[19,20]


� � ⎧ 2𝜋k ⎪ VS (K) = U sin N + 𝜃 � � ⎪ 2𝜋k k = 0, 1, … , N − 1 ⎨ Vrs (K) = sin N � � ⎪ 2𝜋k ⎪ Vrc (K) = cos N ⎩

5

(1)


where Vs(k) is the input signal, Vrs(k) is the sine reference sequence and Vrc(k) is the cosine reference sequence. Both Vrs(k) and Vrc(k) are generated by the DDS IP core.

Rxrs =

M−1 M−1 U U ∑ 1 ∑ Vs (k) ⋅ Vrs (k) = cos 𝜃 − cos M k=0 2 2M k=0

Rxrc =

M−1 M−1 U U ∑ 1 ∑ Vs (k) ⋅ Vrc (k) = sin 𝜃 + sin M k=0 2 2M k=0

(

(

4𝜋k +𝜃 N

4𝜋k +𝜃 N

) =

U cos 𝜃 2

(2)

=

U sin 𝜃 2

(3)

)

where Rxrs is the cross correlation between Vs(k) and Vrs(k), Rxrc is the cross correlation between Vs(k) and Vrc(k). √ 2 2 (4) + Rxrc U = 2 Rxrs

(

R 𝜃 = arctan xrc Rxrs

) (5)

where θ is the phase of the signal when firstly sampled. So the real part and the imaginary part are as follows,

real = U cos 𝜃

(6)

imaginary = Usin𝜃

(7)

3. Numerical simulation 3.1. Simulation model In this study, the finite element model software COMSOL Multiphysics is used. The three-dimensional (3D) models are used to analyse rectangular coil under time-varying harmonic conditions. The governing equations for time-varying harmonic fields are:

( ) ∇ × 𝜇0−1 𝜇r−1 B − 𝜎v × B = J e

(8)

B =∇ × A

(9)

Je =

NIcoil e As coil

(10)


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Figure 5. Geometry of the simulation model (a) 3D model; (b) Top view; (c) Side view.

where A is the magnetic vector potential, v is the electric scalar potential, Icoil is the current in coil, As is the coil’s cross-sectional area, N is the turns of the coil. Boundary conditions are as follows,

n×A=0

(11)

The geometry of the simulation model is shown in Figure 5. The excitation coil has 450 turns with the excitation current of 1 A; the conductivity of the tested specimen is 2.61 × 107 S/m; the relative permeability is 1. The distance between the lower surfaces of the coil and the upper surface of the specimen is 2.75 mm. In the numerical simulation, the magnetic flux density in y direction (By) which is measured in the experiment is calculated to analyse the 4-GMR probe. 3.2. Magnetic flux density distribution Figure 6 shows the y-component of magnetic field distribution below the bottom of the rectangular coil, which is substantially uniform. Figure 7 shows the lift-off effect on the excitation magnetic field on the straight line y = 0 in Figure 6. In Figure 7(a) and (b), the dotted lines mark the range of GMR sensors’ locations. In the GMR sensors’ range, the excitation magnetic field changes smoothly, while outside the range the excitation magnetic field changes sharply. Figure 7(c) shows the mean and variance of the excitation field amplitude


(a)

15 -0.01000

10

-0.009000

Y Axis(mm)

5

-0.008000 -0.007000

0

-0.006000 -0.005000

-5

-0.004000

-10 -15 -30

-0.003000 -20

-10

0

10

20

30

-0.002000

X Axis(mm)

(b) 15 -0.01000

10

-0.009000

5 Y Axis(mm)


7

-0.008000 -0.007000

0

-0.006000

-5

-0.005000 -0.004000

-10

-0.003000 -15 -30

-20

-10

0

10

20

30

-0.002000

X Axis(mm)

Figure 6. Magnetic flux density By (a) Real part; (b) Imaginary part.

with the change of the lift-off. With the increase of the lift-off, the mean amplitude of the excitation decreases, indicating that the magnetic field gets weaker as the lift-off increases; the variance of the amplitude reduces which indicates that with the increase of the lift-off, the rectangular coil magnetic field is more uniform. Figure 8 shows the effect of different frequencies on the excitation field. In Figure 8(a) and (b), the dotted lines mark the range of GMR sensors’ locations. In the GMR sensors’ range, the excitation magnetic field changes smoothly, while outside the range the excitation magnetic field changes rapidly. Figure 8(c) shows the mean and variance of the excitation field amplitude at different excitation frequencies. With the increase of the frequency, the mean amplitude of the excitation increases indicating that the magnetic field gets stronger as the frequency increases; the variance of the amplitude increases which indicates that the increase of the frequency results in deterioration of uniformity for magnetic field under the rectangular coil. 3.3. Sensitivities of the positions Defects can be (12) magnetic field can reflect the change of the conductivity of conductor. Equation 12 is used to analyse the sensitivities of the four positions of the four sensors under the rectangular coil.[21]

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Real part of magnetic field (T)

(a)

0.75 mm 1.25 mm 1.75 mm 2.00 mm 2.25 mm 2.50 mm 2.75 mm 3.00 mm 3.25 mm 3.75 mm

-0.006 -0.007 -0.008 -0.009 -0.010 -0.011 -20

-10

0

10

20

30

20

30

Position (mm)

(b)

0.75 mm 1.25 mm 1.75 mm 2.00 mm 2.25 mm 2.50 mm 2.75 mm 3.00 mm 3.25 mm 3.75 mm

Imaginary part of magnetic field (T)

-0.0005 -0.0006 -0.0007 -0.0008 -0.0009 -0.0010 -0.0011 -30

-20

-10

0

10

Position (mm)

(c)

0.0110

3.30E-009

0.0108 0.0106

3.10E-009

0.0104

3.00E-009

0.0102

2.90E-009

0.0100

2.80E-009

0.0098

2.70E-009

0.0096

2.60E-009

0.0094

2

Mean of applitude(T)

3.20E-009

Mean Var

Var of applitude(T )


-30

2.50E-009

1

2

3

4

Lift-off (mm)

Figure 7. Lift-off effect on the excitation magnetic field By (a) Real part; (b) Imaginary part; (c) Mean and variance of the excitation field amplitude.

Sy =

ΔBy Δ𝜎

(12)

where Sy is the sensitivity at the measurement point, ΔBy is the change of magnetic flux density in y direction. Δσi = σi − σ0, Δσ is the change of conductivity, σ0 is the initial conductivity, σi is the conductivity changed.


Real part of magnetic field (T)

(a)

-0.0060

9

500 Hz 1000 Hz 2000 Hz 3000 Hz 4000 Hz 5000 Hz

-0.0065 -0.0070 -0.0075 -0.0080 -0.0085 -0.0090 -0.0095 -0.0100 -0.0105 -0.0110 -20

-10

0

10

20

30

Position (mm)

(b)

500 Hz 1000 Hz 2000 Hz 3000 Hz 4000 Hz 5000 Hz

Imaginary part of magneitc field (T)

-0.0003 -0.0004 -0.0005 -0.0006 -0.0007 -0.0008 -0.0009 -0.0010 -0.0011 -30

-20

-10

0

10

20

30

Position (mm)

(c)

0.0106 3.20E-009

0.0104

3.00E-009

0.0100 2.90E-009

0.0098 Mean

2.80E-009

2

Mean of applitude(T)

3.10E-009

0.0102

Var of applitude(T )


-30

Var

0.0096

2.70E-009

0.0094

0

1000

2000

3000

4000

5000

Frequency (Hz)

Figure 8. Excitation magnetic field By at different frequencies (a) Real part; (b) Imaginary part; (c) Mean and variance of the excitation field amplitude.

Figure 9 shows the sensitivities of the four positions on the outside bottom of the rectangular coil, where the lift-off is 2.75 mm and the frequency is 1 kHz. It can be seen that the sensitivities of the four positions are not completely the same. The sensitivities of Position 2 (P2) and Position 3 (P3) are slightly larger than those of Position 1 (P1) and Position 4 (P4). The sensitivities of P1 and P4 are 1.21% lower than those of P2 and P3.

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Sensitivity(Tm/S)

1.10E-011

1.00E-011


9.00E-012

1

2

3

4

No. of position

Figure 9. Sensitivities of the four positions.

Figure 10. Specimens under test (a) non-defective weld seam; (b) defective weld seam.

4. Experiment set up and scanning mode weld inspection A quantity C is introduced as a parameter containing directional information of the magnetic field, which could simultaneously reflect the magnitude and direction of the amplitude. [22]

√ C = sign(Re) ×

Re2 + Im2

(13)

where Re and Im are the real and imaginary part of the GMR sensor’s output voltage signal respectively. Sign(Re) is the sign function and has different values with different Re (Re > 0, the function value is +1; Re = 0, the function value is 0; Re