Post Signal Processing of Ultrasonic Phased Array Inspection Data for Non-destructive Testing

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Procedia Engineering 43 ( 2012 ) 419 – 424

International Symposium on Safety Science and Engineering in China, 2012

(ISSSE-2012)

Post Signal Processing of Ultrasonic Phased Array Inspection Data for

Non-destructive Testing

Kun Xiao

a

, Qiang Wang

a,

*, Dong Hu

a

a_{Department of Quality and Safety Engineering, China Jiliang University, Hangzhou 310018. P. R. China}

Abstract

In ultrasonic phased array non-destructive testing, the amplitude of the grain noise can be smaller than that of the echoes, and the grain noise can totally mask echoes characterizing faults. Several algorithms such as band pass filter, low pass filter, wiener deconvolution and wavelet have been employed to reduce the grain noise. In this paper, an actual S-scan detection image was obtained from a real time UT acquisition system, and a comparison of the suppressing grain noise performances of low pass filter and wavelet de-noising algorithm was displayed. The results show that the wavelet de-noising algorithm is better than other algorithms listed in this paper, and it can suppress the amplitude of grain noise from 100% to 20%. This approach is shown to offer significant performance advantages for NDE.

Keywords: NDT, Ultrasonic phase array, Wavelet, De-noising

1.Introduction

Ultrasonic phased array system for non-destructive testing (NDT) has been used increasingly in recent years. Compared with conventional single element transducers, the ultrasonic phased array can perform multiple inspections without the need of reconfiguration, which obtains better sensitivity and coverage[1]. Plane beams, steered angled beams and focused beams are often used to increase the range and inspection accuracy. The recent development of two-dimensional arrays has also led to an increase in interest in three-dimensional volumetric imaging of components [2]. Flexible arrays [3-5] and high temperature arrays [6] are being developed to test components with complex geometries, and applied in harsh environments, especially in the aerospace and nuclear industries. Ultrasound phased array NDT technologies played an important role in the safe operation of many industrial fields.

Grain noise usually appears in NDT ultrasonic phased array testing, which caused by unresolvable reflectors in inspected medium. This noise can be attenuated by certain de-noising algorithms, such as band pass filter, wiener deconvolution, low pass filter, matching pursuit and wavelet de-noising algorithm and so on [7-8]. Thus, several de-noising algorithms have been used to process ultrasonic phased array signals [9].

In this paper, the ultrasonic S-scan images obtained from UT acquisition system (provide by OLYMPUS company), than the A-scan image data which was exported by the S-scan image. Low pass filter and wavelet de-noising algorithm were

Open access under CC BY-NC-ND license.

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chose to deal with the grain noise. In addition, the type of the low pass filter was Butterworth and the mother wavelet of the wavelet de-noising algorithm was sym8.

2.The image acquirement of ultrasonic phased array

If the array geometry is known, a focused image can be generated from the echo data by delay-and-sum beam forming. The imaging model of ultrasonic phased array is showed in Fig 1. The amplitude of focus point

f x z

( , )

can be expressed in equation (1) [10].

( , )

(

m n

,

)

m n m n m n

r

f x z

e

X X

r r

c

¦¦

(1) where

x

and

z

are coordinate of focal point,

m

and

n

is the index of the transmitting and receiving elements,

( ,

_m

,

_n

)

e t X X

is the echo data,

t

is the time,

X

_m

'

m u

and

X

_n

'

n u

are the distance between the origin of probe and the transmitting and receiving elements,

'

u

is the constant element pitch,

c

is the speed,

r

_mand

r

_nis are the distances between the focal point

( , )

x z

and the positions of the transmitting and receiving elements

(

X Z

m

,

m

)

and

(

X Z

n

,

n

)

.

2 2

(

)

(

)

m m m

r

x X

z Z

, (2) 2 2

(

)

(

)

n n n

r

x X

z Z

, (3) where Xm X u( )m andZm Z u( )m is the elements positions in a ultrasonic phased array.

Fig 1. The imaging acquirement of ultrasonic phased array

The focused image

f x z

( , )

has a large dynamic range-weak scattering from the grain structure, moderate scattering from the defects, and a dominant back-face reflection. It is therefore necessary to compress the range of amplitudes in the image. We consider the intensity values on a logarithmic scale (referenced to the brightest target, a target in a calibration specimen, or the back-face reflection) and we clip these values at some lower threshold [10], i.e.,

min min min

( , ), ( , )

( , )

, ( , )

i x z

i

i x z

i

i x z

i

c

t

®

_c

¯

(4) where

(3)

10

( , ) 20log ( ( , ) /

ref

)

i x z

c

f x z

f

, (5)

ref

f

is the reference amplitude, and we choose the threshold

i

_min

20dB

.

3.Post signal processing of ultrasonic phased array

3.1.Low pass filter

A low-pass filter can pass low-frequency signals but attenuates signals with frequencies higher than the cutoff frequency. A typical Butterworth filter can be expressed as

2 2 2 0

1 ( , )

1 [

/

]

n

H u v

u

v

D

, (6)

where

H u v

( , )

is transfer function,

D

₀is cutoff frequency,

n

is order.

Phased array ultrasonic scan images contain many high frequency components. Low pass filter can effectively remove these high frequency components.

3.2.Wavelet de-noising algorithm

The wavelet transformW a b_s( , )of a signal ( )x t is given by [11]

( , ) ( ) ( ) s t b W a b x t dt a f f <

³

, (7) where ( )< is the mother wavelet anda,bare the dilatation and translation coefficients respectively.

Wavelet de-noising procedures can be summarized as (i) wavelet transform of the noisy register; (ii) pruning and/or thresholding of the coefficients in the trans-formed domain; (iii) reconstruction of the de-noised signal by inverse transform.

According to recently researches, the mother wavelet in the Symlet family has good features to detect the ultrasonic echo waves on both time and frequency domains, so the mother wavelet of Sym8 was selected in this paper [12].

4.Experimental result

Ultrasonic S-scan image was obtained by UT acquisition system (named OMNISCAN MX, and provide by OLYMPUS company), than the A-scan image data which was considered as original image exported by TOMOVIEW through the S-scan image. The used transducer is composed of 64 linear piezoelectric elements. Besides, the S-S-scan angle is

30 q q

70

. The thickness of the workpiece is 100mm, and there was a defect in the depth of 25mm.

The low pass filter algorithm is employed to process the ultrasonic S-scan image, and the result is shown in Fig. 2. Comparing the Fig. 2(a~d), it’s clear that the low pass filter can’t suppress the grain noise well, and the amplitude of noise is still high even used 4th-order Butterworth filter.

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(a) (b) Depth(mm) A ngl e( °) 10 20 30 40 50 60 70 80 90 100 110 120 35 40 45 50 55 60 65 70 (c) Depth(mm) An g le (° ) 10 20 30 40 50 60 70 80 90 100 110 120 35 40 45 50 55 60 65 70 (d) Depth(mm) A ngl e( °) 10 20 30 40 50 60 70 80 90 100 110 120 35 40 45 50 55 60 65 70

Fig. 2. The effect of low pass filter algorithm for (a) the original image and (b) first-order Butterworth filter with cutoff frequency 50 and (c) second-order Butterworth filter with cutoff frequency 50 and (d) 4th-order Butterworth filter with cutoff frequency 50.

In Fig. 3, it presents the analysis result of ultrasonic image data after wavelet de-noising. The mother wavelet in this paper chose was sym8, and the first-order wavelet, the second-order wavelet and 4th -order wavelet was used to process the image. From the Fig. 3, we can find that the wavelet de-noising algorithm could attenuate grain noise effectively. Particularly, the 4th-order wavelet de-noising algorithm displays the satisfied performance in suppressing grain noise. The defect in the depth of 25mm, and the backwall echo signal in the depth of 100mm can be clearly seen.

(a) (b) Depth(mm) A ngl e( °) 10 20 30 40 50 60 70 80 90 100 110 120 35 40 45 50 55 60 65 70

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(c) Depth(mm) An g le (° ) 10 20 30 40 50 60 70 80 90 100 110 120 35 40 45 50 55 60 65 70 (d) Depth(mm) An g le (° ) 10 20 30 40 50 60 70 80 90 100 110 120 35 40 45 50 55 60 65 70

Fig. 3. The effect of wavelet de-noising algorithm for (a) the original image and (b) first-order wavelet de-noising algorithm with mother wavelet sym8 and (c) second-order wavelet de-noising algorithm with mother wavelet sym8 and (d) 4th-order wavelet de-noising algorithm with mother wavelet sym8.

To conduct a quantitative analysis, the data of the ultrasonic S-scan image in angle 45ewas extracted. Seen from Fig. 4, the image data of three conditions was presented. In addition, the signal amplitude is expressed by percentage of the total image height in this paper, so the signal amplitude changes between 0 % to 100%. We can find that the low pass filter gives higher signal amplitude than wavelet de-noising algorithm, and the difference is 30%. However, it can’t effectively suppress grain noise in the depth of 30mm. The noise amplitude in the depth of 30mm still as high as 45%, and the noise amplitude in the depth 55-68mm is still exist.

The wavelet de-noising algorithm displays the greater performance than low pass filter. Almost all the depth of noise has been attenuated effectively, and the noise signal curve is very smooth. The noise amplitude in the depth of 30mm is lower than 20%, and the noise amplitude in the depth 55-68mm is disappearance, but the backwall echo signal is still retain. However, to some extent, it also reduce the useful signal to 50%.

0 10 20 30 40 50 60 70 80 90 100 110 120 0 20 40 60 80 100 Depth (mm) A m pl it ude ( % ) Original signal Low pass filter

Wavelet de-noising algorithm

Fig. 4. The noise reduction effects of low pass filter and wavelet de-noising algorithm 5.Conclusion

The grain noise of ultrasonic phased array systems with 64 linear piezoelectric elements for NDT can be attenuated effectively through special algorithms. The low pass filter gives higher signal amplitude but it can’t restrain the grain noise well. The grain noise amplitude is still very high when used low pass filter algorithm. The wavelet de-noising algorithm displays a good performance when used in attenuates signals noise. It can attenuate the noise amplitude effectively, smooth the signal curve, and retain the backwall echo signal, though it also can reduce the useful signal.

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Acknowledgements

This work is supported by Key Program of Science and Technology Planning Project of Zhejiang Province, China under Grant 2011C11079.

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