1 DEFECT DETECTION IN PIPELINE USING ACOUSTIC...

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DEFECT DETECTION IN PIPELINE USING ACOUSTIC EMISSION

AHMED KADHIM ZARZOOR

UNIVERSITI TEKNOLOGI MALAYSIA

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DEFECT DETECTION IN PIPELINE USING ACOUSTIC EMISSION

AHMED KADHIM ZARZOOR

A project report submitted in partial fulfilment of the

requirements for the award of the degree of

Master of Engineering (Mechanical)

Faculty of Mechanical Engineering

Universiti Teknologi Malaysia

JANUARY 2015

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“To my beloved mother, father, my sister and my wife”

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ACKNOWLEDGEMENT

All praises are due to Allah the cherished, the Sustainer of the entire universe,

praise be to him, he who taught man with a pen, what he knew not. I asked Allah

Subhanahu wataallah to bestowed Peace and blessings upon His Messenger,

Muhammad S.A.W, and all his family and companions.

I like to express my profound gratitude to my supervisor, Dr. Raja Ishak bin

Raja Hamzah for his patience, advice, time sparing, useful comments, suggestion,

correction, concern and interest in my understanding of what a research undertaking

is, its development and write -up.

I would like to thank the staff of vibration Laboratory, and Faculty of

mechanical Engineering, Universiti Teknologi Malaysia for their understanding.

I will finally like to express my gratitude with a high degree of appreciation

to my friends for their love, care, concern and support both morally and financially,

my gratitude knows no bound. I say a big thank to them. All worlds most precious

resources would not adequately compensate for them love and sacrifices. With

Allah, however, is an adequate and lasting reward.

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ABSTRACT

Monitoring defects in a pipeline are very important in particularly for buried

pipeline. The ability to identify location, type and size of the defects are always

necessary to save time and cost. Thus, this research project embarks on identifying

defect location and estimating the size of the defect by using Acoustic Emission (AE)

technology. Data were acquired from a two inch diameter pipe with 1mm thickness

using low cost piezoelectric sensors. Location of the defect was estimated based on

the difference on the time arrival coming from the two sensors. Results show that

location of the defect can be estimated within certain degree of accuracy. In addition,

different sizes of the defect have also been studied using artificially induced defect as

well as the actual defect. Defects have been introduced both in the axial and radial

direction on the test pipe. AE data from the pencil break has been collected for each

defect size and processed using few AE parameters such as R.M.S., energy,

amplitude and time-frequency domain. All of these data were then normalized to the

reference value and the correlation between defect sizes and normalized AE

parameters were developed. The results show that there are good correlations

between normalized AE parameter and defect sizes particularly when the defect size

was increased in axial direction. In short, it is shown that AE technology is capable

in locating defect in pipeline as well as giving estimation on the size of the defect.

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ABSTRAK

Pemantauan kerosakan ke atas talian paip adalah amat penting terutamanya

untuk talian paip yang tertanam. Kemampuan untuk mengenal pasti lokasi, jenis dan

saiz kerosakan sentiasa perlu untuk menjimatkan masa dan kos. Oleh itu, projek

penyelidikan ini dijalankan bagi mengenalpasti lokasi kerosakan dan menganggarkan

saiz kerosakan itu dengan menggunakan teknologi Pancaran Akustik (AE). Data

diperolehi daripada paip berdiameter dua inci berketebalan 1 mm menggunakan

sensor piezoelektrik kos rendah. Lokasi kerosakan tersebut dianggarkan berdasarkan

perbezaan pada masa ketibaan yang diberikan daripada kedua-dua sensor. Keputusan

menunjukkan bahawa lokasi kerosakan tersebut boleh dianggarkan pada tahap

ketepatan tertentu. Di samping itu, saiz kerosakan yang berbeza itu juga telah dikaji

dengan menggunakan aruhan kerosakan buatan serta kerosakan yang sebenar.

Kerosakan telah dikenakan ke atas kedua-dua arah paksi dan jejari pada paip ujian.

Data AE daripada patahan pensel telah dikumpulkan untuk setiap saiz kerosakan dan

diproses menggunakan beberapa parameter AE seperti R.M.S, tenaga, amplitud dan

domain masa-frekuensi. Semua data ini kemudiannya dinormalkan kepada nilai

rujukan dan korelasi antara saiz kerosakan dan parameter AE ternormal telah

dibangunkan. Hasil kajian menunjukkan bahawa terdapat korelasi yang baik antara

parameter AE ternormal dan saiz kerosakan terutamanya apabila saiz kerosakan itu

telah meningkat dalam arah paksi. Secara ringkasnya, ia menunjukkan bahawa

teknologi AE mampu mengenalpasti lokasi kerosakan ke atas talian paip serta

memberikan anggaran mengenai saiz kerosakan itu

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TABLE OF CONTENTS

CHAPTER TITLE PAGE

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENT iv

ABSTRACT v

ABSTRAK Vi

TABLE OF CONTENTS Vii

LIST OF TABLES X

LIST OF FIGURES Xi

LIST OF APPENDICES xiii

1 INTRODUCTION 1

1.1 Introduction 1

1.2 Problem Statement 3

1.3 Objective of the Study 4

1.4 Scope of the Study 4

2 LITERATURE REVIEW 5

2.1 Introduction 5

2.1.1 Acoustic Emission Technique 5

2.2 AE Data Analysis Approaches 6

2.2.1 Parameter Based Analysis 6

2.2.2 Waveform Based Analysis 9

2.3 AE Wave Mode 10

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2.3.1 Longitudinal and Shear Waves 10

2.3.2 Surface Waves 11

2.3.3 Lamb Waves 12

2.4 Instrumentation for AE Monitoring 13

2.4.1 Data acquisition 14

2.4.2 Signal Processing Tools 16

2.5 Source Location Theory 17

2.6 Challenge in Using Acoustic Emission Technique 18

2.6.1 Source Localization 19

2.6.1.1 Time of Arrival Method 19

2.6.1.2 Source Location Using Modal

Analysis Technique 19

2.6.2 Noise Removal and Source Differentiation 21

2.7 Summary 21

3 METHODOLOGY 23

3.1 Introduction 23

3.2 Acoustic Emission 23

3.3 Research Design 24

3.4 Calculate Sensitivity of Sensor 25

3.5 Experimental Methods for Data Acquisition 26

3.5.1 Transducer 27

3.5.2 Specimen 28

3.6 Localize AE Source 29

3.7 Estimate Defect Size 32

4 RESULT AND DISCUSSION 34

4.1 Introduction 34

4.2 Source Location Results 35

4.3 The Results of Acoustic Emission Parameters 40

4.3.1 Results for Radial Defect 41

4.3.2 The Results of Longitudinal Defect 48

4.4 The Results of Real Defect (0.8 0.8) cm 53

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5 CONCLUSION AND RECOMMENDATIONS 57

5.1 Conclusion 57

5.2 Recommendations 58

REFERENCES 59

Appendices A-C 62-77

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LIST OF TABLES

TABLE NO TITLE PAGE

3.1 Specification of buzzer 28

4.1 Results for time delay for all position's pencil lead

break 38

4.2 The results of measure and actual distance 39

4.3 Acoustic emission parameters for radial defect 45

4.4 Acoustic emission parameters for longitudinal

defect 50

4.5 Compare the results between artificial defect and

real defect 56

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LIST OF FIGURES

FIGURE NO TITLE PAGE

2.1 Acoustic emission technique 6

2.2 Parameters of AE signals 7

2.3 Energy as measure under rectified signal envelope 8

2.4 Continuous and burst AE signals 9

2.5 (a) Longitudinal and (b) Transverse waves

(continued) 11

2.6 Surface waves 12

2.7 Early arriving symmetric (extensional) mode and

later asymmetric (flexural) modes 12

2.8 Symmetric and asymmetric lamb waves 13

2.9 AE measurement chain 15

2.10 Different types of sensors 15

2.11 AE sensor of the piezoelectric element 16

3.1 Research of flowchart 25

3.2 sensitivity of sensor 26

3.3 Experimental setup 27

3.4 Piezoelectric buzzer 28

3.5 Pipe steel 29

3.6 Schematic pipe with two sensors 29

3.7 Pencil lead break 30

3.8 Pencil-lead break for each distance 31

3.9 Time arrival signals 31

3.10 Increase artificial defect in radial direction 32

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3.11 Increase artificial defect in axial direction 33

4.1 Time arrival signals at 10 cm hit from sensor 1 36




4.5 Comparison between actual and measure distance 39

4.6 (a) AE waveform (b) FFT for defect size (0.8 0.8)

cm recorded by sensor 1 41

4.7 (a) AE waveform and (b) FFT for defect size

(0.8 0.8) cm recorded by sensor 2 42





4.10 Normalization of amplitude for radial defect 46

4.11 Normalization of energy for radial defect 46

4.12 Normalization of RMS for radial defect 47





4.15 Normalization of amplitude for longitudinal defect 51

4.16 Normalization of RMS for longitudinal defect 51

4.17 Normalization of energy for longitudinal defect 52

4.18 Estimate the defect size 52

4.18 a) AE waveform (b) FFT for real defect size


4.19 (a) AE waveform (b) FFT for real defect size


4.20 Real Defect (0.8 x 0.8) cm 55

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LIST OF ABBREVIATIONS

AE acoustic emission

SHM Structural Health Monitoring

NDT Non Destructive Testing

PB piezoelectric buzzer

PLB pencil lead break

TOA time of arrival

RMS Root Mean Square

dB decibel (unit of acoustic emission signal magnitude)

FFT Fast Fourier transforms

SNR signal noise ratio

WT wavelet transform

STFT short Fourier transform

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LIST OF APPENDICES

APPENDIX TITLE PAGE

A MATLAB Code (pure tone ) 62

B Experimental Results Time Arrival Signals 63

C Data analysis for defect size 67

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CHAPTER 1

INTRODUCTION

1.1 Introduction

Technology of pipeline has been developed in order to increase the potential and

ability of this type of transportation. Nowadays, pipelines have become a regular

practice to transfer the material from the raw source to the end user. Due to this

economic, transportation, pipelines become a major role in the petroleum industry

because this method is safe, reliable and can promise constant flow of crude oil, natural

gas and petroleum products.

Leak can occur from small holes caused by corrosion up to catastrophic pipeline

failure due to man-made damage or natural causes such as earthquakes. Because of this

matter, the development of pipe leak monitoring has been introduced and research will

keep running to improve the system from time to time. If the surface exposed, the

location of the leak can be determined by visual technique. But if the pipe is coated or

buried, the location of the leak or crack is difficult to be determined by visual technique.

Therefore, there are several non-destructive testing (NDT) techniques which can be

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applied to this application to detect the earliest leaking condition. One of these

techniques called acoustic emission.

Acoustic Emission (AE) is a phenomenon of all materials where stress waves are

released due to micro-structural changes in the material. These micro-structural changes

could be propagating cracks or corrosion, but can also be caused by friction between two

parts of a structure. The term Acoustic Emission describes the stress waves as well as

the NDT technique which uses these stress waves. The waves travel through the

structure and result in small displacements on the surface, which can be detected by

suitable sensors [1]. AE is a passive NDT technique which means the instrument has

just a receiving unit which is capable of picking up the emission caused by the

propagation of the flaw itself. An active inspection method, in contrast, needs a

transmitting and receiving unit and measures the changes of a signal sent through the

structure.

The discovery of the generation of these stress waves by Joseph Kaiser in 1950

marks the beginning of Acoustic Emission as an NDT technique. Joseph Kaiser studied

this phenomenon occurring during tensile tests of metal specimens. Earlier, a similar

phenomenon was already widely studied prior or during earthquakes and this seismology

has much in common with AE. Since the first discovery AE has developed into a widely

used NDT technique.

Acoustic Emission has already been measurable from cracks down to a few

hundred square micrometers and is therefore able to detect flaws long before structural

integrity is affected and before most other NDT techniques, such as Ultrasonic, X-ray or

Thermography, can sense those cracks [2]. In the strict sense the flaw propagation is

measured, since only the active damage emits stress waves.

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Acoustic Emission (AE) is a passive inspection technique which, unlike

Ultrasonic, does not actively send any signal through the structure, but detects stress

waves from the damage itself when it propagates. A few sensors can monitor a

relatively large area and can detect different types of damage usually long before other

NDT techniques are able to find them. Also, AE testing can be performed when the

structure is in service. This makes AE an ideal tool for SHM applications.

Accurate damage location is important for Acoustic Emission SHM (and NDT)

systems since this technique is able to detect signals from propagating damages in

relatively far distances from the sensor. Exact source location is not only important to

reduce time for further inspection and repairs but, also to identify multiple damage to

understand fatigue damage propagation or to find indications about damage origin.

Although it is already reported that the actual AE signal can give an indication about the

actual damage type, exact source location might also aid to fulfill this SHM task.

1.2 Problem Statement

Pipes are used widely in our domestic and industry. It is one of the most

important parts of human life because piping system is a mechanism of delivering or

transporting a fluid (liquid or gas), mixture of fluids and others from one location to

another. Pipes need to be monitored periodically in order to determine damage to the

pipe and its associated equipment, maximize the efficiency and safety of the pipeline,

minimize potential accidents, and safeguard company and public interests [1].

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1.3 Objective of the Study

The main objective of this study is to localize defect in the pipeline using

acoustic emission and estimate the geometry of defect from acoustic emission signals.

1.4 Scope of the Study:

To use acoustic emission technology to monitor the pipeline.

To undertake experimental test in the lab scale rig.

To Analyze AE signals using MATLAB software.

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