Guided Wave Defect Location In Plate Using Wavelet Technique.
SUPERVISOR DECLARATION
“I hereby declare that I read this thesis and in my opinion this thesis is sufficient in terms of scope and quality for the award of the degree of
Bachelor of Mechanical Engineering (Plant & Maintenance)”
Signature :……….
Supervisor name : DR. NOR SALIM BIN MUHAMMAD
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GUIDED WAVE DEFECT LOCATION IN PLATE USING WAVELET TECHNIQUE
MOHAMAD RAZIN BIN ROSLI
A thesis submitted in partial fulfilment of the Requirement for the award of the degree of
Bachelor of Mechanical Engineering (Plant& Maintenance)
Faculty of Mechanical Engineering UniversitiTeknikal Malaysia Melaka
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DECLARATION
“ I hereby declare that the work in this thesis is my own except for summaries and quotation which have been duly acknowledged ”
Signature :………
Author : MOHAMAD RAZIN BIN ROSLI
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Praise to Allah the Almighty and to my beloved Father and Mother, And to my beloved siblings and friends
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ACKNOWLEDGEMENT
Foremost, I would like to express my sincere gratitude to my supervisor, Dr. Nor Salim Bin Muhammad for the continuous support of my final year project 1 and research, for his patience, motivation, enthusiasm, and immense knowledge. His guidance helped me in all the time of research and writing of this thesis. I could not have imagined having a better supervisor for my final year project.
Besides my advisor, I would like to thank the rest of fellow labmates, friends and technician for the sleepless nights we were working together before deadlines. Last but not the least, I would like to thank my family for supporting me spiritually throughout my life.
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ABSTRACT
Guided wave is a method that widely acknowledged as one of the most encouraging tools for quantitative for identification of damage in large structures. The technique has potential to be improved by using signal processing to visualize defects in the inspected areas. The visualization of defect is important for interpretation of complicated waveform in structures. This paper is trying to analyse the guided wave signal by using a wavelet approach. The wavelet response is an efficient method to detect and characterize a discontinuity in the acoustical impedance profile of a material. The wavelet technique that been approached was used a scalogram and spectrogram which created images from the measured waveform to give an option for defect identification and location in large structures.
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ABSTRAK
Gelombang berpandu adalah satu kaedah yang diperakui secara meluas sebagai satu alat yang menggalakkan pengukuran quantitatif untuk mengenalpasti kerosakan di dalam struktur yang besar. Teknik ini mempunyai potensi untuk dipertingkatkan dengan menggunakan pemprosesan isyarat untuk menggambarkan kerosakan di kawasan yang diperiksa. Penggambaran kerosakan adalah penting untuk tafsiran gelombang yang kompleks di dalam struktur. Kertas kerja ini cuba untuk menganalisis isyarat gelombang berpandu dengan menggunakan pendekatan „wavelet‟. Hasil keluaran data wavelet adalah satu kaedah yang berkesan untuk mengesan dan mencirikan ketakselanjaran dalam profil galangan akustik kepada sesuatu bahan. Teknik wavelet yang telah diberi pendekatan telah menggunakan „scalogram‟ dan „spectrogram‟ yang mewujudkan imej dari bentuk gelombang yang diukur untuk memberi pilihan untuk mengenal pasti kecacatan dan lokasi dalam struktur besar
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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 xi
LIST OF FIGURES xii
CHAPTER 1 INTRODUCTION 1
1.1 Project Background 1
1.2 Problem Statement 4
1.3 Objective 4
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CHAPTER TITLE PAGE
CHAPTER 2 LITERATURE REVIEW 5
2.1 Introduction to Guided Wave and Lamb Wave 5
2.1.1 Guided Wave 5
2.1.2 Lamb Wave 7
2.1.3 Dispersion Curve 8
2.1.4 Application 9
2.2 Wavelet Technique 10
2.2.1 The Continuous Wavelet Transform 11 2.2.2 Discrete Wavelet Transform 12 2.2.3 Spectrogram and Scalogram 13
CHAPTER 3 METHODOLOGY 16
3.1 Flowchart 17
3.2 Guided Wave Dispersion Curve for Aluminium 18 3.3 Wavelet Method for Defect Detections 21
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CHAPTER TITLE PAGE
CHAPTER 4 RESULT & DISCUSSION FOR SIMULATION 24 4.1 Design of The Aluminium Plate for Simulation 24
4.2 Wave Propagation Behaviour 26
4.3 Result and Analysis for Simulation 28
4.4 Wavelet Analysis 32
CHAPTER 5 RESULT & ANALYSIS FOR EXPERIMENT 34
5.1 Aluminium Plate 34
5.2 Sensors and Instrumentations 37
5.3 Function of the Instrumentations 39 5.4 Schematic Diagram for Instrument Arrangement 40
5.5 Experimental setup 40
5.6 5 Points Noise Cancellation 43
5.7 Wavelet Analysis 45
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CHAPTER TITLE PAGE
CHAPTER 6 CONCLUSIOIN AND RECOMMENDATION 64
6.1 Conclusion 64
6.2 Recommendation 66
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LIST OF TABLES
TABLE TITLE PAGE
4.1 Mechanical properties of aluminium plate 26 5.1 Table of apparatus for the experiment 37
5.2 Function of the instruments 39
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LIST OF FIGURES
FIGURE TITLE PAGE
1.1 Differentiation between noise signal and denoised
signal 3
1.2 Signal after been recovering form wavelet shrinkage
technique 3
2.1 Guided wave's wave propagation through medium 6
2.2 Lamb wave propagating in plate 7
2.2 (a) symmetric 7
2.2 (b) anti-symmetric 7
2.3 Phase velocity versus frequency dispersion curve 8 2.4 Group velocity versus frequency dispersion curve 8 2.5 Model of probe elements for guided wave excitation 10
2.5 (a) Single ring element 9
2.5 (b) Array type element 10
2.6 Wavelet analysis for signal 11
2.7 Discrete transform wavelet and Continuous wavelet
transform 13
2.8 The image of the scalogram 14
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FIGURE TITLE PAGE
3.1 Project flow chart 17
3.2 Phase velocity for aluminium 6 mm 18
3.3 Group velocity for aluminium 6mm 19
3.4 Applied force using a tone burst signal 20
3.5 Frequency bandwidth of the signal
(centre frequency at 100 kHz) 20
3.6 Signal with noise 21
3.7 Noise 22
3.8 Visualising the subtracting of the noise in term
of equation 22
3.9 The final signal after subtract ( ) 22
4.1 Example of simulated plate 25
4.2 Single round defect 25
4.3 Wave excitation behaviour when the signal
is introduced 26
4.4 Force direction for S0-mode 27
4.5 Force direction for A0-mode 27
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FIGURE TITLE PAGE
4.7 U1 time waveform for no defect plate 29
4.8 U3 time wave form for round defect plate 29 4.9 U1 time wave form for the round defect plate 30
4.10 U3 signal after subtracted 30
4.11 U1 signal after subtracted 31
4.12 Screenshot of the wavelet interface 31
4.13 Wavelet analysis for U1 32
4.14 Wavelet analysis for U3 33
5.1(a) Dimension of the aluminium plate 34
5.1 (b) Diagram for defect plate 35
5.2 (a) 2 mm depth groove 35
5.2 (b) 3 mm depth groove 35
5.2 (c) 4 mm depth groove 36
5.2 (d) No defect plate 36
5.3 Acrylic wedge 41
5.4 Aqualene wedge 41
5.5 Interface of guided wave program 42
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FIGURE TITLE PAGE
5.7 Location of the transducer while run the experiment 44 5.8 Example of the signal after using 5 points cancellation 44
5.9 Wavelet interface 45
5.10 Wavelet analysis of 2 mm with 80 kHz (Ao) 46 5.11 Wavelet analysis of 2 mm with 100 kHz (Ao) 47 5.12 Wavelet analysis of 2 mm with 120 kHz (Ao) 48 5.13 Wavelet analysis of 3 mm with 80 kHz (Ao) 49 5.14 Wavelet analysis of 3 mm with 100 kHz (Ao) 50 5.15 Wavelet analysis of 3 mm with 120 kHz (Ao) 51 5.16 Wavelet analysis of 4 mm with 80 kHz (Ao) 52 5.17 Wavelet analysis of 4 mm with 100 kHz (Ao) 53 5.18 Wavelet analysis of 4 mm with 120 kHz (Ao) 54 5.19 Wavelet analysis of 2 mm with 80 kHz (So) 55 5.20 Wavelet analysis of 2 mm with 100 kHz (So) 56 5.21 Wavelet analysis of 2 mm with 120 kHz (So) 57 5.22 Wavelet analysis of 3 mm with 80 kHz (So) 58 5.23 Wavelet analysis of 3 mm with 100 kHz (So) 59 5.24 Wavelet analysis of 3 mm with 120 kHz (So) 60
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FIGURE TITLE PAGE
5.25 Wavelet analysis of 4 mm with 80 kHz (So) 61 5.26 Wavelet analysis of 4 mm with 100 kHz (So) 62 5.27 Wavelet analysis of 4 mm with 120 kHz (So) 63
6.1 Time arrival of defect echo in Ao 65
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CHAPTER 1
INTRODUCTION
1.0 OVERVIEW
This chapter covers the introduction of this project that involved the project background, problem statement, objectives of the project and scope of study.
1.1 BACKGROUND
Wavelet theory started from research activities in many areas of science and engineering. As a result, it finds applications in a wide range of practical problems. Wavelet techniques are indicatively suited for non-stationary signals for which classic Fourier methods are ineffective. Evolvements over the last decade have led to many new wavelet applications such as image compression, turbulence, human vision, radar, and earthquake prediction (Jaideva C.Goswami, 2011).
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2 Basically wavelets transform is an another approach to the short time Fourier transfom which is to run-over the resolution problem. Principle of wavelet transform is divided the signal into a bunch of signals which will representing the same signal but all correspond to different frequency bands.
There are resemblances between fast fourier transform (FFT) and wavelet analysis which FFT and discrete wavelet transform are both linear operations that develop a data structure that contains segments of various lengths, usually filling and trnsforming it into a different data vector of length . (Graps 1995)
Without us noticing, wavelet already been used as an application since 1980‟s which David Marr, an expert on human visual system, work at MIT‟s Artificial Intelligence Laboratory on artificial vision on robots. His goal was to learn why the first attempts to create a robot capable of compassionate its surrounding were unsuccessful (Meyer, 1993). Marr theorized two things which he claims that intensity changes occur at different scales in an image, so that their optimal detection requires the use operators of different sizes. And the theory that he theorized is the sudden changes produce a peak or stiff in the first derivative of the image. His hypothesis require a different operator and it should be able of being turn to act at any desire scale which that operator was a wavelet referred as a “Marr wavelet”.
The other famous application that used nowadays is denoising noisy data. In world of science, scientists are faced with the problem of recovering a signal from a noisy data. This can be done through a technique called wavelet shrinkage and thresholding methods, which David Donoho had been worked on for several years (D.Donoho, 1993). This denoised technique is an important step forward in conducting noisy data because the denoising is carried out without smoothing out the sharp structures. The final result then is a cleaned-up signal that still shows important details.
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Figure 1.1: Differentiation between noise signal and denoised signal
Figure 1.2: Signal after been recovering form wavelet shrinkage technique (D.Donoho, 1993)
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1.2 PROBLEM STATEMENT
Guided waves, such as Lamb waves have found many applications towards damage defection, location and measurement. Permanently mounted transducer can be used to generate and detect guided waves in structures. However, the number and location of the bonded transducers limit resolution and fidelity of defect detection and measurement in amplitude and frequency monitoring FFT technique. The conventional time waveform does not provide the frequency information whilst the FFT is only valid for steady-state vibration in machinery. The wavelet response is a method which enables an easy probing of depth dependent properties of material which display amplitude changes in scalogram and frequency changes in spectrogram. The use of this technique gives an option to analyse on defect response in structures.
1.3 OBJECTIVES
The objectives of this study are as below:
1. To apply wavelet analysis for structural health monitoring.
2. To study effect of depth on frequency component in reflected waveform defect.
1.4 SCOPE OF STUDY
The scopes of this study are as below:
1. Study on benefit of wavelet in defect analysis.
2. Develop wavelet application for defect response in Labview.
3. Analyze the effect of wavelet analysis on defect response by varying parameters in wavelet visual method, scalogram and spectrogram.
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CHAPTER 2
LITERATURE REVIEW
2.0 OVERVIEW
This chapter covers the review about guided wave, what is defect location and also wavelet technique itself. The review gathers is collected from the past journals, articles, technical paper and reference book that involved the area of this chapter.
2.1 INTRODUCTION TO GUIDED WAVE AND LAMB WAVE
2.1.1 GUIDED WAVE
Guided wave testing (GW) is one of the Non-Destructive Testing (NDT) that had been recognized and approved through worldwide especially in term of the testing which is much easier. In industrial and civil structures, the inspection to
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6 detect defect or damage is very important because it involve safety of the structure and people. Speak about guided wave, the wave will travel along the surface and are guided by the geometry of the surface (Singh, 2014). The guided wave can be generated as various modes with respect to frequency, thickness, and incident angle and they can propagate a large distance along the geometry of a structure (Lamb, 1989). Guided wave technique is particularly useful in NDT of thin plate and tubular structures which are very hard to test.
For one-dimensional wave propagation, the assumption is stated that it is used for conventional surface reflectance technique which used to control the quality, such as test or impact echo impulse response.
Figure 2.1: Guided wave's wave propagation through medium
Since 1980s, application of guided wave studies had been carried out by plentiful of researchers such as Rose and Cawley and it was demonstrated that guided waves can be applied to safety insurance of nuclear power station and aircraft successfully (Y. Cho, 1995).
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2.1.2 LAMB WAVE
When two boundaries in solid plates are close together, the elastic wave motion on each surface will interact to produce lamb waves (Scruby, 1990). The lamb wave theory was originally developed by Horace Lamb in 1916 to describe the characteristics of waves propagating in plates. Lamb wave can be generated with free boundaries with an infinite number of modes for both symmetric and anti-symmetric displacements with the layer.
The usual way to describe the propagation characteristics is by the use of dispersion curves based on the plate mode phase velocity as a function of the product of frequency times thickness. Normally the dispersion curves are labelled as and so on which is depending on the mode whether it is symmetric or anti-symmetric
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Basically wavelets transform is an another approach to the short time Fourier transfom which is to run-over the resolution problem. Principle of wavelet transform is divided the signal into a bunch of signals which will representing the same signal but all correspond to different frequency bands.
There are resemblances between fast fourier transform (FFT) and wavelet analysis which FFT and discrete wavelet transform are both linear operations that develop a data structure that contains segments of various lengths, usually filling and trnsforming it into a different data vector of length . (Graps 1995)
Without us noticing, wavelet already been used as an application since 1980‟s which David Marr, an expert on human visual system, work at MIT‟s Artificial Intelligence Laboratory on artificial vision on robots. His goal was to learn why the first attempts to create a robot capable of compassionate its surrounding were unsuccessful (Meyer, 1993). Marr theorized two things which he claims that intensity changes occur at different scales in an image, so that their optimal detection requires the use operators of different sizes. And the theory that he theorized is the sudden changes produce a peak or stiff in the first derivative of the image. His hypothesis require a different operator and it should be able of being turn to act at any desire scale which that operator was a wavelet referred as a “Marr wavelet”.
The other famous application that used nowadays is denoising noisy data. In world of science, scientists are faced with the problem of recovering a signal from a noisy data. This can be done through a technique called wavelet shrinkage and thresholding methods, which David Donoho had been worked on for several years (D.Donoho, 1993). This denoised technique is an important step forward in conducting noisy data because the denoising is carried out without smoothing out the sharp structures. The final result then is a cleaned-up signal that still shows important details.
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Figure 1.1: Differentiation between noise signal and denoised signal
Figure 1.2: Signal after been recovering form wavelet shrinkage technique
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1.2 PROBLEM STATEMENT
Guided waves, such as Lamb waves have found many applications towards damage defection, location and measurement. Permanently mounted transducer can be used to generate and detect guided waves in structures. However, the number and location of the bonded transducers limit resolution and fidelity of defect detection and measurement in amplitude and frequency monitoring FFT technique. The conventional time waveform does not provide the frequency information whilst the FFT is only valid for steady-state vibration in machinery. The wavelet response is a method which enables an easy probing of depth dependent properties of material which display amplitude changes in scalogram and frequency changes in spectrogram. The use of this technique gives an option to analyse on defect response in structures.
1.3 OBJECTIVES
The objectives of this study are as below:
1. To apply wavelet analysis for structural health monitoring.
2. To study effect of depth on frequency component in reflected waveform defect.
1.4 SCOPE OF STUDY
The scopes of this study are as below:
1. Study on benefit of wavelet in defect analysis.
2. Develop wavelet application for defect response in Labview.
3. Analyze the effect of wavelet analysis on defect response by varying parameters in wavelet visual method, scalogram and spectrogram.
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CHAPTER 2
LITERATURE REVIEW
2.0 OVERVIEW
This chapter covers the review about guided wave, what is defect location and also wavelet technique itself. The review gathers is collected from the past journals, articles, technical paper and reference book that involved the area of this chapter.
2.1 INTRODUCTION TO GUIDED WAVE AND LAMB WAVE
2.1.1 GUIDED WAVE
Guided wave testing (GW) is one of the Non-Destructive Testing (NDT) that had been recognized and approved through worldwide especially in term of the testing which is much easier. In industrial and civil structures, the inspection to
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detect defect or damage is very important because it involve safety of the structure and people. Speak about guided wave, the wave will travel along the surface and are guided by the geometry of the surface (Singh, 2014). The guided wave can be generated as various modes with respect to frequency, thickness, and incident angle and they can propagate a large distance along the geometry of a structure (Lamb, 1989). Guided wave technique is particularly useful in NDT of thin plate and tubular structures which are very hard to test.
For one-dimensional wave propagation, the assumption is stated that it is used for conventional surface reflectance technique which used to control the quality, such as test or impact echo impulse response.
Figure 2.1: Guided wave's wave propagation through medium
Since 1980s, application of guided wave studies had been carried out by plentiful of researchers such as Rose and Cawley and it was demonstrated that guided waves can be applied to safety insurance of nuclear power station and aircraft successfully (Y. Cho, 1995).
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2.1.2 LAMB WAVE
When two boundaries in solid plates are close together, the elastic wave motion on each surface will interact to produce lamb waves (Scruby, 1990). The lamb wave theory was originally developed by Horace Lamb in 1916 to describe the characteristics of waves propagating in plates. Lamb wave can be generated with free boundaries with an infinite number of modes for both symmetric and anti-symmetric displacements with the layer.
The usual way to describe the propagation characteristics is by the use of dispersion curves based on the plate mode phase velocity as a function of the product of frequency times thickness. Normally the dispersion curves are labelled as and so on which is depending on the mode whether it is symmetric or anti-symmetric