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16 diagnostics have associated advantages and disadvantages. The most common active techniques are based upon the measurement of the electro-mechanical impedance or the use of ultrasonic guided waves. With few exceptions, active methods require the measurement and storage of a vast amount of baseline information and, often, require a fairly dense array of transducers. However, active methods control the excitation characteristics within the system. Therefore, they possess the capability to customize the excitation in order to achieve greater sensitivity to specific defect types. Local passive methods for damage identification can alleviate complications associated with the requirement of dense sensor arrays, large storage of baseline feature measurements, complex signal processing and statistical pattern process algorithms. The most common passive approaches use piezoelectric transducers to monitor impacts or acoustic emissions generated from internal material damage. These methods, thereby, rely on measurement of propagating waves within the structure. In this scenario, damage detection is straight forward. Measurements above a specified threshold are assumed to correspond to the onset of damage. Damage localization can be evaluated through the use of simple triangulation algorithms. Otherwise, higher levels of damage identification can be achieved by incorporating neural networks or dynamic models. A disadvantage of passive approaches is the requirement of continuous system monitoring, since it is generally not known when damage may occur. In addition, each of the passive methods discussed show difficulty in accurate damage identification for large scale complex structures. 1.4. VIBRATION-BASED VS GUIDED WAVES- BASED TECHNIQUES: OUR CHOICE Many structural health monitoring techniques developed over the years are based on the detection of changes in the dynamic behaviour of the monitored components. Valuable review of the state-of-the-art in dynamics-based structural health monitoring can be found in [8, 9, 10]. Early studies evaluated the influence on the natural frequencies of localized stiffness reduction caused by
INTRODUCTION 17 damage. These investigations have generally proven that natural frequencies are damage indicators which generally show low sensitivity and they do not allow the determination of the location of damage. More recent studies have investigated the effect of localized and distributed damage on mode shapes, operational deflection shapes (ODS) and corresponding curvatures. The detection of small changes in the deformed configuration of the structure can be used to localize damage and, potentially, estimate its severity. The existing techniques vary on the basis of the type of dynamic response signals used for the analysis and on the features or parameters considered as damage indicators. Such features or parameters must obviously be sensitive to damage and must vary monotonically with the extent of damage. In particular, small variations from an undamaged state can be highlighted by successive spatial differentiations of the deflections, as typically required for estimating curvature modes and associated strain energy. These modal-based methods are very attractive as they provide information regarding the general state of health of the structure. However, they tend to have limited sensitivity and, generally, they are not accurate enough to provide detailed information regarding damage type and extent. The lack in sensitivity and capability of discriminating damage from changes in the operating conditions of modal-based methods can be overcome by applying inspection techniques based on Guided Ultrasonic Waves (GUWs) propagation [5, 6, 7]. Guided waves, such as Lamb waves, show sensitivity to a variety of damage types and, as opposed to bulk waves used in traditional ultrasonic techniques, have the ability to travel relatively long distances within the structure under investigation. For this reason, GUWs are particularly suitable for SHM applications, which may employ a built-in sensor/actuator network to interrogate and assess the state of health of the structure. In most applications, GUWs are generated and received by piezoelectric transducers which can both excite the structure and record its response. In our case, the sensing device is the SLDV. The fundamentals of this type of operation consist in evaluating the characteristics of the propagation along the wave path between each transducer/receiver pair and detecting reflections associated with damage. The interpretation of the signals characteristics and the detection of reflections are,
Page 1: Unione Europea Università degli St
Page 5 and 6: RINGRAZIAMENTI E’ per me doveroso
Page 7: Vorrei, infine, disporre del vocabo
Page 11 and 12: CONTENTS Abstract of dissertation .
Page 13 and 14: LIST OF FIGURES AND TABLES Fig. 1.1
Page 15 and 16: Fig. 3.32 - : RMS of the field of r
Page 17 and 18: ABSTRACT OF DISSERTATION 7 ABSTRACT
Page 19 and 20: ABSTRACT OF DISSERTATION 9 are: The
Page 21 and 22: INTRODUCTION 11 Ideally, routinely
Page 23 and 24: INTRODUCTION 13 Feature extraction
Page 25: INTRODUCTION 15 1.3. GLOBAL VERSUS
Page 29 and 30: INTRODUCTION 19 between shifts at v
Page 31 and 32: INTRODUCTION 21 Space Shuttle Orbit
Page 33 and 34: INTRODUCTION 23 1.6. GUIDED WAVES-B
Page 35 and 36: INTRODUCTION 25 Fig. 1.3 - Differen
Page 37 and 38: INTRODUCTION 27 Considering the arg
Page 39 and 40: INTRODUCTION 29 Fig. 1.6 - Differen
Page 41 and 42: INTRODUCTION 31 2 ω c 2 k = 2 ω
Page 43 and 44: INTRODUCTION 33 Fig. 1.8 - Frequenc
Page 45 and 46: INTRODUCTION 35 where 1 1 p1 c k =
Page 47 and 48: INTRODUCTION 37 Fig. 1.12 - Group v
Page 49 and 50: INTRODUCTION 39 Fig. 1.13 - Directi
Page 51 and 52: INTRODUCTION 41 for very simple cas
Page 53 and 54: INNOVATIVE SHM TECHNIQUES BASED ON
Page 63 and 64: EXPERIMENTAL ANALYSIS 53 3. EXPERIM
Page 65 and 66: EXPERIMENTAL ANALYSIS 55 Fig. 3.3 -
Page 67 and 68: EXPERIMENTAL ANALYSIS 57 same point
Page 73 and 74: EXPERIMENTAL ANALYSIS 63 of the ene
Page 75 and 76: EXPERIMENTAL ANALYSIS 65 Fig. 3.13
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EXPERIMENTAL ANALYSIS 67 Fig. 3.16
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EXPERIMENTAL ANALYSIS 69 Analysis g
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EXPERIMENTAL ANALYSIS 71 Analysis g
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EXPERIMENTAL ANALYSIS 73 and in spa
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EXPERIMENTAL ANALYSIS 75 and are tr
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EXPERIMENTAL ANALYSIS 77 obtained w
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EXPERIMENTAL ANALYSIS 81 (a) t = 68
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EXPERIMENTAL ANALYSIS 97 The data p
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EXPERIMENTAL ANALYSIS 101 To increa
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EXPERIMENTAL ANALYSIS 103 Both of t
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EXPERIMENTAL ANALYSIS 107 Complete
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FINITE ELEMENT MODELING OF WAVE PRO
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CONCLUSIONS AND FUTURE WORK 131 5.
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CONCLUSIONS AND FUTURE WORK 133 cas
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REFERENCES 135 [6] Rose, J. L. “A
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REFERENCES 137 [20] Ko, J. M., Wong
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REFERENCES 139 [35] J. D. Achenbach
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