tesi R. Valiante.pdf - EleA@UniSA

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12 1.1. GENERAL SHM PARADIGM Damage identification in accordance with an SHM paradigm involves progressive stages. According to Sohn at al. [3] and Worden and Dulieu-Barton [4], this sequential process includes operational evaluation, data acquisition, signal processing, feature extraction and statistical pattern processing (Fig. 1.1). Fig. 1.1 - Scheme of SHM based damage identification process. The operational evaluation entails the appraisal of economic and life safety motives for the SHM system, definition of damage within the structure, determination of the operational and environmental conditions under which the structure is subjected and how this may affect the ability for data acquisition, which involves the collection of the dynamic response measurements in the system. Signal processing, which includes data cleansing, denoising and data transformation, is paramount in the damage identification procedure. Common methods of data cleansing and de-noising include digital or analogical filters, signal averaging and more recently, the use of discrete wavelet transform and of multi-dimensional Fourier transforms.
INTRODUCTION 13 Feature extraction consists of quantifying and collecting damage sensitive variables. For enhanced damage identification reliability, it is necessary to carefully select features that allow for maximum sensitivity to the particular damage of interest while also ensuring that their sensitivity to operational and environmental variability is minimal. Due to likely stringent memory and processing limitations of on-board applications, features should be dimensionally low and computationally simple. 1.2. DEFINITION OF DAMAGE IN CFRP COMPOSITE COMPONENTS Damage can be defined as changes in the material, geometry or connectivity of the system that adversely affect its current or future performance. Although defects exist within any engineering material at the microscopic level, it is generally accounted for in the initial design of the structure, such as through the appropriate designation of material yield strength. As a result, the system can still perform according to the optimal design specifications. Contrarily, damage results in system performance below idealized conditions. Common damage sources include fatigue, overloading conditions, material degradation through environmental effects, and unanticipated discrete events such as impacts or seismic events. Carbon Fiber Reinforced Polymer (CFRP) composites are becoming widely used within the aerospace industry due to its very high specific strength and stiffness properties. However, FRP composites are also quite susceptible to various forms of damage. Common damage modes within FRP composites include matrix cracking, delamination, and fiber breakage [28]. For composite laminates, delamination is a major concern, since this can significantly reduce the load carrying capacity of the laminate. Unlike metallic structures, which are homogenous and have the ability to dissipate energy through yielding, composite structures are relatively brittle and exhibit weak interfacial strength between laminae. As a consequence, even low velocity impacts on FRP composites can introduce significant delamination that is not visible from the surface. In addition to the laminate damage described above,
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: INTRODUCTION 11 Ideally, routinely
Page 25 and 26: INTRODUCTION 15 1.3. GLOBAL VERSUS
Page 27 and 28: INTRODUCTION 17 damage. These inves
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
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EXPERIMENTAL ANALYSIS 63 of the ene
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EXPERIMENTAL ANALYSIS 65 Fig. 3.13
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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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