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Acoustic Emission and Durability of Composite Materials


Acoustic Emission and Durability of Composite Materials


1. Aufl.

von: Nathalie Godin, Pascal Reynaud, Gilbert Fantozzi

139,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 15.02.2018
ISBN/EAN: 9781119510604
Sprache: englisch
Anzahl Seiten: 208

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Beschreibungen

<p>In this book, two kinds of analysis based on acoustic emission recorded during mechanical tests are investigated.</p> <p>In the first, individual, analysis, acoustic signature of each damage mechanism is characterized. So with a clustering method, AE signals that have similar shapes or similar features can be group together into a cluster. Afterwards, each cluster can be linked with a main damage. The second analysis is based on a global AE analysis, on the investigation of liberated energy, with a view to identify a critical point. So beyond this characteristic point, the criticality can be modeled with a power-law in order to evaluate time to failure.</p>
<p>Introduction ix</p> <p><b>Chapter 1 Acoustic Emission: Definition and Overview 1</b></p> <p>1.1 Overview 1</p> <p>1.2 Acoustic waves 8</p> <p>1.2.1 Infinite medium: volume waves 8</p> <p>1.2.2 Semi-infinite medium: surface waves 9</p> <p>1.2.3 Guided waves 9</p> <p>1.2.4 Anisotropic medium and wave attenuation 10</p> <p>1.3 The sensors and acquisition system 12</p> <p>1.4 Location of sources 16</p> <p>1.5 The extracted descriptors from the AE signal 21</p> <p>1.5.1 Time domain descriptors 22</p> <p>1.5.2 Frequency domain descriptors 26</p> <p>1.5.3 Time–frequency analysis 30</p> <p>1.6 The different analyses of AE data 32</p> <p>1.6.1 Conventional analysis: qualitative analysis 32</p> <p>1.6.2 Multivariable statistical analysis: application of pattern recognition techniques 42</p> <p>1.7 Added value of quantitative acoustic emission 55</p> <p><b>Chapter 2 Identification of the Acoustic Signature of Damage Mechanisms 59</b></p> <p>2.1 Selection of signals for analysis 59</p> <p>2.2 Acoustic signature of fiber rupture: model materials 63</p> <p>2.2.1 Characterization of the fiber at the scale of the bundle 64</p> <p>2.2.2 At the microcomposite scale 69</p> <p>2.2.3 At the minicomposite scale 72</p> <p>2.3 Discrimination using temporal descriptors of damage mechanisms in composites: single-descriptor analysis 75</p> <p>2.4 Identification of the acoustic signature of composite damage mechanisms from a frequency descriptor 79</p> <p>2.5 Identification of the acoustic signature of composite damage mechanisms using a time/frequency analysis 81</p> <p>2.6 Modal acoustic emission 82</p> <p>2.7 Unsupervised multivariable statistical analysis 84</p> <p>2.7.1 Damage identification for organic matrix composites 85</p> <p>2.7.2 Static fatigue damage sequence identification for a ceramic matrix composite 89</p> <p>2.7.3 Identification of the cyclic fatigue damage sequence for a ceramic matrix composite 92</p> <p>2.7.4 Validation of cluster labeling 96</p> <p>2.8 Supervised multivariable statistical analysis 100</p> <p>2.8.1 Library created from data based on model materials 100</p> <p>2.8.2 Library created from structured data by unsupervised classification 103</p> <p>2.9 The limits of multivariable statistical analysis based on pattern recognition techniques 104</p> <p>2.9.1 Performance of algorithms 105</p> <p>2.9.2 Influence of the acquisition conditions and the geometry of the samples 113</p> <p>2.10 Contribution of modeling: towards quantitative acoustic emission 120</p> <p><b>Chapter 3 Lifetime Estimation 123</b></p> <p>3.1 Prognostic models: physical or data-oriented models 125</p> <p>3.2 Generalities on power laws: link with seismology 128</p> <p>3.3 Acoustic energy 133</p> <p>3.3.1 Definition of acoustic energy 133</p> <p>3.3.2 Taking into account coupling and definition of equivalent energy 134</p> <p>3.4 Identification of critical times or characteristic times in long-term tests: towards lifetime prediction 136</p> <p>3.4.1 The R AE emission coefficient 137</p> <p>3.4.2 Optimal circle contribution: highlighting the critical region 139</p> <p>3.4.3 The attenuation coefficient B 140</p> <p>3.4.4 The R LU coefficient for cyclic fatigue tests 142</p> <p>3.4.5 The coupling between acoustic energy and mechanical energy: the Sentry function 144</p> <p>3.5 Simulation of the release of energy using a power law: prediction of the rupture time 146</p> <p>Conclusion 151</p> <p>Bibliography 153</p> <p>Index 181</p>
<strong>Nathalie Godin</strong>, MATEIS INSA, France. <p><strong>Gilbert Fantozzi</strong>, MATEIS INSA, France. <p><strong>Pascal Reynaud</strong>, CNRS, MATEIS INSA, France.

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