259 research outputs found

    Application and Challenges of Signal Processing Techniques for Lamb Waves Structural Integrity Evaluation: Part A-Lamb Waves Signals Emitting and Optimization Techniques

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    Lamb waves have been widely studied in structural integrity evaluation during the past decades with their low-attenuation and multi-defects sensitive nature. The performance of the evaluation has close relationship with the vibration property and the frequency of Lamb waves signals. Influenced by the nature of Lamb waves and the environment, the received signals may be difficult to interpret that limits the performance of the detection. So pure Lamb waves mode emitting and high-resolution signals acquisition play important roles in Lamb waves structural integrity evaluation. In this chapter, the basic theory of Lamb waves nature and some environment factors that should be considered in structural integrity evaluation are introduced. Three kinds of typical transduces used for specific Lamb waves mode emitting and sensing are briefly introduced. Then the development of techniques to improve the interpretability of signals are discussed, including the waveform modulation techniques, multi-scale analysis techniques and the temperature effect compensation techniques are summarized

    An artificial bee colony optimization based matching pursuit approach for ultrasonic echo estimation

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    Ultrasonic echo estimation is important in ultrasonic non-destructive evaluation and material characterization. Matching pursuit is one of the most popular methods for the purpose of estimating ultrasonic echoes. In this paper, an artificial bee colony optimization based matching pursuit approach (ABC-MP) is proposed specifically for ultrasonic signal decomposition by integrating the artificial bee colony algorithm into the matching pursuit method. The optimal atoms are searched from a continuous parameter space over a tailored Gabor dictionary in ABC-MP instead of a discrete parameter space in matching pursuit. As a result, echoes characterized by a set of physical parameters can be estimated accurately and efficiently. The performance of ABC-MP is tested using both simulated signals and real ultrasonic signals, and compared with matching pursuit. Results clearly demonstrate the superior performance of the proposed ABC-MP approach over matching pursuit in ultrasonic echo estimation in terms of the shape and amplitude of the recovered echoes and the reconstructed signal, and the residue signal

    Improvement of signal analysis for the ultrasonic microscopy

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    This dissertation describes the improvement of signal analysis in ultrasonic microscopy for nondestructive testing. Specimens with many thin layers, like modern electronic components, pose a particular challenge for identifying and localizing defects. In this thesis, new evaluation algorithms have been developed which enable analysis of highly complex layer-stacks. This is achieved by a specific evaluation of multiple reflections, a newly developed iterative reconstruction and deconvolution algorithm, and the use of classification algorithms with a highly optimized simulation algorithm. Deep delaminations inside a 19-layer component can now not only be detected, but also localized. The new analysis methods also enable precise determination of elastic material parameters, sound velocities, thicknesses, and densities of multiple layers. The highly improved precision of determined reflections parameters with deconvolution also provides better and more conclusive results with common analysis methods.:Kurzfassung......................................................................................................................II Abstract.............................................................................................................................V List ob abbreviations........................................................................................................X 1 Introduction.......................................................................................................................1 1.1 Motivation.....................................................................................................................2 1.2 System theoretical description.....................................................................................3 1.3 Structure of the thesis..................................................................................................6 2 Sound field.........................................................................................................................8 2.1 Sound field measurement............................................................................................8 2.2 Sound field modeling..................................................................................................11 2.2.1 Reflection and transmission coefficients.........................................................11 2.2.2 Sound field modeling with plane waves..........................................................13 2.2.3 Generalized sound field position.....................................................................19 2.3 Receiving transducer signal.......................................................................................20 2.3.1 Calculation of the transducer signal from the sound field...............................20 2.3.2 Received signal amplitude..............................................................................21 2.3.3 Measurement of reference signals..................................................................24 3 Ultrasonic Simulation......................................................................................................27 3.1 State of the art............................................................................................................27 3.2 Simulation approach..................................................................................................28 3.2.1 Sound field measurement based simulation...................................................28 3.2.2 Reference signal based simulation.................................................................30 3.3 Determination of the impulse response.....................................................................31 3.3.1 1D ray-trace algorithm....................................................................................31 3.3.2 2D ray-trace algorithm....................................................................................33 3.3.3 Complexity reduction – optimizations.............................................................35 4 Deconvolution – Determination of reflection parameters............................................38 4.1 State of the art............................................................................................................39 4.1.1 Decomposition techniques..............................................................................39 4.1.2 Deconvolution.................................................................................................41 4.2 Analytic signal investigations for deconvolution.........................................................42 4.3 Single reference pulse deconvolution........................................................................44 4.4 Multi-pulse deconvolution..........................................................................................47 4.4.1 Homogeneous multi-pulse deconvolution.......................................................48 4.4.2 Multi-pulse deconvolution with simulated GSP profile....................................49 5 Reconstruction.................................................................................................................50 5.1 State of the art............................................................................................................50 5.2 Reconstruction approach...........................................................................................51 5.3 Direct material parameter estimation.........................................................................52 5.3.1 Sound velocities and layer thickness..............................................................52 5.3.2 Density, elastic modules and acoustic attenuation.........................................54 5.4 Iterative material parameter determination of a single layer......................................56 5.5 Reconstruction of complex specimens......................................................................60 5.5.1 Material characterization of multiple layers ....................................................60 5.5.2 Iterative simulation parameter optimization with correlation...........................62 5.5.3 Pattern recognition reconstruction of specimens with known base structure. 66 6 Applications and results.................................................................................................71 6.1 Analysis of stacked components................................................................................71 6.2 Time-of-flight and material analysis...........................................................................74 7 Conclusions and perspectives.......................................................................................78 References.......................................................................................................................82 Figures.............................................................................................................................86 Tables...............................................................................................................................88 Appendix..........................................................................................................................89 Acknowledgments.........................................................................................................100 Danksagung...................................................................................................................101Die vorgelegte Dissertation befasst sich mit der Verbesserung der Signalauswertung für die Ultraschallmikroskopie in der zerstörungsfreien Prüfung. Insbesondere bei Proben mit vielen dünnen Schichten, wie bei modernen Halbleiterbauelementen, ist das Auffinden und die Bestimmung der Lage von Fehlstellen eine große Herausforderung. In dieser Arbeit wurden neue Auswertealgorithmen entwickelt, die eine Analyse hochkomplexer Schichtabfolgen ermöglichen. Erreicht wird dies durch die gezielte Auswertung von Mehrfachreflexionen, einen neu entwickelten iterativen Rekonstruktions- und Entfaltungsalgorithmus und die Nutzung von Klassifikationsalgorithmen im Zusammenspiel mit einem hoch optimierten neu entwickelten Simulationsalgorithmus. Dadurch ist es erstmals möglich, tief liegende Delaminationen in einem 19-schichtigem Halbleiterbauelement nicht nur zu detektieren, sondern auch zu lokalisieren. Die neuen Analysemethoden ermöglichen des Weiteren eine genaue Bestimmung von elastischen Materialparametern, Schallgeschwindigkeiten, Dicken und Dichten mehrschichtiger Proben. Durch die stark verbesserte Genauigkeit der Reflexionsparameterbestimmung mittels Signalentfaltung lassen sich auch mit klassischen Analysemethoden deutlich bessere und aussagekräftigere Ergebnisse erzielen. Aus den Erkenntnissen dieser Dissertation wurde ein Ultraschall-Analyseprogramm entwickelt, das diese komplexen Funktionen auf einer gut bedienbaren Oberfläche bereitstellt und bereits praktisch genutzt wird.:Kurzfassung......................................................................................................................II Abstract.............................................................................................................................V List ob abbreviations........................................................................................................X 1 Introduction.......................................................................................................................1 1.1 Motivation.....................................................................................................................2 1.2 System theoretical description.....................................................................................3 1.3 Structure of the thesis..................................................................................................6 2 Sound field.........................................................................................................................8 2.1 Sound field measurement............................................................................................8 2.2 Sound field modeling..................................................................................................11 2.2.1 Reflection and transmission coefficients.........................................................11 2.2.2 Sound field modeling with plane waves..........................................................13 2.2.3 Generalized sound field position.....................................................................19 2.3 Receiving transducer signal.......................................................................................20 2.3.1 Calculation of the transducer signal from the sound field...............................20 2.3.2 Received signal amplitude..............................................................................21 2.3.3 Measurement of reference signals..................................................................24 3 Ultrasonic Simulation......................................................................................................27 3.1 State of the art............................................................................................................27 3.2 Simulation approach..................................................................................................28 3.2.1 Sound field measurement based simulation...................................................28 3.2.2 Reference signal based simulation.................................................................30 3.3 Determination of the impulse response.....................................................................31 3.3.1 1D ray-trace algorithm....................................................................................31 3.3.2 2D ray-trace algorithm....................................................................................33 3.3.3 Complexity reduction – optimizations.............................................................35 4 Deconvolution – Determination of reflection parameters............................................38 4.1 State of the art............................................................................................................39 4.1.1 Decomposition techniques..............................................................................39 4.1.2 Deconvolution.................................................................................................41 4.2 Analytic signal investigations for deconvolution.........................................................42 4.3 Single reference pulse deconvolution........................................................................44 4.4 Multi-pulse deconvolution..........................................................................................47 4.4.1 Homogeneous multi-pulse deconvolution.......................................................48 4.4.2 Multi-pulse deconvolution with simulated GSP profile....................................49 5 Reconstruction.................................................................................................................50 5.1 State of the art............................................................................................................50 5.2 Reconstruction approach...........................................................................................51 5.3 Direct material parameter estimation.........................................................................52 5.3.1 Sound velocities and layer thickness..............................................................52 5.3.2 Density, elastic modules and acoustic attenuation.........................................54 5.4 Iterative material parameter determination of a single layer......................................56 5.5 Reconstruction of complex specimens......................................................................60 5.5.1 Material characterization of multiple layers ....................................................60 5.5.2 Iterative simulation parameter optimization with correlation...........................62 5.5.3 Pattern recognition reconstruction of specimens with known base structure. 66 6 Applications and results.................................................................................................71 6.1 Analysis of stacked components................................................................................71 6.2 Time-of-flight and material analysis...........................................................................74 7 Conclusions and perspectives.......................................................................................78 References.......................................................................................................................82 Figures.............................................................................................................................86 Tables...............................................................................................................................88 Appendix..........................................................................................................................89 Acknowledgments.........................................................................................................100 Danksagung...................................................................................................................10

    Approximation performance of model functions for blind deconvolution of ultrasonic reflections

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    Comparison of the approximation performance of the ultrasonic reflections by simple model functions used in blind deconvolution is presented. New model function was proposed where causality of the signal is easily modelled without the need for piecewise-linear equations. Parameter estimation technique was developed. Performance investigation was done for three model functions using four experimentally collected ultrasonic signals under different signal filtering conditions
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