The amount and morphology of the graphite phase largely controls the resulting properties of cast iron. For instance, in flake graphite cast irons the mechanical properties are low while the thermal conductivity is high. This is in contrast with spheroidal graphite cast irons where the mechanical properties are high and the thermal conductivity is low. These differences are due to the different graphite morphologies and must be accounted for in the design work and material selection of cast iron components. In this work the influence of the graphite phase on the elastic and plastic deformation behaviour of cast irons has been studied. The material grades studied originate from castings for marine diesel engine piston rings with different chemical analyses. Two groups of pearlitic cast iron materials were studied; one with differences in graphite morphology and one with grey irons that differed in graphite content. For these different material grades the mechanical properties were correlated to microstructural parameters. In addition to standard uniaxial tensile tests, acoustic emission measurements were used for the study of deformation. When studying the modulus of elasticity of the cast iron it was found that the modulus of elasticity of the inherent graphite phase depends on the roundness of the graphite particles and is due to the strong anisotropy of the graphite phase. A linear correlation between nodularity and the modulus of elasticity of the graphite phase was derived. This correlation made it possible to account for the anisotropy of the graphite phase in the model used. By applying the linear function when modelling the effective modulus of elasticity, a high accuracy between experimental and theoretical values was achieved. Another factor affecting the elastic response when subjecting a cast iron component to tensile load was found to be the plastic deformation that actually occurs at very low strains for all of the studied cast iron grades. It was observed that the plastic deformation in the low strain elastic region, quantified by using acoustic emission measurements, increased linearly with decreasing modulus of elasticity. These measurements showed that the amount of plastic deformation in the elastic region was largely controlled by the graphite morphology. It was concluded that as the roundness of the graphite particles increases, the plastic deformation activity in the elastic region decreases. The plastic deformation activity continued linearly into the pronounced plastic region of the tensile tests. A decrease in roundness or increase in graphite fraction resulted in an increase of the amount of plastic deformation and the strain hardening exponent. A dependence between strength coefficient and graphite fraction was observed. Models for the flow curves for pearlitic cast irons were developed and shown to accurately reproduce the observed experimental curves. The surveys performed and conclusions from this thesis will be helpful in the design of new cast iron materials.

Currently, the maintenance and repair of civil engineering infrastructures (especially bridges and highways) have become increasingly important, as these structures age and deteriorate. Interface between two different mixes or strengths of concrete also appear in large concrete structures involving mass concreting such as dams, nuclear containment vessels, cooling towers etc., since joints between successive lifts are inevitable. These joints and interfaces are potential sites for crack formation, leading to weakening of mechanical strength and subsequent failure. In case of a bi-material interface, the stress singularities are oscillatory in nature and the fracture behavior of a concrete-concrete bi-material interface is much more complicated. A comprehensive experimental work has been undertaken for characterization of the behavior of different concrete-concrete interfaces under static and fatigue loading. The effect of specimen size on the concrete-concrete interfaces is studied and the non-linear fracture parameters such as fracture energy, mode I fracture toughness, critical crack tip opening displacement, critical crack length, length of process zone, brittleness number, size of process zone, crack growth resistance curve and tension softening diagram. These parameters are required for modeling the concrete-concrete interfaces in non-linear finite element analysis. Presently, the advanced non-destructive techniques namely acoustic emission, digital image correlation and micro-indentation have great capabilities to characterize the fracture behavior. The damage in plain concrete and concrete interface specimens is characterized both qualitatively and quantitatively using acoustic emission technique by measuring the width of fracture process zone and width of damage zones. The DIC technique is used to obtain the fracture parameters such as mode I and mode II fracture toughness and critical energy release rate. The micro-mechanical properties are obtained by performing depth-sensing micro-indentation tests on the concrete-concrete interfaces. Civil engineering structures such as long-span bridges, offshore structures, airport pavements and gravity dams are frequently subjected to variable-amplitude cyclic loadings in actual conditions. Hence, in order to understand the fracture behaviour under fatigue loading, the fatigue crack growth in plain concrete and concrete-concrete interface is also studied using the acoustic emission technique. An attempt is made to apply the Paris’ law, which is applicable to mechanical behaviour of metals, for acoustic emission count data. All these studies show that, as the difference in the compressive strength of concrete on either side of the interface increases, the load carrying capacity decreases and the fracture parameters indicate the increase in the brittleness of the specimens. It is concluded that the repair concrete should be selected in such a way that its elastic properties are as those of the parent concrete.

Oil Jet Cavitation Peening in Air (OPA) is capable of inducing compressive residual stress in standard aerospace materials. This paper demonstrates the process capabilities of OPA on Al 2024-T3. Specifically, changes in the workpiece residual stress, microhardness, mass loss and surface roughness are investigated as a function of the control parameters for the system. Additionally, the paper identifies a method to monitor the process in situ through the use of high frequency acoustic emission sensors. The results indicate the OPA process is capable of generating residual stresses comparable to those of standard shot peening, up to 60% of the yield strength of the material, at similar depths, around 300 µm. Finally, the acoustic emission signal may be utilized to monitor the process, specifically in predicting the microhardness and mass loss of the system.

Safety and reliability are prime concerns in aircraft performance due to the involved costs and risk to lives. Despite the best efforts in design methodology, quality evaluation in production and structural integrity assessment in-service, attainment of one hundred percent safety through development and use of a suitable in-flight health monitoring system is still a farfetched goal. And, evolution of such a system requires, first, identification of an appropriate Technique and next its adoption to meet the challenges posed by newer materials (advanced composites), complex structures and the flight environment. In fact, a quick survey of the available Non-Destructive Evaluation (NDE) techniques suggests Acoustic Emission (AE) as the only available method. High merit in itself could be a weakness - Noise is the worst enemy of AE. So, while difficulties are posed due to the insufficient understanding of the basic behavior of composites, growth and interaction of defects and damage under a specified load condition, high in-flight noise further complicates the issue making the developmental task apparently formidable and challenging. Development of an in-flight monitoring system based on AE to function as an early warning system needs addressing three aspects, viz., the first, discrimination of AE signals from noise data, the second, extraction of required information from AE signals for identification of sources (source characterization) and quantification of its growth, and the third, automation of the entire process. And, a quick assessment of the aspects involved suggests that Artificial Neural Networks (ANN) are ideally suited for solving such a complex problem. A review of the available open literature while indicates a number of investigations carried out using noise elimination and source characterization methods such as frequency filtering and statistical pattern recognition but shows only sporadic attempts using ANN. This may probably be due to the complex nature of the problem involving investigation of a large number of influencing parameters, amount of effort and time to be invested, and facilities required and multi-disciplinary nature of the problem. Hence as stated in the foregoing, the need for such a study cannot be over emphasized. Thus, this thesis is an attempt addressing the issue of analysis and automation of complex sets of AE data such as AE signals mixed with in-flight noise thus forming the first step towards in-flight monitoring using AE. An ANN can in fact replace the traditional algorithmic approaches used in the past. ANN in general are model free estimators and derive their computational efficiency due to large connectivity, massive parallelism, non-linear analog response and learning capabilities. They are better suited than the conventional methods (statistical pattern recognition methods) due to their characteristics such as classification, pattern matching, learning, generalization, fault tolerance and distributed memory and their ability to process unstructured data sets which may be carrying incomplete information at times and hence chosen as the tool. Further, in the current context, the set of investigations undertaken were in the absence of sufficient a priori information and hence clustering of signals generated by AE sources through self-organizing maps is more appropriate. Thus, in the investigations carried out under the scope of this thesis, at first a hybrid network named "NAEDA" (Neural network for Acoustic Emission Data Analysis) using Kohonen self-organizing feature map (KSOM) and multi-layer perceptron (MLP) that learns on back propagation learning rule was specifically developed with innovative data processing techniques built into the network. However, for accurate pattern recognition, multi-layer back propagation NN needed to be trained with source and noise clusters as input data. Thus, in addition to optimizing the network architecture and training parameters, preprocessing of input data to the network and multi-class clustering and classification proved to be the corner stones in obtaining excellent identification accuracy. Next, in-flight noise environment of an aircraft was generated off line through carefully designed simulation experiments carried out in the laboratory (Ex: EMI, friction, fretting and other mechanical and hydraulic phenomena) based on the in-flight noise survey carried out by earlier investigators. From these experiments data was acquired and classified into their respective classes through MLP. Further, these noises were mixed together and clustered through KSOM and then classified into their respective clusters through MLP resulting in an accuracy of 95%- 100% Subsequently, to evaluate the utility of NAEDA for source classification and characterization, carbon fiber reinforced plastic (CFRP) specimens were subjected to spectrum loading simulating typical in-flight load and AE signals were acquired continuously up to a maximum of three designed lives and in some cases up to failure. Further, AE signals with similar characteristics were grouped into individual clusters through self-organizing map and labeled as belonging to appropriate failure modes, there by generating the class configuration. Then MLP was trained with this class information, which resulted in automatic identification and classification of failure modes with an accuracy of 95% - 100%. In addition, extraneous noise generated during the experiments was acquired and classified so as to evaluate the presence or absence of such data in the AE data acquired from the CFRP specimens. In the next stage, noise and signals were mixed together at random and were reclassified into their respective classes through supervised training of multi-layer back propagation NN. Initially only noise was discriminated from the AE signals from CFRP failure modes and subsequently both noise discrimination and failure mode identification and classification was carried out resulting in an accuracy of 95% - 100% in most of the cases. Further, extraneous signals mentioned above were classified which indicated the presence of such signals in the AE signals obtained from the CFRP specimen. Thus, having established the basis for noise identification and AE source classification and characterization, two specific examples were considered to evaluate the utility and efficiency of NAEDA. In the first, with the postulation that different basic failure modes in composites have unique AE signatures, the difference in damage generation and progression can be clearly characterized under different loading conditions. To examine this, static compression tests were conducted on a different set of CFRP specimens till failure with continuous AE monitoring and the resulting AE signals were classified through already trained NAEDA. The results obtained shows that the total number of signals obtained were very less when compared to fatigue tests and the specimens failed with hardly any damage growth. Further, NAEDA was able to discriminate the"noise and failure modes in CFRP specimen with the same degree of accuracy with which it has classified such signals obtained from fatigue tests. In the second example, with the same postulate of unique AE signatures for different failure modes, the differences in the complexion of the damage growth and progression should become clearly evident when one considers specimens with different lay up sequences. To examine this, the data was reclassified on the basis of differences in lay up sequences from specimens subjected to fatigue. The results obtained clearly confirmed the postulation. As can be seen from the summary of the work presented in the foregoing paragraphs, the investigations undertaken within the scope of this thesis involve elaborate experimentation, development of tools, acquisition of extensive data and analysis. Never the less, the results obtained were commensurate with the efforts and have been fruitful. Of the useful results that have been obtained, to state in specific, the first is, discrimination of simulated noise sources achieved with significant success but for some overlapping which is not of major concern as far as noises are concerned. Therefore they are grouped into required number of clusters so as to achieve better classification through supervised NN. This proved to be an innovative measure in supervised classification through back propagation NN. The second is the damage characterization in CFRP specimens, which involved imaginative data processing techniques that proved their worth in terms of optimization of various training parameters and resulted in accurate identification through clustering. Labeling of clusters is made possible by marking each signal starting from clustering to final classification through supervised neural network and is achieved through phenomenological correlation combined with ultrasonic imaging. Most rewarding of all is the identification of failure modes (AE signals) mixed in noise into their respective classes. This is a direct consequence of innovative data processing, multi-class clustering and flexibility of grouping various noise signals into suitable number of clusters. Thus, the results obtained and presented in this thesis on NN approach to AE signal analysis clearly establishes the fact that methods and procedures developed can automate detection and identification of failure modes in CFRP composites under hostile environment, which could lead to the development of an in-flight monitoring system.

Τα βασικά προβλήματα που εμφανίζονται κατά τον μη καταστροφικό έλεγχο με την μέθοδο της ακουστικής εκπομπής (ΑΕ) είναι η απομόνωση του θορύβου, η αξιόπιστη επεξεργασία και αναγνώριση των σημάτων από πραγματικές αστοχίες του υλικού, ο προσδιορισμός της θέσης της αστοχίας και ο χαρακτηρισμός του τύπου και της κρισιμότητας της βλάβης στο υλικό. Κατά την διάρκεια εκπόνησης της παρούσας διδακτορικής διατριβής δόθηκε ιδιαίτερη έμφαση στην μεθοδολογία εύρεσης της θέσης της πηγής ΑΕ δεδομένου ότι είναι γνωστοί οι χρόνοι άφιξης κάποιων χαρακτηριστικών των σημάτων που έχουν καταγραφεί στους αισθητήρες. Αναπτύχθηκαν ολοκληρωμένες μέθοδοι στις οποίες επεξεργάζονται τα σήματα των αισθητήρων για να προσδιοριστούν τα χαρακτηριστικά που θα αποτελέσουν την βάση για τον υπολογισμό της θέσης της πηγής. Έχοντας εξασφαλίσει την αξιόπιστη μέθοδο προσδιορισμού των χρόνων άφιξης ορισμένων χαρακτηριστικών των σημάτων αναπτύχθηκαν μέθοδοι οι οποίοι χρησιμοποιούν όσο το δυνατό περισσότερη πληροφορία για βελτίωση της ακρίβειας εκτίμησης και μικρότερες απαιτήσεις σε επιπλέον γνώση δεδομένων. / In non-destructive control, acoustic emission signals are used for reliable construction monitoring and damage recognition. In this thesis several methods for the acoustic emission (AE) source location are developed and evaluated. Automatic estimation of minimum number and optimal placement of sensors are derived at the minimum sum of localization errors at randomly positioning AE sources. A new method was proposed and evaluated for the estimation of optimum sensors position in problems of AE localization in spherically and cylindrical structures. The particular methodology can be easily adjusted in different structures, and is of paramount important in case where the sensors must be permanently placed in a structure. Six source location methods were developed using a parametric model for the AE signal, genetic algorithm and simulated annealing. The magnitude of the Fast Fourier Transform or the position of the maximum peak of cross correlation function are extracted from the AE signals acquired by multiple sensors positioning at arbitrary locations in a plain or a cylindrical structure. The AE source is estimated at the minimum of the error function between the signal or the features derived from the acoustic signal, and the signal or features estimated from the AE signal model. Moreover, a novel source location method based on radial basis function network is presented and evaluated. The problem of AE localization in plane surfaces and cylindrical surfaces are solved in a close-form using the arrival-time differences using three or more sensors. A close-form solution for Acoustic-Emission source location (AESL) and material constant G is presented and evaluated in simulation experiments using the Time-of-Arrival (TOA) of several events detected in arbitrary positioning sensors in 3d-space in dispersive media. The normalized distances and the constant G are derived from the TOA at four arbitrary selected sensors using the events propagation velocities in a reference material. The actual AE position is derived using the multidimensional scaling method using the complete set of sensors. In simulation experiments, the advantages of the proposed method are demonstrated. Overcoming the most important weakness of the proposed method, the use of only four sensors for the estimation of the parameter G, an algorithm for successive estimation of the AESL is developed using the complete set of TOAs.An extension of the AESL method is developed using a successive approximation algorithm assuming a minimum of two known propagation velocities for the recorded events. It is proved that the proposed algorithm converges to the local minimum of the optimization function. Under few restrictions the proposed algorithm can be used to estimate the AESL even in case where the propagation velocities for all events are unknown.

Στη συγκεκριμένη εργασία ασχολήθηκα με την εκτίμηση της συνάρτησης πυκνότητας πιθανότητας παραμέτρων που προέρχονται από σήματα πηγών ακουστικής εκπομπής που επεξεργάστηκα. Στο θεωρητικό κομμάτι το μεγαλύτερο ενδιαφέρον παρουσίασαν ο Μη Καταστροφικός Έλεγχος και η Ακουστική Εκπομπή, καθώς και οι εφαρμογές τους. Τα δεδομένα που επεξεργάστηκα χωρίζονται σε δύο κατηγορίες: σε εκείνα που μου δόθηκαν έτοιμα και σε εκείνα που λήφθηκαν μετά από μετρήσεις. Στην επεξεργασία των πειραματικών δεδομένων χρησιμοποιήθηκε ο αλγόριθμος πρόβλεψης-μεγιστοποίησης, τον οποίο μελέτησα θεωρητικά και με βάση τον οποίο εξάχθηκαν οι παράμετροι για κάθε σήμα. Έχοντας βρει τις παραμέτρους, προχώρησα στην ταξινόμηση των σημάτων σε κατηγορίες με βάση τη θεωρία της αναγνώρισης προτύπων. Στο τέλος της εργασίας παρατίθεται το παράρτημα με τα αναλυτικά αποτελέσματα, καθώς και η βιβλιογραφία που χρησιμοποίησα. / In this diploma paper the subject was the calculation of the probability density function of parameters which come from signals of sources of acoustic emission. In the theoritical part, the chapters with the greatest interest were Non Destructive Control and Acoustic Emission and their applications. The data which were processed are divided in two categories: those which were given without requiring any laboratory research and those which demanded laboratory research. The expectation-maximization algorithm, which was used in the process of the laboratory data, was the basis for the calculation of the parameters of each signal. Having calculated the parameters, the signals were classified in categories according to the theory of pattern recognition. In the end of the paper, the results and the bibliography which was used are presented.

Η συσσώρευση της βλάβης σε σύνθετα υλικά κεραμικής μήτρας που υπόκεινται σε μηχανική φόρτιση είναι ένα ζήτημα που δεν έχει απαντηθεί ικανοποιητικά μέχρι σήμερα. Η βασικότερη αντικειμενική δυσκολία στο πρόβλημα αυτό είναι ο τρόπος προσέγγισης και προσδιορισμού της βλάβης στα σύνθετα υλικά καθώς πρόκειται για πολυπαραμετρικό πρόβλημα. Επίσης τίθεται το ζήτημα του τρόπου παρακολούθησης της βλάβης. Οι μη καταστρεπτικοί έλεγχοι αποτελούν μια πολύ καλή επιλογή για την παρακολούθηση και τη μελέτη της εξέλιξης της βλάβης. Ο βασικός σκοπός της εργασίας αυτής είναι η μελέτη της εξέλιξης της βλάβης και των μηχανισμών αστοχίας στα υλικά αυτά με τη χρήση δύο διαφορετικών τεχνικών μη καταστροφικών ελέγχων (Aκουστική Eκπομπή AE και Aκουστο-Yπέρηχο AY) κατά τη διάρκεια μηχανικών δοκιμών, καθώς επίσης και η εύρεση ποσοτικών δεικτών ικανών να παρακολουθούν τα διάφορα επίπεδα βλάβης του υλικού. Ιδιαίτερη έμφαση δίνεται στις μεθοδολογίες επεξεργασίας των σημάτων που προκύπτουν από κάθε τεχνική. Στην κατεύθυνση αυτή δοκιμάστηκαν τρεις τύποι υλικών C/C με ενίσχυση τύπου υφάσματος. Η διαφοροποίηση από τύπο σε τύπο υλικού έγκειται στις διαφορετικές ιδιότητες της διεπιφάνειας που επέλεξε ο κατασκευαστής να προσδώσει χωρίς να διατεθούν περαιτέρω λεπτομέρειες (βιομηχανικό απόρρητο). Παράλληλα, από τα αποτελέσματα της εφαρμογής των διαφορετικών μεθοδολογιών επεξεργασίας των σημάτων που προέκυψαν από κάθε μη καταστροφική μέθοδο, επιχειρείται η εξαγωγή συμπερασμάτων σχετικά με τον τρόπο που οι διαφορετικές ποιότητες της διεπιφάνειας επηρεάζουν τους μηχανισμούς συσσώρευσης βλάβης στα υπό εξέταση υλικά. Αναλυτικότερα οι στόχοι που επιδιώχθησαν στο πλαίσιο της διατριβής είναι οι ακόλουθοι: • Εκτέλεση ειδικά επιλεγμένων μηχανικών δοκιμών σε τρία είδη συνθέτων υλικών C/C με ενίσχυση τύπου υφάσματος, που δίδουν τη δυνατότητα ανάπτυξης βλάβης πολλαπλών επιπέδων στη δομή του υλικού • Χρήση μη καταστροφικών μεθόδων όπως η ακουστική εκπομπή (AE) και οι ακουστο-υπέρηχοι (AU) για την παρακολούθηση της βλάβης που αναπτύσσεται και εξελίσσεται κατά τη διάρκεια των μηχανικών δοκιμών • Αναγνώριση των μηχανισμών αστοχίας και εξέλιξης της βλάβης έπειτα από επεξεργασία των σημάτων ΑΕ • Ανάπτυξη και εφαρμογή καινοτόμων τεχνικών επεξεργασίας για τα σήματα του ΑΥ βασιζόμενες στο μετασχηματισμό κυματιδίων • Ανάπτυξη ποσοτικών δεικτών για την παρακολούθηση της συσσώρευσης της βλάβης από την επεξεργασία των σημάτων του ΑΥ • Εξαγωγή συμπερασμάτων για τον τρόπο που η διαφοροποίηση στις τελικές ιδιότητες της διεπιφάνειας επηρεάζει τον τρόπο εξέλιξης και συσσώρευσης στα υπό εξέταση υλικά / The accumulation of damage in compοsite materials of ceramic matrix under mechanic loading is a topic that has not been answered satisfactorily up to today. The most basic objective difficulty in this problem is the way of approach and determination of damage in compοsite materials as it is a multiparametric problem. The question of the way of monitoring the damage is also rised. Non destructive testing constitutes of a very good choice for the monitoring and the study of the development of damage. The basic aim of this work is the study of development of damage and the failure mechanisms in composite materials with the use of two different techniques of not destructive techniques (Acoustic Emission AE and Acousto-Ultrasonic AU) during the mechanical testing, as well as the development of quantitative indicators capable of monitoring the various levels of damage of the material. Particular accent is given in the signal processing methodologies for the signals that result from each technique. To this direction three types of woven C/C composite material were tested. The differentiation in type of material lies in the different interfacial properties that the manufacturer selected without further details (industrial secrecy). At the same time, from the results of the application of the different signal processing methodologies that resulted from each non destructive method, conclusions are attempted to be exported with regard to the way that the different interfacial qualities influence the mechanisms of accumulation of damage. More analytically the objectives that were sought in the frame of this thesis are as follows: • Implementation of specifically selected mechanical tests in the three types of the woven composite C/C materials, that give the ability of development of multiple level damage in the structure of materials • Use of non destructive methods as the acoustic emission (AE) and the acousto-ultrasonics (AU) for the monitoring of damage that is developed during the mechanical tests • Recognition of the material’s failure mechanisms after the processing of AE signals • Development and application of innovative techniques for the processing of AU signals based on the wavelet transform • Development of quantitative indicators for the monitoring of damage accumulation from the processing of AU signals • Export of conclusions on the way that the differentiation in the final interfacial properties influences the way of development and accumulation of damage in the under review materials

Στα πλαίσια της διατριβής, πραγματοποιήθηκε μελέτη και ανάλυση σημάτων πηγών ακουστικής εκπομπής, προτάθηκαν νέες ολοκληρωμένες μεθοδολογίες βασισμένες σε συμβατικές αλλά και προχωρημένες τεχνικές επεξεργασίας και ανάλυσης δεδομένων για την εξαγωγή εκείνων των χαρακτηριστικών που διαχωρίζουν τα σήματα ακουστικής εκπομπής από τον περιβάλλοντα θόρυβο. Εξετάσθηκαν ποια χαρακτηριστικά γνωρίσματα (παράμετροι) περιέχουν σημαντικό τμήμα της “πληροφορίας” έτσι ώστε στη συνέχεια χρησιμοποιώντας προχωρημένες μεθόδους αναγνώρισης προτύπων να επιτευχθεί ανίχνευση και χαρακτηρισμός ρωγμοειδών αστοχιών σε θορυβώδεις συνθήκες αλλά και σε σύνθετες κατασκευές. Συνοπτικά στην παρούσα διατριβή προτάθηκε και αξιολογήθηκε μια νέα μέθοδος για την εκτίμηση της βέλτιστης τοποθέτησης αισθητήρων. Προτάθηκαν δύο μέθοδοι για τον εντοπισμό θέσης πηγής ακουστικής εκπομπής. Πραγματοποιήθηκε για πρώτη φορά εξαγωγή ενενήντα παραμέτρων, εκ’ των οποίων οι εξήντα επτά προσδιορίστηκαν μετά από επεξεργασία του σήματος στο πεδίο του χρόνου ενώ οι υπόλοιπες είκοσι τρεις με επεξεργασία του σήματος στο πεδίο της συχνότητας. H μείωση του αριθμού των παραμέτρων, χωρίς όμως να μειώνεται ταυτόχρονα και η αξιοπιστία του ταξινομητή, αποτελεί ένα μεγάλος μέρος έρευνας που πραγματοποιήθηκε στα πλαίσια εκπόνησης της παρούσας διατριβής. Προτάθηκαν και αξιολογήθηκαν τέσσερις μέθοδοι επιλογής παραμέτρων. Για πρώτη φορά κατασκευάστηκαν και αξιολογήθηκαν ολοκληρωμένα συστήματα ανίχνευσης αστοχιών τα οποία έχουν την δυνατότητα να ανιχνεύουν τη δημιουργία ρωγμών λόγω καταπόνησης σε καιρικές συνθήκες βροχής. Στο τελευταίο μέρος της διατριβής κατασκευάστηκε και αξιολογήθηκε ένα καινοτόμο σύστημα χαρακτηρισμού ρωγμοειδών γεγονότων για τις ενισχύσεις πλοίων, υπό προσομοιωμένες συνθήκες λειτουργίας του πλοίου. / The present PhD thesis dealt with the following subjects: best sensors position, source location, features extraction and features selection, crack detection on raining conditions, crack characterization in ship structures. A new method, for the estimation of the best sensors position that used for accurate acoustic emission source location on empty spherical surfaces, is presented. Two acoustic emission source location methods are presented and evaluated. In this thesis, an extensive set of ninety features (forty-one novel features) are extracted from acoustic emission signals, sixty-seven in the time domain and twenty-three by processing the signal in the frequency domain. The features are estimated for two time-frames the first has 1msec duration (typically the signal does not contain all the reflections from the material edges) and the second has 32msec of the normalized signal, which is not separated by its reflections, in small structures. To achieve robust performance both in accuracy and computational complexity of any classification method, it is necessary to pick up the most relevant features. Four features selection methods are proposed and evaluated. In outside constructions (e.g bridges, tanks, ships etc) real-life noises reduce significantly the capability of location and characterization acoustic emission sources. Among the most important types of noise is the rain, producing signal similar to crack. A completed system of detection crack on condition of rain is estimated. An efficient system for automatic and real-time characterization of crack events using a robust set of features to monitor crack events in ship structures is presented. In normal operation of ship, real-life noises (e.g engines, sea waves, weather conditions etc) reduce significantly the capability of location and characterization of crack events.

Nowadays, the need for three-dimensional miniaturized components is increasing in many areas, such as electronics, biomedics, aerospace and defence, etc. To support the demands, various micro-scale fabrication techniques have been further introduced and developed over the last decades, including micro-electric-mechanical technologies (MEMS and LIGA), laser ablation, and miniature machine tools (mMTs). Each of these techniques has its own benefits, however miniature machine tools are superior to any others in enabling three-dimensional complex geometry with high relative accuracy, and the capability of dealing with a wide range of mechanical materials. Thus, mMTs are emerging as a promising fabrication process. In this work, various researches have been carried out based on the mMTs. The thesis presents micro-machining, in particular, micro-milling force model and three relevant subsystems for miniature machine tools (mMTs), to enhance machining productivity/efficiency and dimensional accuracy of machined parts. The comprehensive force model that predicts micro-endmilling dynamics has been developed. Unlike conventional macro-machining, the cutting mechanism in micro-machining is complex with high level of non-linearity due to the combined effects of edge radius, size, and minimum chip thickness effect, etc., resulting in no chip formation when the chip thickness is below the minimum chip forming thickness. Instead, part of the work material deforms plastically under the edge of a tool and the rest of the material recovers elastically. The developed force model for micro-endmilling is effective to understand the micro-machining process. As a result, the micro-endmilling force model is helpful to improve the quality of machined parts. In addition, three relevant subsystems which deliver maximum machining productivity and efficiency are also introduced. Firstly, ultrasonic atomization-based cutting fluid application system is introduced. During machining, cutting fluid is required at the cutting zone for cooling and lubricating the cutting tool against the workpiece. Improper cutting fluid application leads to significantly increased tool wear, and which results in overall poor machined parts quality. For the micro-machining, conventional cooling methods using high pressure cutting fluid is not viable due to the potential damage and deflection of weak micro-cutting tools. The new atomization-based cutting fluids application technique has been proven to be quite effective in machinability due to its high level of cooling and lubricating. Secondly, an acoustic emission (AE)-based tool tip positioning method is introduced. Tool tip setting is one of the most important factors to be considered in the CNC machine tool. Since several tools with different geometries are employed during machining, overall dimensional accuracy of the machined parts are determined by accurate coordinates of each tool tip. In particular, tool setting is more important due to micro-scale involved in micro-machining. The newly developed system for tool tip positioning determines the accurate coordinates of the tool tip through simple and easy manipulation. At last, with the advance of the 3D micro-fabrication technologies, the machinable miniaturized components are getting complex in geometry, leading to increased demand on dimensional quality control. However, the system development for micro-scale parts is slow and difficult due to complicated detection devices, algorithm, and fabrication of a micro-probe. Consequently, the entire dimensional probing system tends to become bulky and expensive. A new AE-based probing system with a wire-based probe was developed to address this issue with reduced cost and size, and ease of application. / Graduate

The goal of this research is to investigate the fundamentals of fracturing processes in heterogeneous materials such as concrete using geophysical methods and dynamic micromechanical models. This work describes how different aspects of fracture formation in concrete can be investigated using a combination of Acoustic Emission (AE) techniques, ultrasonic wave velocity imaging, and high resolution Computed Tomography (CT). Fracture formation and evolution were studied during shear failure of large reinforced concrete beams and compressive failure of concrete samples. AE analysis includes studying complex spatial and temporal fracture development that precedes shear failure. Predominant microcrack mechanisms were analyzed at different stages of fracture formation. CT images were used to investigate the influence of concrete microstructure on fracture topography. Combined AE and CT damage evaluation techniques revealed different aspects of fracture development, thus expanding our understanding of AE events and their mechanisms. These images show how aggregate particles influence fracture nucleation and development. An emphasis has been placed on the role of coarse aggregates during the interlocking of fracture surfaces at transferring shear stresses. Ultrasonic wave velocity and AE techniques have been applied to uniaxial compression tests of concrete with various aggregate sizes and strengths similar to that of the concrete beams. AE parameters, p-wave velocities, and stress-strain data have been analyzed concurrently to image damage evolution under compression. Influence of material composition on microcracking and material state changes during loading has been investigated in detail. The results of compressive tests were used as building blocks for developing realistic micromechanical numerical models of concrete. The models were designed using a distinct element code, where material is modelled through the combination of bonded particles. A number of procedures were developed to transfer the exact microstructure of material incorporating its visual representation into the model. The models’ behaviour has been verified against experimental data. It was shown that these models exhibit realistic micromechanical behaviour. The results of the experimental investigation of concrete fracturing were expanded by modelling more cases with aggregate size and strength variations. It was shown that geophysical imaging techniques, along with advanced micromechanical numerical modelling, can help us understand damage formation and evolution.