Fault detection, diagnosis and active fault tolerant control for a satellite attitude control system

Modern control systems are becoming more and more complex and control algorithms more and more sophisticated. Consequently, Fault Detection and Diagnosis (FDD) and Fault Tolerant Control (FTC) have gained central importance over the past decades, due to the increasing requirements of availability, cost efficiency, reliability and operating safety. This thesis deals with the FDD and FTC problems in a spacecraft Attitude Determination and Control System (ADCS). Firstly, the detailed nonlinear models of the spacecraft attitude dynamics and kinematics are described, along with the dynamic models of the actuators and main external disturbance sources. The considered ADCS is composed of an array of four redundant reaction wheels. A set of sensors provides satellite angular velocity, attitude and flywheel spin rate information. Then, general overviews of the Fault Detection and Isolation (FDI), Fault Estimation (FE) and Fault Tolerant Control (FTC) problems are presented, and the design and implementation of a novel diagnosis system is described. The system consists of a FDI module composed of properly organized model-based residual filters, exploiting the available input and output information for the detection and localization of an occurred fault. A proper fault mapping procedure and the nonlinear geometric approach are exploited to design residual filters explicitly decoupled from the external aerodynamic disturbance and sensitive to specific sets of faults. The subsequent use of suitable adaptive FE algorithms, based on the exploitation of radial basis function neural networks, allows to obtain accurate fault estimations. Finally, this estimation is actively exploited in a FTC scheme to achieve a suitable fault accommodation and guarantee the desired control performances. A standard sliding mode controller is implemented for attitude stabilization and control. Several simulation results are given to highlight the performances of the overall designed system in case of different types of faults affecting the ADCS actuators and sensors.

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).

Fault detection in rotating machines by vibration signal processing techniques

Machines with moving parts give rise to vibrations and consequently noise. The setting up and the status of each machine yield to a peculiar vibration signature. Therefore, a change in the vibration signature, due to a change in the machine state, can be used to detect incipient defects before they become critical. This is the goal of condition monitoring, in which the informations obtained from a machine signature are used in order to detect faults at an early stage. There are a large number of signal processing techniques that can be used in order to extract interesting information from a measured vibration signal. This study seeks to detect rotating machine defects using a range of techniques including synchronous time averaging, Hilbert transform-based demodulation, continuous wavelet transform, Wigner-Ville distribution and spectral correlation density function. The detection and the diagnostic capability of these techniques are discussed and compared on the basis of experimental results concerning gear tooth faults, i.e. fatigue crack at the tooth root and tooth spalls of different sizes, as well as assembly faults in diesel engine. Moreover, the sensitivity to fault severity is assessed by the application of these signal processing techniques to gear tooth faults of different sizes.

Radio frequency communication and fault detection for railway signalling

The continuous and swift progression of both wireless and wired communication technologies in today's world owes its success to the foundational systems established earlier. These systems serve as the building blocks that enable the enhancement of services to cater to evolving requirements. Studying the vulnerabilities of previously designed systems and their current usage leads to the development of new communication technologies replacing the old ones such as GSM-R in the railway field. The current industrial research has a specific focus on finding an appropriate telecommunication solution for railway communications that will replace the GSM-R standard which will be switched off in the next years. Various standardization organizations are currently exploring and designing a radiofrequency technology based standard solution to serve railway communications in the form of FRMCS (Future Railway Mobile Communication System) to substitute the current GSM-R. Bearing on this topic, the primary strategic objective of the research is to assess the feasibility to leverage on the current public network technologies such as LTE to cater to mission and safety critical communication for low density lines. The research aims to identify the constraints, define a service level agreement with telecom operators, and establish the necessary implementations to make the system as reliable as possible over an open and public network, while considering safety and cybersecurity aspects. The LTE infrastructure would be utilized to transmit the vital data for the communication of a railway system and to gather and transmit all the field measurements to the control room for maintenance purposes. Given the significance of maintenance activities in the railway sector, the ongoing research includes the implementation of a machine learning algorithm to detect railway equipment faults, reducing time and human analysis errors due to the large volume of measurements from the field.

Detection and localization of GLUTs in spermatozoa from different domestic species

Sperm cells need hexoses as a substrate for their function, for both the maintenance of membrane homeostasis and the movement of the tail. These cells have a peculiar metabolism that has not yet been fully understood, but it is clear that they obtain energy from hexoses through glycolisis and/or oxidative phosphorylation. Spermatozoa are in contact with different external environments, beginning from the testicular and epididymal fluid, passing to the seminal plasma and finally to the female genital tract fluids; in addition, with the spread of reproductive biotechnologies, sperm cells are diluted and stored in various media, containing different energetic substrates. To utilize these energetic sources, sperm cells, as other eukaryotic cells, have a well-constructed protein system, that is mainly represented by the GLUT family proteins. These transporters have a membrane-spanning α-helix structure and work as an enzymatic pump that permit a fast gradient dependent passage of sugar molecules through the lipidic bilayer of sperm membrane. Many GLUTs have been studied in man, bull and rat spermatozoa; the presence of some GLUTs has been also demonstrated in boar and dog spermatozoa. The aims of the present study were - to determine the presence of GLUTs 1, 2, 3, 4 and 5 in boar, horse, dog and donkey spermatozoa and to describe their localization; - to study eventual changes in GLUTs location after capacitation and acrosome reaction in boar, stallion and dog spermatozoa; - to determine possible changes in GLUTs localization after capacitation induced by insulin and IGF stimulation in boar spermatozoa; - to evaluate changes in GLUTs localization after flow-cytometric sex sorting in boar sperm cells. GLUTs 1, 2, 3 and 5 presence and localization have been demonstrated in boar, stallion, dog and donkey spermatozoa by western blotting and immunofluorescence analysis; a relocation in GLUTs after capacitation has been observed only in dog sperm cells, while no changes have been observed in the other species examined. As for boar, the stimulation of the capacitation with insulin and IGF didn’t cause any change in GLUTs localization, as well as for the flow cytometric sorting procedure. In conclusion, this study confirms the presence of GLUTs 1, 2 ,3 and 5 in boar, dog, stallion and donkey spermatozoa, while GLUT 4 seems to be absent, as a confirmation of other studies. Only in dog sperm cells capacitating conditions induce a change in GLUTs distribution, even if the physiological role of these changes should be deepened.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

RICORDACI: Research on the Conservation, Restoration and Diagnosis of Cinematographic Films

This thesis is the result of the RICORDACI project, a three-year European-funded initiative involving the collaboration between the University of Bologna and the restoration laboratory of the Cineteca di Bologna, L'immagine Ritrovata, which aimed to develop innovative solutions and technologies for the preservation of cinematographic film heritage. In particular, this thesis presents new analytical methodologies to exploit two types of portable miniaturized Near Infrared spectrometers working in Diffuse Reflectance over the Short Wave Infrared (SWIR) range, to study the near infrared (NIR) spectral behavior of film base materials for an accurate, non-invasive and fast characterization of the polymer type; and for films with cellulose acetate supports, they can be employed as a diagnostic tool for monitoring the Degree of substitution (DS) affected by the loss of acetyl groups. The proposed methods offer non-invasive, fast, inexpensive and simple alternatives for the characterization and diagnosis of film bases to help the strategic planning and decision-making regarding storage, digitalization and intervention of film collections. Secondly, the thesis includes the evaluation of new green cleaning systems and solvents for the effective, fast and innocuous removal of undesired substances from degraded cinematographic films bases; these tests compared the efficiency of traditional systems and solvents against the new proposals. Firstly, the use of Deep Eutectic Solvent formulations for removing softened gelatin residues from cellulose nitrate bases; and secondly, the employment of green volatile solvents with different application methods, including the use of new electrospun nylon mats, for avoiding the dangerous use of friction for the removal of Triphenyl Phosphate blooms from the surface of cellulose acetate bases. The results obtained will help improving the efficiency of the interventions needed before the digitalization of historical cinematographic films and will pave the way for further investigation on the use of green solvents for cleaning polymeric heritage objects.

Context detection and abstraction in smart environments

Context-aware computing is currently considered the most promising approach to overcome information overload and to speed up access to relevant information and services. Context-awareness may be derived from many sources, including user profile and preferences, network information, sensor analysis; usually context-awareness relies on the ability of computing devices to interact with the physical world, i.e. with the natural and artificial objects hosted within the "environment”. Ideally, context-aware applications should not be intrusive and should be able to react according to user’s context, with minimum user effort. Context is an application dependent multidimensional space and the location is an important part of it since the very beginning. Location can be used to guide applications, in providing information or functions that are most appropriate for a specific position. Hence location systems play a crucial role. There are several technologies and systems for computing location to a vary degree of accuracy and tailored for specific space model, i.e. indoors or outdoors, structured spaces or unstructured spaces. The research challenge faced by this thesis is related to pedestrian positioning in heterogeneous environments. Particularly, the focus will be on pedestrian identification, localization, orientation and activity recognition. This research was mainly carried out within the “mobile and ambient systems” workgroup of EPOCH, a 6FP NoE on the application of ICT to Cultural Heritage. Therefore applications in Cultural Heritage sites were the main target of the context-aware services discussed. Cultural Heritage sites are considered significant test-beds in Context-aware computing for many reasons. For example building a smart environment in museums or in protected sites is a challenging task, because localization and tracking are usually based on technologies that are difficult to hide or harmonize within the environment. Therefore it is expected that the experience made with this research may be useful also in domains other than Cultural Heritage. This work presents three different approaches to the pedestrian identification, positioning and tracking: Pedestrian navigation by means of a wearable inertial sensing platform assisted by the vision based tracking system for initial settings an real-time calibration; Pedestrian navigation by means of a wearable inertial sensing platform augmented with GPS measurements; Pedestrian identification and tracking, combining the vision based tracking system with WiFi localization. The proposed localization systems have been mainly used to enhance Cultural Heritage applications in providing information and services depending on the user’s actual context, in particular depending on the user’s location.

Fault delineation and stress orientations from the analysis of background, low magnitude seismicity in Southern Apennines (Italy)

The aim of this work was to show that refined analyses of background, low magnitude seismicity allow to delineate the main active faults and to accurately estimate the directions of the regional tectonic stress that characterize the Southern Apennines (Italy), a structurally complex area with high seismic potential. Thanks the presence in the area of an integrated dense and wide dynamic network, was possible to analyzed an high quality microearthquake data-set consisting of 1312 events that occurred from August 2005 to April 2011 by integrating the data recorded at 42 seismic stations of various networks. The refined seismicity location and focal mechanisms well delineate a system of NW-SE striking normal faults along the Apenninic chain and an approximately E-W oriented, strike-slip fault, transversely cutting the belt. The seismicity along the chain does not occur on a single fault but in a volume, delimited by the faults activated during the 1980 Irpinia M 6.9 earthquake, on sub-parallel predominant normal faults. Results show that the recent low magnitude earthquakes belongs to the background seismicity and they are likely generated along the major fault segments activated during the most recent earthquakes, suggesting that they are still active today thirty years after the mainshock occurrences. In this sense, this study gives a new perspective to the application of the high quality records of low magnitude background seismicity for the identification and characterization of active fault systems. The analysis of the stress tensor inversion provides two equivalent models to explain the microearthquake generation along both the NW-SE striking normal faults and the E- W oriented fault with a dominant dextral strike-slip motion, but having different geological interpretations. We suggest that the NW-SE-striking Africa-Eurasia convergence acts in the background of all these structures, playing a primary and unifying role in the seismotectonics of the whole region.

Detection and Modeling of Boundary Layer Height

This thesis tackles the problem of the automated detection of the atmospheric boundary layer (BL) height, h, from aerosol lidar/ceilometer observations. A new method, the Bayesian Selective Method (BSM), is presented. It implements a Bayesian statistical inference procedure which combines in an statistically optimal way different sources of information. Firstly atmospheric stratification boundaries are located from discontinuities in the ceilometer back-scattered signal. The BSM then identifies the discontinuity edge that has the highest probability to effectively mark the BL height. Information from the contemporaneus physical boundary layer model simulations and a climatological dataset of BL height evolution are combined in the assimilation framework to assist this choice. The BSM algorithm has been tested for four months of continuous ceilometer measurements collected during the BASE:ALFA project and is shown to realistically diagnose the BL depth evolution in many different weather conditions. Then the BASE:ALFA dataset is used to investigate the boundary layer structure in stable conditions. Functions from the Obukhov similarity theory are used as regression curves to fit observed velocity and temperature profiles in the lower half of the stable boundary layer. Surface fluxes of heat and momentum are best-fitting parameters in this exercise and are compared with what measured by a sonic anemometer. The comparison shows remarkable discrepancies, more evident in cases for which the bulk Richardson number turns out to be quite large. This analysis supports earlier results, that surface turbulent fluxes are not the appropriate scaling parameters for profiles of mean quantities in very stable conditions. One of the practical consequences is that boundary layer height diagnostic formulations which mainly rely on surface fluxes are in disagreement to what obtained by inspecting co-located radiosounding profiles.

Evaluation of Microbial Contamination in Bivalve Mollusks: Epidemiology and Diagnosis

Shellfish are filter-feeding organisms that can accumulate many bacteria and viruses. Considering that depuration procedures are not effective in removal of certain microorganisms, shellfish-borne diseases are frequent in many parts of the world, and their control must rely primarily on investigation of prevalence of human pathogens in shellfish and water environment. However, the diffusion of enteric viruses and Vibrio bacteria is not known in many geographical areas, for example in Sardinia, Italy. A survey aimed at investigating the prevalence of Norovirus (NoV), hepatitis A virus (HAV), V. parahaemolyticus, V. cholerae and V. vulnificus was carried out, analyzing both local and imported purified, non-purified and retail shellfish from North Italy and Sardinia. Shellfish from both areas were found contaminated by NoVs, HAV and Vibrio, including retail and purified animals. Molecular analysis evidenced different NoV genogroups and genotypes, including bovine NoVs, as well as pathogenic Vibrio strains, underlining the risk for shellfish consumers. However, also other approaches are needed to control the diffusion of shellfish-borne diseases. It was originally thought that enteric viruses are passively accumulated by shellfish. Recently, it was proven that NoVs bind to specific carbohydrate ligands in oysters, and various NoV strains are characterized by a different bioaccumulation pattern. To deepen the knowledge on this argument, a study was carried out, analyzing bioaccumulation of up to 8 different NoV strains in four different species of shellfish. Different bioaccumulation patterns were observed for each shellfish species and NoV strain used, potentially important in setting up effective shellfish purification protocols. Finally, a novel study of evaluation of viral contamination in shellfish from the French Atlantic coast was carried out following the passage of Xynthia tempest over Western Europe which caused massive destruction. Different enteric viruses were found over a one month period, evidencing the potential of these events of contaminating shellfish.

Radar based improvements and diagnosis of the convective capabilities of the cosmo-2 model

In the last few years the resolution of numerical weather prediction (nwp) became higher and higher with the progresses of technology and knowledge. As a consequence, a great number of initial data became fundamental for a correct initialization of the models. The potential of radar observations has long been recognized for improving the initial conditions of high-resolution nwp models, while operational application becomes more frequent. The fact that many nwp centres have recently taken into operations convection-permitting forecast models, many of which assimilate radar data, emphasizes the need for an approach to providing quality information which is needed in order to avoid that radar errors degrade the model's initial conditions and, therefore, its forecasts. Environmental risks can can be related with various causes: meteorological, seismical, hydrological/hydraulic. Flash floods have horizontal dimension of 1-20 Km and can be inserted in mesoscale gamma subscale, this scale can be modeled only with nwp model with the highest resolution as the COSMO-2 model. One of the problems of modeling extreme convective events is related with the atmospheric initial conditions, in fact the scale dimension for the assimilation of atmospheric condition in an high resolution model is about 10 Km, a value too high for a correct representation of convection initial conditions. Assimilation of radar data with his resolution of about of Km every 5 or 10 minutes can be a solution for this problem. In this contribution a pragmatic and empirical approach to deriving a radar data quality description is proposed to be used in radar data assimilation and more specifically for the latent heat nudging (lhn) scheme. Later the the nvective capabilities of the cosmo-2 model are investigated through some case studies. Finally, this work shows some preliminary experiments of coupling of a high resolution meteorological model with an Hydrological one.

Kinematic models of interseismic deformation from inversion of GPS and InSAR measurements to estimate fault parameters and coupling degree

We have used kinematic models in two Italian regions to reproduce surface interseismic velocities obtained from InSAR and GPS measurements. We have considered a Block modeling, BM, approach to evaluate which fault system is actively accommodating the occurring deformation in both considered areas. We have performed a study for the Umbria-Marche Apennines, obtaining that the tectonic extension observed by GPS measurements is explained by the active contribution of at least two fault systems, one of which is the Alto Tiberina fault, ATF. We have estimated also the interseismic coupling distribution for the ATF using a 3D surface and the result shows an interesting correlation between the microseismicity and the uncoupled fault portions. The second area analyzed concerns the Gargano promontory for which we have used jointly the available InSAR and GPS velocities. Firstly we have attached the two datasets to the same terrestrial reference frame and then using a simple dislocation approach, we have estimated the best fault parameters reproducing the available data, providing a solution corresponding to the Mattinata fault. Subsequently we have considered within a BM analysis both GPS and InSAR datasets in order to evaluate if the Mattinata fault may accommodate the deformation occurring in the central Adriatic due to the relative motion between the North-Adriatic and South-Adriatic plates. We obtain that the deformation occurring in that region should be accommodated by more that one fault system, that is however difficult to detect since the poor coverage of geodetic measurement offshore of the Gargano promontory. Finally we have performed also the estimate of the interseismic coupling distribution for the Mattinata fault, obtaining a shallow coupling pattern. Both of coupling distributions found using the BM approach have been tested by means of resolution checkerboard tests and they demonstrate that the coupling patterns depend on the geodetic data positions.

Detection and molecular characterization of viruses infecting Actinidia spp.

Kiwifruit (genus Actinidia) is an important horticultural crop grown in the temperate regions. The four world’s largest producers are China, Italy, New Zealand and Chile. More than 50 species are recognized in the genus but the principal species in cultivation are A. deliciosa and A. chinensis. In Italy, as well as in many other countries, the kiwifruit crop has been considered to be relatively disease free and then no certification system for this species has been developed to regulate importation of propagation plant material in the European Union. During the last years a number of fungal and bacterial diseases have been recorded such as Botrytis cinerea and Pseudomonas syringae pv. actinidiae. Since 2003, several viruses and virus-like diseases have been identified and more recent studies demonstrated that Actinidia spp can be infected by a wide range of viral agents. In collaboration with the University of Auckland we have been detected thirteen different viral species on kiwifruit plants. During the three years of my PhD I worked on the characterization of Cucumber mosaic virus (CMV) and Pelargonium zonate spot virus (PZSV). The determination of causal agents has been based on host range, symptom expression in the test plant species and morphological properties of the virus particles using transmission electron microscopy (TEM) and using specific oligonucleotide primers in reverse transcription-polymerase chain reaction (RT-PCR). Both viruses induced several symptoms on kiwifruit plants. Moreover with new technologies such as high-throughput sequencing we detected additional viruses, a new member of the family Closteroviridae and a new member of the family Totiviridae. Taking together all results of my studies it is clear that, in order to minimize the risk of serious viral disease in kiwifruit, it is vital to use virus-free propagation material in order to prevent the spread of these viruses.

Synthesis of constrained peptidomimetics for therapeutic, diagnostic and theranostic applications

This thesis work deals, principally, with the development of different chemical protocols ranging from environmental sustainability peptide synthesis to asymmetric synthesis of modified tryptophans to a series of straightforward procedures for constraining peptide backbones without the need for a pre-formed scaffold. Much efforts have been dedicated to the structural analysis in a biomimetic environment, fundamental for predicting the in vivo conformation of compounds, as well as for giving a rationale to the experimentally determined bioactivity. The conformational analyses in solution has been done mostly by NMR (2D gCosy, Roesy, VT, titration experiments, molecular dynamics, etc.), FT-IR and ECD spectroscopy. As a practical application, 3D rigid scaffolds have been employed for the synthesis of biological active compounds based on peptidomimetic and retro-mimetic structures. These mimics have been investigated for their potential as antiflammatory agents and actually the results obtained are very promising. Moreover, the synthesis of Amo ring permitted the development of an alternative high effective synthetic pathway for obtaining Linezolid antibiotic. The final section is, instead, dedicated to the construction of a new biosensor based on zeolite L SAMs functionalized with the integrin ligand c[RGDfK], that has showed high efficiency for the selective detection of tumor cells. Such kind of sensor could, in fact, enable the convenient, non-invasive detection and diagnosis of cancer in early stages, from a few drops of a patient's blood or other biological fluids. In conclusion, the researches described herein demonstrate that the peptidomimetic approach to 3D definite structures, allows unambiguous investigation of the structure-activity relationships, giving an access to a wide range bioactive compounds of pharmaceutical interest to use not only as potential drugs but also for diagnostic and theranostic applications.