Acquisition of Vibration Signals for Predictive Maintenance: a Practical Case

As predictive maintenance becomes more and more relevant in industrial environment, the possible range of applications for this maintenance strategy grows. The progresses in components technology and their reduction in price, together with the late years' advances in machine learning and in computational power, are making the implementation of predictive maintenance possible in plants where it would have previously been unreasonably costly. This is leading major pharmaceutical industries to explore the possibility of the application of condition monitoring systems on progressively less and less critical equipment. The focus of this thesis is on the implementation of a system to gather vibrational data from the motors installed in a pre-existing machine using off-the-shelf components. The final goal for the system is to provide the necessary vibration data, in the form of frequency spectra, to a machine learning system developed by IMA Digital, which will be leveraging such data to predict possible upcoming faults and to give the final client all the information necessary to plan maintenance activity according to the estimated machine condition.

Simulation of visible light communications in vehicular networks

The rapid development in the field of lighting and illumination allows low energy consumption and a rapid growth in the use, and development of solid-state sources. As the efficiency of these devices increases and their cost decreases there are predictions that they will become the dominant source for general illumination in the short term. The objective of this thesis is to study, through extensive simulations in realistic scenarios, the feasibility and exploitation of visible light communication (VLC) for vehicular ad hoc networks (VANETs) applications. A brief introduction will introduce the new scenario of smart cities in which visible light communication will become a fundamental enabling technology for the future communication systems. Specifically, this thesis focus on the acquisition of several, frequent, and small data packets from vehicles, exploited as sensors of the environment. The use of vehicles as sensors is a new paradigm to enable an efficient environment monitoring and an improved traffic management. In most cases, the sensed information must be collected at a remote control centre and one of the most challenging aspects is the uplink acquisition of data from vehicles. My thesis discusses the opportunity to take advantage of short range vehicle-to-vehicle (V2V) and vehicle-to-roadside (V2R) communications to offload the cellular networks. More specifically, it discusses the system design and assesses the obtainable cellular resource saving, by considering the impact of the percentage of vehicles equipped with short range communication devices, of the number of deployed road side units, and of the adopted routing protocol. When short range communications are concerned, WAVE/IEEE 802.11p is considered as standard for VANETs. Its use together with VLC will be considered in urban vehicular scenarios to let vehicles communicate without involving the cellular network. The study is conducted by simulation, considering both a simulation platform (SHINE, simulation platform for heterogeneous interworking networks) developed within the Wireless communication Laboratory (Wilab) of the University of Bologna and CNR, and network simulator (NS3). trying to realistically represent all the wireless network communication aspects. Specifically, simulation of vehicular system was performed and introduced in ns-3, creating a new module for the simulator. This module will help to study VLC applications in VANETs. Final observations would enhance and encourage potential research in the area and optimize performance of VLC systems applications in the future.

Analysis of the Variability of Carbonate System Parameters in the North-East Atlantic.

The purpose of this thesis is to analyse the spatial and temporal variability of the aragonite saturation state (ΩAR), commonly used as an indicator of ocean acidification, in the North-East Atlantic. When the aragonite saturation state decreases below a certain threshold, ΩAR <1, calcifying organisms (i.e. molluscs, pteropods, foraminifera, crabs, etc.) are subject to dissolution of shells and aragonite structures. This objective agrees with the challenge 'Ocean, climate change and acidification' of the EU COST Ocean Governance for Sustainability project, which aims to combine the information collected on the state of health of the oceans. Two open-sources data products, EMODnet and GLODAPv2, have been integrated and analysed for the first time in the North-East Atlantic region. The integrated dataset contains 1038 ΩAR vertical profiles whose time distribution spans from 1970 to 2014. The ΩAR has been computed from CO2SYS software considering different combinations of input parameters, pH, Total Alkalinity (TAlk) and Dissolved Inorganic Carbon (DIC), associated with Temperature, Salinity and Pressure at in situ conditions. A sensitivity analysis has been performed to better understand the data consistency of ΩAR computed from the different combinations of pH, Talk and DIC and to verify the difference among observed TAlk and DIC parameters and their output values from the CO2SYS tool. Maps of ΩAR have been computed with the best data coverage obtained from the two datasets, at different levels of depth in the area of investigation and they have been compared to the work of Jiang et al. (2015). The results are consistent and show similar horizontal and vertical patterns. The study highlights some aragonite undersaturated values (ΩAR <1) below 500 meters depth, suggesting a potential effect of acidification in the considered time period. This thesis aims to be a preliminary work for future studies that will be able to design the ΩAR variability on a decadal distribution based on the extended time-series acquired in this work.

Robotics and neurodevelopmental disorder: design and implementation of a system of engagement metrics in human-robot interactions.

In the recent decades, robotics has become firmly embedded in areas such as education, teaching, medicine, psychology and many others. We focus here on social robotics; social robots are designed to interact with people in a natural and interpersonal way, often to achieve positive results in different applications. To interact and cooperate with humans in their daily-life activities, robots should exhibit human-like intelligence. The rapid expansion of social robotics and the existence of various kinds of robots on the market have allowed research groups to carry out multiple experiments. The experiments carried out have led to the collections of various kinds of data, which can be used or processed for psychological studies, and studies in other fields. However, there are no tools available in which data can be stored, processed and shared with other research groups. This thesis proposes the design and implementation of visual tool for organizing dataflows in Human Robot Interaction (HRI).

Assimilation of data from conventional and non conventional networks through a LETKF scheme in the COSMO model

The present work studies a km-scale data assimilation scheme based on a LETKF developed for the COSMO model. The aim is to evaluate the impact of the assimilation of two different types of data: temperature, humidity, pressure and wind data from conventional networks (SYNOP, TEMP, AIREP reports) and 3d reflectivity from radar volume. A 3-hourly continuous assimilation cycle has been implemented over an Italian domain, based on a 20 member ensemble, with boundary conditions provided from ECMWF ENS. Three different experiments have been run for evaluating the performance of the assimilation on one week in October 2014 during which Genova flood and Parma flood took place: a control run of the data assimilation cycle with assimilation of data from conventional networks only, a second run in which the SPPT scheme is activated into the COSMO model, a third run in which also reflectivity volumes from meteorological radar are assimilated. Objective evaluation of the experiments has been carried out both on case studies and on the entire week: check of the analysis increments, computing the Desroziers statistics for SYNOP, TEMP, AIREP and RADAR, over the Italian domain, verification of the analyses against data not assimilated (temperature at the lowest model level objectively verified against SYNOP data), and objective verification of the deterministic forecasts initialised with the KENDA analyses for each of the three experiments.

Cryogenic optical readout for a liquid argon neutrino imaging detector

The GRAIN detector is part of the SAND Near Detector of the DUNE neutrino experiment. A new imaging technique involving the collection of the scintillation light will be used in order to reconstruct images of particle tracks in the GRAIN detector. Silicon photomultiplier (SiPM) matrices will be used as photosensors for collecting the scintillation light emitted at 127 nm by liquid argon. The readout of SiPM matrices inside the liquid argon requires the use of a multi-channel mixed-signal ASIC, while the back-end electronics will be implemented in FPGAs outside the cryogenic environment. The ALCOR (A Low-power Circuit for Optical sensor Readout) ASIC, developed by Torino division of INFN, is under study, since it is optimized to readout SiPMs at cryogenic temperatures. I took part in the realization of a demonstrator of the imaging system, which consists of a SiPM matrix connected to a custom circuit board, on which an ALCOR ASIC is mounted. The board communicates with an FPGA. The first step of the present project that I have accomplished was the development of an emulator for the ALCOR ASIC. This emulator allowed me to verify the correct functioning of the initial firmware before the real ASIC itself was available. I programmed the emulator using VHDL and I also developed test benches in order to test its correct working. Furthermore, I developed portions of the DAQ software, which I used for the acquisition of data and the slow control of the ASICs. In addition, I made some parts of the DAQ firmware for the FPGAs. Finally, I tested the complete SiPMs readout system at both room and cryogenic temperature in order to ensure its full functionality.