9 resultados para condition monitoring system

em AMS Tesi di Laurea - Alm@DL - Università di Bologna


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Industrial companies, particularly those with induction motors and gearboxes as integral components of their systems, are utilizing Condition Monitoring (CM) systems more frequently in order to discover the need for maintenance in advance, as traditional maintenance only performs tasks when a failure has been identified. Utilizing a CM system is essential to boost productivity and minimize long-term failures that result in financial loss. The more exact and practical the CM system, the better the data analysis, which adds to a more precise maintenance forecast. This thesis project is a cooperation with PEI Vibration Monitoring s.r.l. to design and construct a low-cost vibrational condition monitoring system to check the health of induction motors and gearboxes automatically. Moreover, according to the company's request, such a system should have specs comparable to NI 9234, one of the company's standard Data Acquisition (DAQ) boards, but at a significantly cheaper price. Additionally, PEI VM Company has supplied all hardware and electronic components. The suggested CM system is capable of highprecision autonomous monitoring of induction motors and gearboxes, and it consists of a Raspberry Pi 3B and MCC 172 DAQ board.

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EUMETSAT (www.eumetsat.int) e’ l’agenzia europea per operazioni su satelliti per monitorare clima, meteo e ambiente terrestre. Dal centro operativo situato a Darmstadt (Germania), si controllano satelliti meteorologici su orbite geostazionarie e polari che raccolgono dati per l’osservazione dell’atmosfera, degli oceani e della superficie terrestre per un servizio continuo di 24/7. Un sistema di monitoraggio centralizzato per programmi diversi all’interno dell’ambiente operazionale di EUMETSAT, e’ dato da GEMS (Generic Event Monitoring System). Il software garantisce il controllo di diverse piattaforme, cross-monitoring di diverse sezioni operative, ed ha le caratteristiche per potere essere esteso a future missioni. L’attuale versione della GEMS MMI (Multi Media Interface), v. 3.6, utilizza standard Java Server Pages (JSP) e fa uso pesante di codici Java; utilizza inoltre files ASCII per filtri e display dei dati. Conseguenza diretta e’ ad esempio, il fatto che le informazioni non sono automaticamente aggiornate, ma hanno bisogno di ricaricare la pagina. Ulteriori inputs per una nuova versione della GEMS MMI vengono da diversi comportamenti anomali riportati durante l’uso quotidiano del software. La tesi si concentra sulla definizione di nuovi requisiti per una nuova versione della GEMS MMI (v. 4.4) da parte della divisione ingegneristica e di manutenzione di operazioni di EUMETSAT. Per le attivita’ di supporto, i test sono stati condotti presso Solenix. Il nuovo software permettera’ una migliore applicazione web, con tempi di risposta piu’ rapidi, aggiornamento delle informazioni automatico, utilizzo totale del database di GEMS e le capacita’ di filtri, insieme ad applicazioni per telefoni cellulari per il supporto delle attivita’ di reperibilita’. La nuova versione di GEMS avra’ una nuova Graphical User Interface (GUI) che utilizza tecnologie moderne. Per un ambiente di operazioni come e’ quello di EUMETSAT, dove l’affidabilita’ delle tecnologie e la longevita’ dell’approccio scelto sono di vitale importanza, non tutti gli attuali strumenti a disposizione sono adatti e hanno bisogno di essere migliorati. Allo stesso tempo, un’ interfaccia moderna, in termini di visual design, interattivita’ e funzionalita’, e’ importante per la nuova GEMS MMI.

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The dissertation starts by providing a description of the phenomena related to the increasing importance recently acquired by satellite applications. The spread of such technology comes with implications, such as an increase in maintenance cost, from which derives the interest in developing advanced techniques that favor an augmented autonomy of spacecrafts in health monitoring. Machine learning techniques are widely employed to lay a foundation for effective systems specialized in fault detection by examining telemetry data. Telemetry consists of a considerable amount of information; therefore, the adopted algorithms must be able to handle multivariate data while facing the limitations imposed by on-board hardware features. In the framework of outlier detection, the dissertation addresses the topic of unsupervised machine learning methods. In the unsupervised scenario, lack of prior knowledge of the data behavior is assumed. In the specific, two models are brought to attention, namely Local Outlier Factor and One-Class Support Vector Machines. Their performances are compared in terms of both the achieved prediction accuracy and the equivalent computational cost. Both models are trained and tested upon the same sets of time series data in a variety of settings, finalized at gaining insights on the effect of the increase in dimensionality. The obtained results allow to claim that both models, combined with a proper tuning of their characteristic parameters, successfully comply with the role of outlier detectors in multivariate time series data. Nevertheless, under this specific context, Local Outlier Factor results to be outperforming One-Class SVM, in that it proves to be more stable over a wider range of input parameter values. This property is especially valuable in unsupervised learning since it suggests that the model is keen to adapting to unforeseen patterns.

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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.

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The current design life of nuclear power plant (NPP) could potentially be extended to 80 years. During this extended plant life, all safety and operationally relevant Instrumentation & Control (I&C) systems are required to meet their designed performance requirements to ensure safe and reliable operation of the NPP, both during normal operation and subsequent to design base events. This in turn requires an adequate and documented qualification and aging management program. It is known that electrical insulation of I&C cables used in safety related circuits can degrade during their life, due to the aging effect of environmental stresses, such as temperature, radiation, vibration, etc., particularly if located in the containment area of the NPP. Thus several condition monitoring techniques are required to assess the state of the insulation. Such techniques can be used to establish a residual lifetime, based on the relationship between condition indicators and ageing stresses, hence, to support a preventive and effective maintenance program. The object of this thesis is to investigate potential electrical aging indicators (diagnostic markers) testing various I&C cable insulations subjected to an accelerated multi-stress (thermal and radiation) aging.

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L’obiettivo della seguente tesi è quello di illustrare le condizioni in cui avviene il trasferimento di conoscenza da consulente a cliente, e come questo sia il fattore abilitante per l’esistenza e l’utilizzo di tale figura professionale da parte delle organizzazioni. Questa tesi nasce dall’esperienza vissuta durante la partecipazione alla XXIV edizione di Junior Consulting, un programma organizzato da CONSEL - ELIS presso Roma, che ha permesso al sottoscritto di prendere parte al progetto di consulenza “Engineering & Construction - Performance Monitoring System” commissionato da Enel Green Power. L’esigenza manifestata dall’azienda era quella di riuscire ad avere una visione chiara e definita della qualità delle attività svolte dalla funzione Engineering & Construction (E&C) e quindi l’obiettivo del progetto si è concretizzato nella definizione di un set di KPI idoneo a rappresentare una misura delle performance della suddetta funzione. Avendo testato, seppure per pochi mesi, l’attività consulenziale, il candidato ha compiuto uno studio teorico che andasse ad analizzare in dettaglio l’attività del consulente, la sua importanza nel mondo economico, il contesto in cui opera e i principali dibattiti accademici di cui è protagonista negli ultimi anni. Nell’elaborato viene analizzato il caso pratico sulla base degli studi della letteratura, con lo scopo di formulare un modello che descriva l’approccio che il consulente dovrebbe avere, durante lo svolgimento delle sue attività, per la realizzazione del trasferimento di conoscenza. Nel primo capitolo è riportato uno studio relativo all’importanza e agli effetti che le società di consulenza hanno avuto nell’ultimo secolo ed in particolare negli ultimi 30 anni. Nel secondo capitolo è descritto il core asset delle società di consulenza, ovvero la conoscenza, e come questa è strutturata e gestita. Nel terzo capitolo sono analizzate le principali teorie sviluppate sulla figura del consulente, sia l’evoluzione storica che le principali posizioni ancora oggi oggetto di dibattito. Nel quarto capitolo l’attenzione è focalizzata sul trasferimento di conoscenza da consulente a cliente e sulle condizioni in cui questo può avvenire. Nel quinto capitolo è presentato il progetto sopracitato, i cui risultati sono riportati negli allegati 1 e 2. Infine, nel sesto capitolo, è presentato un modello di approccio del consulente ottenuto dall’analisi critica del caso pratico sulla base delle evidenze emerse dallo studio della letteratura.

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The main purpose of ultrarelativistic heavy-ion collisions is the investigation of the QGP. The ALICE experiment situated at the CERN has been specifically designed to study heavy-ion collisions for centre-of-mass energies up to 5.5 per nucleon pair. Extended particle identification capability is one of the main characteristics of the ALICE experiment. In the intermediate momentum region (up to 2.5 GeV/c for pi/K and 4 GeV/c for K/p), charged particles are identified in the ALICE experiment by the Time of Flight (TOF) detector. The ALICE-TOF system is a large-area detector based on the use of Multi-gap Resistive Plate Chamber (MRPC) built with high efficiency, fast response and intrinsic time resolution better than 40 ps. This thesis work, developed with the ALICE-TOF Bologna group, is part of the efforts carried out to adapt the read-out of the detector to the new requirements after the LHC Long Shutdown 2. Tests on the feasibility of a new read-out scheme for the TOF detector have been performed. In fact, the achievement of a continuous read-out also for the TOF detector would not be affordable if one considers the replacement of the TRM cards both for hardware and budget reasons. Actually, the read-out of the TOF is limited at 250 kHz i.e. it would be able to collect up to just a fourth of the maximum collision rate potentially achievable for pp interactions. In this Master’s degree thesis work, I discuss a different read-out system for the ALICE-TOF detector that allows to register all the hits at the interaction rate of 1 MHz foreseen for pp interactions after the 2020, by using the electronics currently available. Such solution would allow the ALICE-TOF detector to collect all the hits generated by pp collisions at 1 MHz interaction rate, which corresponds to an amount four times larger than that initially expected at such frequencies with the triggered read-out system operated at 250 kHz for LHC Run 3. The obtained results confirm that the proposed read-out scheme is a viable option for the ALICE TOF detector. The results also highlighted that it will be advantageous if the ALICE-TOF group also implement an online monitoring system of noisy channels to allow their deactivation in real time.

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This work presents the case of the San Lorenzo road tunnel, a transportation infrastructure located in the northern part of Italy, involved in the so-called Passo della Morte landslide. This tunnel crosses a large rockslide characterized by slow movements. Damages like water seepage inside the tunnel and concrete lining detachments have surfaced through the years, increasing the risk. This work develops the objective of tracing back the landslide-induced stresses directly responsible for the cracks’ pattern on the most damaged segments of the tunnel. The first section of this work gives information about the global framework: site geography and its strategic relevance, geological setting, hydrological and climate conditions will be provided. The road tunnel infrastructure and its interaction with the landslide phenomena will be discussed together with the active monitoring system, which has been working for more than 20 years. In the second part the several steps and tools used to add more details about the road damages are reported. A visualization of the actual state of the most damaged portions of the road has been reached. Then the attention has been addressed to the stresses acting on the road tunnel’s aforesaid portions, developing a FEM model of a section of the tunnel through a selected software. This latter process can be deemed as a beginning for further developments. Some preliminary results are shown to demonstrate the goodness of the assumptions made. The possible future set by this work aims at constant enlargement of information to be provided to the FEM software, and at the validation of the obtained results through the monitoring data interpretative tools.

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This thesis studies the state-of-the-art of phasor measurement units (PMUs) as well as their metrological requirements stated in the IEEE C37.118.1 and C37.118.2 Standards for guaranteeing correct measurement performances. Communication systems among PMUs and their possible applicability in the field of power quality (PQ) assessment are also investigated. This preliminary study is followed by an analysis of the working principle of real-time (RT) simulators and the importance of hardware-in-the-loop (HIL) implementation, examining the possible case studies specific for PMUs, including compliance tests which are one of the most important parts. The core of the thesis is focused on the implementation of a PMU model in the IEEE 5-bus network in Simulink and in the validation of the results using OPAL RT-4510 as a real-time simulator. An initial check allows one to get an idea about the goodness of the results in Simulink, comparing the PMU data with respect to the load-flow steady-state information. In this part, accuracy indices are also calculated for both voltage and current synchrophasors. The following part consists in the implementation of the same code in OPAL-RT 4510 simulator, after which an initial analysis is carried out in a qualitative way in order to get a sense of the goodness of the outcomes. Finally, the confirmation of the results is based on an examination of the attained voltage and current synchrophasors and accuracy indices coming from Simulink models and from OPAL system, using a Matlab script. This work also proposes suggestions for an upcoming operation of PMUs in a more complex system as the Digital Twin (DT) in order to improve the performances of the already-existing protection devices of the distribution system operator (DSO) for a future enhancement of power systems reliability.