939 resultados para Condition-based Maintenance, Condition Monitoring, Prognostics, Reliability


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This paper presents a multi-stage algorithm for the dynamic condition monitoring of a gear. The algorithm provides information referred to the gear status (fault or normal condition) and estimates the mesh stiffness per shaft revolution in case that any abnormality is detected. In the first stage, the analysis of coefficients generated through discrete wavelet transformation (DWT) is proposed as a fault detection and localization tool. The second stage consists in establishing the mesh stiffness reduction associated with local failures by applying a supervised learning mode and coupled with analytical models. To do this, a multi-layer perceptron neural network has been configured using as input features statistical parameters sensitive to torsional stiffness decrease and derived from wavelet transforms of the response signal. The proposed method is applied to the gear condition monitoring and results show that it can update the mesh dynamic properties of the gear on line.

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Registration of births, recording deaths by age, sex and cause, and calculating mortality levels and differentials are fundamental to evidence-based health policy, monitoring and evaluation. Yet few of the countries with the greatest need for these data have functioning systems to produce them despite legislation providing for the establishment and maintenance of vital registration. Sample vital registration (SVR), when applied in conjunction with validated verbal autopsy, procedures and implemented in a nationally representative sample of population clusters represents an affordable, cost-effective, and sustainable short- and medium-term solution to this problem. SVR complements other information sources by producing age-, sex-, and cause-specific mortality data that are more complete and continuous than those currently available. The tools and methods employed in an SVR system, however, are imperfect and require rigorous validation and continuous quality assurance; sampling strategies for SVR are also still evolving. Nonetheless, interest in establishing SVR is rapidly growing in Africa and Asia. Better systems for reporting and recording data on vital events will be sustainable only if developed hand-in-hand with existing health information strategies at the national and district levels; governance structures; and agendas for social research and development monitoring. If the global community wishes to have mortality measurements 5 or 10 years hence, the foundation stones of SVR must be laid today.

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OBJECTIVE - The purpose of this study was to determine whether beneficial effects on glycemic control of an initial laboratory-supervised resistance training program could be sustained through a community center-based maintenance program. RESEARCH DESIGN AND METHODS - We studied 57 overweight (BMI >= 27 kg/m(2)) sedentary men and women aged 40-80 years with established (> 6 months) type 2 diabetes. initially, all participants attended a twice-weekly 2-month supervised resistance training program conducted in the exercise laboratory. Thereafter, participants undertook a resistance training maintenance program (2 times/week) for 12 months and were randomly assigned to carry this out either in a community fitness and recreation center (center) or in their domestic environment (home). Glycemic control (HbA(1c) [A1C]) was assessed at 0, 2, and 14 months. RESULTS - Pooling data from the two groups for the 2-month supervised resistance training program showed that compared with baseline, mean A1C fell by -0.4% [95% CI -0.6 to -0.2]. Within-group comparisons showed that A I C remained lower than baseline values at 14 months in the center group (- 0.4% [-0.7 to -0.03]) but not in the home group (-0.1% [-0.4 to 0.3]). However, no between-group differences were observed at each time point. Changes in AIC during the maintenance period were positively associated with exercise adherence in the center group only. CONCLUSIONS - Center-based but not home-based resistance training was associated with the maintenance of modestly improved glycemic control from baseline, which was proportional to program adherence. Our findings emphasize the need to develop and test behavioral methods to promote healthy lifestyles including increased physical activity in adults with type 2 diabetes.

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This thesis presents the potential sensing applications of fibre Bragg gratings in polymer optical fibres. Fibre Bragg gratings are fabricated in different kinds of polymer optical fibres, including Poly methyl methacrylate (PMMA) and TOPAS cyclic olefin copolymer based microstructured polymer optical fibres and PMMA based step-index photosensitive polymer optical fibre, using the 325nm continuous wave ultraviolet laser and phase mask technique. The thermal response of fabricated microstructured polymer optical fibre Bragg gratings has been characterized. The PMMA based single mode microstructured polymer optical fibre Bragg gratings exhibit negative non-linear Bragg wavelength shift with temperature, including a quasi-linear region. The thermal sensitivity of such Bragg gratings in the linear region is up to -97pm/°C. A permanent shift in the grating wavelength at room temperature is observed when such gratings are heated above a threshold temperature which can be extended by annealing the fibre before grating inscription. The largest positive Bragg wavelength shift with temperature in transmission is observed in TOPAS based few moded microstructured polymer optical fibre Bragg gratings and the measured temperature sensitivity is 250±0.5pm/°C. Gluing method is developed to maintain stable optical coupling between PMMA based single mode step index polymer optical fibre Bragg gratings and single mode step index silica optical fibre. Being benefit from this success, polymer optical fibre Bragg gratings are able to be characterised for their temperature, humidity and strain sensitivity, which are -48.2±1pm/°C, 38.3±0.5pm per %RH and 1.33±0.04 pm/µ??respectively. These sensitivities have been utilised to achieve several applications. The strain sensitivity of step index polymer optical fibre Bragg grating devices has been exploited in the potential application of the strain condition monitoring of heavy textiles and when being attached to textile specimens with certain type of adhesives. These polymer fibre Bragg grating devices show better strain transfer and lower structure reinforcement than silica optical fibre Bragg grating devices. The humidity sensitivity of step index polymer optical fibre Bragg grating devices is applied to detecting water in jet fuel and is proved to be able to measure water content of less than 20 ppm in Jet fuel. A simultaneous temperature and humidity sensor is also made by attaching a polymer fibre Bragg grating to a silica optical fibre Bragg grating and it shows better humidity measurement accuracy than that of electronic competitors.

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The Product Service Systems, servitization, and Service Science literature continues to grow as organisations seek to protect and improve their competitive position. The potential of technology applications to deliver service delivery systems facilitated by the ability to make real time decisions based upon ‘in the field’ performance is also significant. Research identifies four key questions to be addressed. Namely: how far along the servitization continuum should the organisation go in a single strategic step? Does the organisation have the structure and infrastructure to support this transition? What level of condition monitoring should it employ? Is the product positioned correctly in the value chain to adopt condition monitoring technology? Strategy consists of three dimensions, namely content, context, and process. The literature relating to PSS, servitization, and strategy all discuss the concepts relative to content and context but none offer a process to deliver an aligned strategy to deliver a service delivery system enabled by condition based management. This paper presents a tested iterative strategy formulation methodology which is the result of a structured development programme.

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The utilization of solar energy by photovoltaic (PV) systems have received much research and development (R&D) attention across the globe. In the past decades, a large number of PV array have been installed. Since the installed PV arrays often operate in harsh environments, non-uniform aging can occur and impact adversely on the performance of PV systems, especially in the middle and late periods of their service life. Due to the high cost of replacing aged PV modules by new modules, it is appealing to improve energy efficiency of aged PV systems. For this purpose, this paper presents a PV module reconfiguration strategy to achieve the maximum power generation from non-uniformly aged PV arrays without significant investment. The proposed reconfiguration strategy is based on the cell-unit structure of PV modules, the operating voltage limit of gird-connected converter, and the resulted bucket-effect of the maximum short circuit current. The objectives are to analyze all the potential reorganization options of the PV modules, find the maximum power point and express it in a proposition. This proposition is further developed into a novel implementable algorithm to calculate the maximum power generation and the corresponding reconfiguration of the PV modules. The immediate benefits from this reconfiguration are the increased total power output and maximum power point voltage information for global maximum power point tracking (MPPT). A PV array simulation model is used to illustrate the proposed method under three different cases. Furthermore, an experimental rig is built to verify the effectiveness of the proposed method. The proposed method will open an effective approach for condition-based maintenance of emerging aging PV arrays.

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This paper presents a novel real-time power-device temperature estimation method that monitors the power MOSFET's junction temperature shift arising from thermal aging effects and incorporates the updated electrothermal models of power modules into digital controllers. Currently, the real-time estimator is emerging as an important tool for active control of device junction temperature as well as online health monitoring for power electronic systems, but its thermal model fails to address the device's ongoing degradation. Because of a mismatch of coefficients of thermal expansion between layers of power devices, repetitive thermal cycling will cause cracks, voids, and even delamination within the device components, particularly in the solder and thermal grease layers. Consequently, the thermal resistance of power devices will increase, making it possible to use thermal resistance (and junction temperature) as key indicators for condition monitoring and control purposes. In this paper, the predicted device temperature via threshold voltage measurements is compared with the real-time estimated ones, and the difference is attributed to the aging of the device. The thermal models in digital controllers are frequently updated to correct the shift caused by thermal aging effects. Experimental results on three power MOSFETs confirm that the proposed methodologies are effective to incorporate the thermal aging effects in the power-device temperature estimator with good accuracy. The developed adaptive technologies can be applied to other power devices such as IGBTs and SiC MOSFETs, and have significant economic implications.

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The importance of non-destructive techniques (NDT) in structural health monitoring programmes is being critically felt in the recent times. The quality of the measured data, often affected by various environmental conditions can be a guiding factor in terms usefulness and prediction efficiencies of the various detection and monitoring methods used in this regard. Often, a preprocessing of the acquired data in relation to the affecting environmental parameters can improve the information quality and lead towards a significantly more efficient and correct prediction process. The improvement can be directly related to the final decision making policy about a structure or a network of structures and is compatible with general probabilistic frameworks of such assessment and decision making programmes. This paper considers a preprocessing technique employed for an image analysis based structural health monitoring methodology to identify sub-marine pitting corrosion in the presence of variable luminosity, contrast and noise affecting the quality of images. A preprocessing of the gray-level threshold of the various images is observed to bring about a significant improvement in terms of damage detection as compared to an automatically computed gray-level threshold. The case dependent adjustments of the threshold enable to obtain the best possible information from an existing image. The corresponding improvements are observed in a qualitative manner in the present study.

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A field experiment was conducted on a real continuous steel Gerber-truss bridge with artificial damage applied. This article summarizes the results of the experiment for bridge damage detection utilizing traffic-induced vibrations. It investigates the sensitivities of a number of quantities to bridge damage including the identified modal parameters and their statistical patterns, Nair’s damage indicator and its statistical pattern and different sets of measurement points. The modal parameters are identified by autoregressive time-series models. The decision on bridge health condition is made and the sensitivity of variables is evaluated with the aid of the Mahalanobis–Taguchi system, a multivariate pattern recognition tool. Several observations are made as follows. For the modal parameters, although bridge damage detection can be achieved by performing Mahalanobis–Taguchi system on certain modal parameters of certain sets of measurement points, difficulties were faced in subjective selection of meaningful bridge modes and low sensitivity of the statistical pattern of the modal parameters to damage. For Nair’s damage indicator, bridge damage detection could be achieved by performing Mahalanobis–Taguchi system on Nair’s damage indicators of most sets of measurement points. As a damage indicator, Nair’s damage indicator was superior to the modal parameters. Three main advantages were observed: it does not require any subjective decision in calculating Nair’s damage indicator, thus potential human errors can be prevented and an automatic detection task can be achieved; its statistical pattern has high sensitivity to damage and, finally, it is flexible regarding the choice of sets of measurement points.

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There are various tools for monitoring the concentration of pollutants on aquatic ecosystems. Today these studies are based on biological monitoring and biomarkers. The aim of this study was to measure the concentration of the acetylcholinesterase (AChE), glutathione S-transferase and catalase as biomarkers of heavy metal contamination in pearl oyster Pinctada radiata and their mechanism in aquatic ecosystems. Heavy metals lead, cadmium and nickel were measured in soft tissue and studied stations in four seasons. Samples were collected seasonally in Lavan stations, Hendurabi and Nakhilo (in the northern Persian Gulf) from spring 2013 to winter of that year by scuba diving. Pearl oysters are divided according to their shells size; shells separated from soft tissues and were transferred to the laboratory for analysis of heavy metals and enzymes. Moopam standard method for were used for measuring the concentration of heavy metals and for analyzing tissue concentrations of glutathione S-transferase in Clam the method recommended by Habig et al in 1974 were used. For measuring acetylcholinesterase Ellman method were used. Catalase contamination in pearl oyster in the supernatant obtained from the study based on the method homogeate soft tissue of mussels (Abei, 1974) was evaluated. The results showed that the concentration of lead has significant difference in sediments station, the concentration of lead in Lavan is significantly higher than the other two stations, This could be due to the movement of tanker, boats and floating refueling and with a considerable amount of wastewater containing oil and Petroleum into the water, and also due to precipitation and industrial discharges the lead in the region is increasing, land-disposed sewage sludge, has large concentrations of lead. Compare the results of this study with standards related and other similar studies at the regional and international level showed that pollutant concentration of heavy metals in all cases significantly less than all the standards and guide values associated. And also compared to other world research results have been far less than others, Being Less of the conclusion given in this research according that nickel is one of the indicators of oil pollution in the study area and emissions have been relatively low of oil. The concentration of acetylcholinesterase at several stations, in large and small sizes and in the seasons had no significant difference. Variations of catalase, and glutathione S-transferase were almost similar to each other and parameters, station and seasons were significantly different in the concentrations of these enzymes. The effects and interaction between various parameters indicate that following parameters has impact on the concentration of catalase and glutathione S-transferase. Stations; Seasonal changes in antioxidant enzymes related to (assuming a constant in salinity and oxygen) to age, reproductive cycle, availability of food and water temperature. With increasing temperature at warm season, antioxidant enzymes were increase, with increasing temperature and abundance of food in the environment the amount of antioxidant enzymes may increase. The presence of the enzyme concentration may indicate that the higher levels of the enzyme to eliminate ROS activities to be any healthier situation. At the time of gonads maturation and spawning season catalase activity increases. This study also indicates that catalase was significantly higher in the warm season. Due to low pollutants of heavy metals in the study area, a lower level of contaminants were observed in shellfish tissue incidents of international standards and strong correlation between the amount of heavy metal contamination in pearl oyster tissue and enzymes was not observed. Therefore, we can say that the pearl oyster remains in a healthy condition and the amount of enzyme is normal.

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In questo elaborato di tesi si affronta uno studio inerente alla Manutenzione su Condizione (CBM), applicata ad una macchina automatica adibita alla produzione di capsule in plastica, in collaborazione con il gruppo SACMI S.C. di Imola. Nel Capitolo 1 viene fornita una introduzione sul tema della manutenzione e sulla sua evoluzione dalla prima rivoluzione industriale ad oggi. Nel Capitolo 2 vengono descritti i principi teorici della manutenzione predittiva e se ne analizza lo stato dell’arte. Nel Capitolo 3 viene fornita una introduzione sull’azienda SACMI S.C. e in seguito vengono descritte nel dettaglio le macchine sulle quali si sono concentrate le successive analisi. Nel Capitolo 4 viene approfondito l’estrusore, uno dei componenti principali delle macchine analizzate. Nel Capitolo 5 viene presentato un esempio di valutazione dell’efficienza di alcune macchine collegate in serie attraverso il calcolo di un indicatore chiamato Overall Equipment Effectiveness (OEE). Il Capitolo 6 rappresenta il cuore della tesi e contiene tutte le analisi di CBM effettuate durante il periodo di tirocinio. Vengono analizzati i principali gruppi funzionali della macchina a partire da quelli più critici per tempi o costi di manutenzione. Le analisi sono state condotte ricercando all’interno di tutto il parco macchine quelle che presentavano delle condizioni di funzionamento sospette. Nel Capitolo 7 vengono presentate alcune analisi relative ai tempi di fermo macchina dovuti alle manutenzioni preventive e ai costi dei ricambi previsti dal manuale di manutenzione. Queste analisi vengono poi declinate su un caso reale nel quale si calcola il costo dei ricambi negli ultimi cinque anni distinguendo tra costi dovuti ad azioni preventive o correttive. Nel Capitolo 8 vengono presentate le conclusioni, mentre nel Capitolo 9 sono presentati gli sviluppi futuri di questo lavoro.

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A densely built environment is a complex system of infrastructure, nature, and people closely interconnected and interacting. Vehicles, public transport, weather action, and sports activities constitute a manifold set of excitation and degradation sources for civil structures. In this context, operators should consider different factors in a holistic approach for assessing the structural health state. Vibration-based structural health monitoring (SHM) has demonstrated great potential as a decision-supporting tool to schedule maintenance interventions. However, most excitation sources are considered an issue for practical SHM applications since traditional methods are typically based on strict assumptions on input stationarity. Last-generation low-cost sensors present limitations related to a modest sensitivity and high noise floor compared to traditional instrumentation. If these devices are used for SHM in urban scenarios, short vibration recordings collected during high-intensity events and vehicle passage may be the only available datasets with a sufficient signal-to-noise ratio. While researchers have spent efforts to mitigate the effects of short-term phenomena in vibration-based SHM, the ultimate goal of this thesis is to exploit them and obtain valuable information on the structural health state. First, this thesis proposes strategies and algorithms for smart sensors operating individually or in a distributed computing framework to identify damage-sensitive features based on instantaneous modal parameters and influence lines. Ordinary traffic and people activities become essential sources of excitation, while human-powered vehicles, instrumented with smartphones, take the role of roving sensors in crowdsourced monitoring strategies. The technical and computational apparatus is optimized using in-memory computing technologies. Moreover, identifying additional local features can be particularly useful to support the damage assessment of complex structures. Thereby, smart coatings are studied to enable the self-sensing properties of ordinary structural elements. In this context, a machine-learning-aided tomography method is proposed to interpret the data provided by a nanocomposite paint interrogated electrically.

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Dissertation to obtain the Master degree in Electrical Engineering and Computer Science

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The primary objective of this research was to demonstrate the benefits of NDT technologies for effectively detecting and characterizing deterioration in bridge decks. In particular, the objectives were to demonstrate the capabilities of ground-penetrating radar (GPR) and impact echo (IE), and to evaluate and describe the condition of nine bridge decks proposed by Iowa DOT. The first part of the report provides a detailed review of the most important deterioration processes in concrete decks, followed by a discussion of the five NDT technologies utilized in this project. In addition to GPR and IE methods, three other technologies were utilized, namely: half-cell (HC) potential, electrical resistivity (ER), and ultrasonic surface waves (USW) method. The review includes a description of the principles of operation, field implementation, data analysis, and interpretation; information regarding their advantages and limitations in bridge deck evaluations and condition monitoring are also implicitly provided.. The second part of the report provides descriptions and bridge deck evaluation results from the nine bridges. The results of the NDT surveys are described in terms of condition assessment maps and are compared with the observations obtained from the recovered cores or conducted bridge deck rehabilitation. Results from this study confirm that the used technologies can provide detailed and accurate information about a certain type of deterioration, electrochemical environment, or defect. However, they also show that a comprehensive condition assessment of bridge decks can be achieved only through a complementary use of multiple technologies at this stage,. Recommendations are provided for the optimum implementation of NDT technologies for the condition assessment and monitoring of bridge decks.

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Sähkömoottorin jatkuva-aikainen kunnonvalvonta vaatii tiedonsiirtoa moottorilta ylemmälle tietojärjestelmätasolle, kuten taajuusmuuttajalle. Uusien kaapeleiden asennus on työlästä ja kallista. Moottorin ja taajuusmuuttajan välillä on kuitenkin aina kaapeli, jota käytetään moottorin tehonsyöttöön. Tätä kaapelia on mahdollista käyttää myös tiedonsiirtokanavana. Tässä diplomityössä käsitellään ja tutkitaan sähköverkkotiedonsiirtomenetelmää, jonka avulla voidaan muodostaa Ethernet-yhteys moottorilta taajuusmuuttajalle tai toisinpäin. Työssä kehitetään simulointimalli tiedonsiirtokanavan taajuusriippuvan vaimennuksen simuloimiseen. Lisäksi kehitetään kytkentärajapinta, joka mahdollistaa tiedonsiirron kolmivaiheisessa taajuusmuuttajan syöttämässä moottorikaapelissa. Työssä suunnitellaan ja toteutetaan tiedonsiirtoa varten pilot-laitteisto, jolla tehdään laboratoriotestit. Laboratoriotesteillä varmistetaan menetelmän soveltuvuus. Laboratoriotestien avulla etsitään myös reunaehdot tiedonsiirron toiminnalle ja tiedonsiirtonopeuteen vaikuttavia tekijöitä taajuusmuuttajakäytössä. Lisäksi tarkastellaan menetelmän aiheuttamaa viivettä, joka on tärkeäsäätösovellusten kannalta. Lopuksi arvioidaan menetelmän soveltuvuus käytännön sovelluksiin.