933 resultados para condition monitoring system
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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In 2005, Wetland Studies and Solutions, Inc. (WSSI) installed an extensive Low Impact Development (LID) stormwater management system on their new office site in Gainesville, Virginia. The 4-acre site is serviced by a network of LID components: permeable pavements (two proprietary and one gravel type), bioretention cell / rain garden, green roof, vegetated swale, rainwater harvesting and drip irrigation, and slow-release underground detention. The site consists of heavy clay soils, and the LID components are mostly integrated by a series of underdrain pipes. A comprehensive monitoring system has been designed and installed to measure hydrologic performance throughout the LID, underdrained network. The monitoring system measures flows into and out of each LID component independently while concurrently monitoring rainfall events. A sensitivity analysis and laboratory calibration has been performed on the flow measurement system. Field data has been evaluated to determine the hydrologic performance of the LID features. Finally, hydrologic models amenable to compact, underdrained LID sites have been reviewed and recommended for future modeling and design.
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Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.
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In this paper, we present experimental results for monitoring long distance WDM communication links using a line monitoring system suitable for legacy optically amplified long-haul undersea systems. This monitoring system is based on setting up a simple, passive, low cost high-loss optical loopback circuit at each repeater that provides a connection between the existing anti-directional undersea fibres, and can be used to define fault location. Fault location is achieved by transmitting a short pulse supervisory signal along with the WDM data signals where a portion of the overall signal is attenuated and returned to the transmit terminal by the loopback circuit. A special receiver is used at the terminal to extract the weakly returned supervisory signal where each supervisory signal is received at different times corresponding to different optical repeaters. Therefore, the degradation in any repeater appears on its corresponding supervisory signal level. We use a recirculating loop to simulate a 4600 km fibre link, on which a high-loss loopback supervisory system is implemented. Successful monitoring is accomplished through the production of an appropriate supervisory signal at the terminal that is detected and identified in a satisfactory time period after passing through up to 45 dB attenuation in the loopback circuit. © 2012 Elsevier B.V. All rights reserved.
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In this paper, we present experimental results for monitoring long distance WDM communication links using a line monitoring system suitable for legacy optically amplified long-haul undersea systems. This monitoring system is based on setting up a simple, passive, low cost high-loss optical loopback circuit at each repeater that provides a connection between the existing anti-directional undersea fibres, and can be used to define fault location. Fault location is achieved by transmitting a short pulse supervisory signal along with the WDM data signals where a portion of the overall signal is attenuated and returned to the transmit terminal by the loopback circuit. A special receiver is used at the terminal to extract the weakly returned supervisory signal where each supervisory signal is received at different times corresponding to different optical repeaters. Therefore, the degradation in any repeater appears on its corresponding supervisory signal level. We use a recirculating loop to simulate a 4600 km fibre link, on which a high-loss loopback supervisory system is implemented. Successful monitoring is accomplished through the production of an appropriate supervisory signal at the terminal that is detected and identified in a satisfactory time period after passing through up to 45 dB attenuation in the loopback circuit. © 2012 Elsevier B.V. All rights reserved.
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In this paper, we present experimental results for monitoring long distance WDM communication links using a line monitoring system suitable for legacy optically amplified long-haul undersea systems. This monitoring system is based on setting up a simple, passive, low cost high-loss optical loopback circuit at each repeater that provides a connection between the existing anti-directional undersea fibres, and can be used to define fault location. Fault location is achieved by transmitting a short pulse supervisory signal along with the WDM data signals where a portion of the overall signal is attenuated and returned to the transmit terminal by the loopback circuit. A special receiver is used at the terminal to extract the weakly returned supervisory signal where each supervisory signal is received at different times corresponding to different optical repeaters. Therefore, the degradation in any repeater appears on its corresponding supervisory signal level. We use a recirculating loop to simulate a 4600 km fibre link, on which a high-loss loopback supervisory system is implemented. Successful monitoring is accomplished through the production of an appropriate supervisory signal at the terminal that is detected and identified in a satisfactory time period after passing through up to 45 dB attenuation in the loopback circuit. © 2012 Elsevier B.V. All rights reserved.
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Structural monitoring and dynamic identification of the manmade and natural hazard objects is under consideration. Math model of testing object by set of weak stationary dynamic actions is offered. The response of structures to the set of signals is under processing for getting important information about object condition in high frequency band. Making decision procedure into active monitoring system is discussed as well. As an example the monitoring outcome of pillar-type monument is given.
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Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. ^ Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. ^ The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. ^ The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. ^ The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles. ^
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The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system's EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter's components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled
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The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system’s EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter’s components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled
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Appropriate ways to monitor the availability and use of illicit drugs were examined. Four methods were tested concurrently: (1) a quantitative survey of injecting drug users, (2) a qualitative key informant study of illicit drug users and professionals working in the drug field, (3) examination of existing sources of survey, health and law enforcement data and (4) an ethnographic study of a high risk group of illicit drug users. The first three methods were recommended for inclusion in an ongoing national monitoring system, enabling the collection of both quantitative and qualitative data on a range of illicit drugs in a relatively brief, quick and cost-effective manner. A degree of convergent validity was also noted among these methods, improving the degree of confidence in drug trends. The importance of injecting drug users as a sentinel population of illicit drug users was highlighted, along with optimal methods for qualitative research.
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Gamma and beta radiation emitting radiopharmaceuticals are handled in nuclear medicine services, and in many cases there is only individual monitoring of gamma radiation. In this paper, the results obtained using a wrist dosimeter prototype (CaSO(4):Dy + Teflon pellets) show that the doses for workers occupationally exposed to beta radiation from (153)Sm are not negligible. It is important that this dose is evaluated, and it has to be taken into consideration in the individual monitoring system.
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This paper presents experimental results of the communication performance evaluation of a prototype ZigBee-based patient monitoring system commissioned in an in-patient floor of a Portuguese hospital (HPG – Hospital Privado de Guimar~aes). Besides, it revisits relevant problems that affect the performance of nonbeacon-enabled ZigBee networks. Initially, the presence of hidden-nodes and the impact of sensor node mobility are discussed. It was observed, for instance, that the message delivery ratio in a star network consisting of six wireless electrocardiogram sensor devices may decrease from 100% when no hidden-nodes are present to 83.96% when half of the sensor devices are unable to detect the transmissions made by the other half. An additional aspect which affects the communication reliability is a deadlock condition that can occur if routers are unable to process incoming packets during the backoff part of the CSMA-CA mechanism. A simple approach to increase the message delivery ratio in this case is proposed and its effectiveness is verified. The discussion and results presented in this paper aim to contribute to the design of efficient networks,and are valid to other scenarios and environments rather than hospitals.
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AIM: This work presents detailed experimental performance results from tests executed in the hospital environment for Health Monitoring for All (HM4All), a remote vital signs monitoring system based on a ZigBee® (ZigBee Alliance, San Ramon, CA) body sensor network (BSN). MATERIALS AND METHODS: Tests involved the use of six electrocardiogram (ECG) sensors operating in two different modes: the ECG mode involved the transmission of ECG waveform data and heart rate (HR) values to the ZigBee coordinator, whereas the HR mode included only the transmission of HR values. In the absence of hidden nodes, a non-beacon-enabled star network composed of sensing devices working on ECG mode kept the delivery ratio (DR) at 100%. RESULTS: When the network topology was changed to a 2-hop tree, the performance degraded slightly, resulting in an average DR of 98.56%. Although these performance outcomes may seem satisfactory, further investigation demonstrated that individual sensing devices went through transitory periods with low DR. Other tests have shown that ZigBee BSNs are highly susceptible to collisions owing to hidden nodes. Nevertheless, these tests have also shown that these networks can achieve high reliability if the amount of traffic is kept low. Contrary to what is typically shown in scientific articles and in manufacturers' documentation, the test outcomes presented in this article include temporal graphs of the DR achieved by each wireless sensor device. CONCLUSIONS: The test procedure and the approach used to represent its outcomes, which allow the identification of undesirable transitory periods of low reliability due to contention between devices, constitute the main contribution of this work.
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The present paper results of an ongoing research project were it is expected to develop an information system to monitoring a cultural-touristic route. The route to monitor is the Romanesque Route of Tâmega. This Route is composed of 58 monuments located in the region of Tâmega in the North of Portugal. Due to the particular location of this region, that is between coastal zone, but not yet in the inland, it has a weak political influence, and it is reflected in the low levels of development at several levels, observed. The Romanesque Route was implemented in a part of this region in 1998, and enlarged to the all-region in 2010. In order to evaluate the socio-ecomonic impact of this route in the region a research project is being developed. The main goal of this paper is to open a discussion on the elements that must be taken into consideration to evaluate the economic and social impact of a touristic cultural route within a region and this one in particular.