955 resultados para Noise detection
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Structural Health Monitoring (SHM) has diverse potential applications, and many groups work in the development of tools and techniques for monitoring structural performance. These systems use arrays of sensors and can be integrated with remote or local computers. There are several different approaches that can be used to obtain information about the existence, location and extension of faults by non destructive tests. In this paper an experimental technique is proposed for damage location based on an observability grammian matrix. The dynamic properties of the structure are identified through experimental data using the eigensystem realization algorithm (ERA). Experimental tests were carried out in a structure through varying the mass of some elements. Output signals were obtained using accelerometers.
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The cyclic voltammetric behavior of acetaldehyde and the derivatized product with 2,4-dinitrophenylhydrazine (DNPHi) has been studied at a glassy carbon electrode. This study was used to optimize the best experimental conditions for its determination by high-performance liquid chromatographic (HPLC) separation coupled with electrochemical detection. The acetaldehyde-2,4-dinitrophenyl.hydrazone (ADNPH) was eluted and separated by a reversed-phase column, C-18, under isocratic conditions with the mobile phase containing a binary mixture of methanol/LiCl(aq) at a concentration of 1.0 x 10(-3) M (80:20 v/v) and a flow rate of 1.0 mL min(-1). The optimum condition for the electrochemical detection of ADNPH was +1.0 V vs. Ag/AgCl as a reference electrode. The proposed method was simple, rapid (analysis time 7 min) and sensitive (detection limit 3.80 mu g L-1) at a signal-to-noise ratio of 3:1. It was also highly selective and reproducible [standard deviation 8.2% +/- 0.36 (n = 5)]. The analytical curve of ADNPH was linear over the range of 3-300 mg L-1 per injection (20 mu L), and the analytical recovery was > 99%.
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An analysis of the active pixel sensor (APS), considering the doping profiles of the photodiode in an APS fabricated in a 0.18 μm standard CMOS technology, is presented. A simple and accurate model for the junction capacitance of the photodiode is proposed. An analytic expression for the output voltage of the APS obtained with this capacitance model is in good agreement with measurements and is more accurate than the models used previously. A different mode of operation for the APS based on the dc level of the output is suggested. This new mode has better low-light-level sensitivity than the conventional APS operating mode, and it has a slower temporal response to the change of the incident light power. At 1μW/cm2 and lower levels of light, the measured signal-to-noise ratio (SNR) of this new mode is more than 10 dB higher than the SNR of previously reported APS circuits. Also, with an output SNR of about 10 dB, the proposed dc level is capable of detecting light powers as low as 20 nW/cm2, which is about 30 times lower than the light power detected in recent reports by other groups. © 2007 IEEE.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In water distribution systems, old metallic pipes have been replaced by plastic pipes due to their deterioration over time. Although acoustic methods are effective in finding leaks in metallic pipes, they have been found to be problematic when applied to plastic pipes due to the high damping within the pipe wall and the surrounding medium. This is responsible for the leak signal not traveling long distances. Moreover, the leak energy in plastic pipes is generally located at a narrow frequency range located at low frequencies. However, the presence of resonances can narrow even more this frequency range. In order to minimise the influence of background noise and resonances on the calculation of the time delay estimate, band-pass filters are often used to supress undesirable frequency components of the noise. The objective of this paper is to investigate the influence of resonances in the pipe system (pipe, valves, connections and hydrants), on the time delay estimate calculated using acoustic signals. Analytical models and actual leak data collected in a bespoke rig located in the United Kingdom are used to investigate this feature.
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Optimal levels of noise stimulation have been shown to enhance the detection and transmission of neural signals thereby improving the performance of sensory and motor systems. The first series of experiments in the present study aimed to investigate whether subsensory electrical noise stimulation applied over the triceps surae (TS) in seated subjects decreases torque variability during a force-matching task of isometric plantar flexion and whether the same electrical noise stimulation decreases postural sway during quiet stance. Correlation tests were applied to investigate whether the noise-induced postural sway decrease is linearly predicted by the noise-induced torque variability decrease. A second series of experiments was conducted to investigate whether there are differences in torque variability between conditions in which the subsensory electrical noise is applied only to the TS, only to the tibialis anterior (TA) and to both TS and TA, during the force-matching task with seated subjects. Noise stimulation applied over the TS muscles caused a significant reduction in force variability during the maintained isometric force paradigm and also decreased postural oscillations during quiet stance. Moreover, there was a significant correlation between the reduction in force fluctuation and the decrease in postural sway with the electrical noise stimulation. This last result indicates that changes in plantar flexion force variability in response to a given subsensory random stimulation of the TS may provide an estimate of the variations in postural sway caused by the same subsensory stimulation of the TS. We suggest that the decreases in force variability and postural sway found here are due to stochastic resonance that causes an improved transmission of proprioceptive information. In the second series of experiments, the reduction in force variability found when noise was applied to the TA muscle alone did not reach statistical significance, suggesting that TS proprioception gives a better feedback to reduce force fluctuation in isometric plantar flexion conditions.
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The magnetic behaviour of most commercial ferromagnetic steels is usually anisotropic presenting a magnetic easy axis. Changes in the direction of this axis can be related to mechanical changes and anomalies that occur in the fabrication process. The present work describes a method that uses a device with permanent magnets to create a precise rotational magnetic field. The device measures continuous Magnetic Barkhausen Noise signals related to the angle of magnetization, in order to determine the direction of the macroscopic magnetic easy axis. It also offers the possibility of obtaining real time parameters that quantify the magnetic anisotropy of the sample. (C) 2011 Elsevier Ltd. All rights reserved.
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The Pierre Auger Observatory is exploring the potential of the radio detection technique to study extensive air showers induced by ultra-high energy cosmic rays. The Auger Engineering Radio Array (AERA) addresses both technological and scientific aspects of the radio technique. A first phase of AERA has been operating since September 2010 with detector stations observing radio signals at frequencies between 30 and 80 MHz. In this paper we present comparative studies to identify and optimize the antenna design for the final configuration of AERA consisting of 160 individual radio detector stations. The transient nature of the air shower signal requires a detailed description of the antenna sensor. As the ultra-wideband reception of pulses is not widely discussed in antenna literature, we review the relevant antenna characteristics and enhance theoretical considerations towards the impulse response of antennas including polarization effects and multiple signal reflections. On the basis of the vector effective length we study the transient response characteristics of three candidate antennas in the time domain. Observing the variation of the continuous galactic background intensity we rank the antennas with respect to the noise level added to the galactic signal.
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This paper presents preliminary results to determine small displacements of a global positioning system (GPS) antenna fastened to a structure using only one L1 GPS receiver. Vibrations, periodic or not, are common in large structures, such as bridges, footbridges, tall buildings, and towers under dynamic loads. The behavior in time and frequency leads to structural analysis studies. The hypothesis of this article is that any large structure that presents vibrations in the centimeter-to-millimeter range can be monitored by phase measurements of a single L1 receiver with a high data rate, as long as the direction of the displacement is pointing to a particular satellite. Within this scenario, the carrier phase will be modulated by antenna displacement. During a period of a few dozen seconds, the relative displacement to the satellite, the satellite clock, and the atmospheric phase delays can be assumed as a polynomial time function. The residuals from a polynomial adjustment contain the phase modulation owing to small displacements, random noise, receiver clock short time instabilities, and multipath. The results showed that it is possible to detect displacements of centimeters in the phase data of a single satellite and millimeters in the difference between the phases of two satellites. After applying a periodic nonsinusoidal displacement of 10 m to the antenna, it is clearly recovered in the difference of the residuals. The time domain spectrum obtained by the fast Fourier transform (FFT) exhibited a defined peak of the third harmonic much more than the random noise using the proposed third-degree polynomial model. DOI: 10.1061/(ASCE)SU.1943-5428.0000070. (C) 2012 American Society of Civil Engineers.
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[EN] The aortic dissection is a disease that can cause a deadly situation, even with a correct treatment. It consists in a rupture of a layer of the aortic artery wall, causing a blood flow inside this rupture, called dissection. The aim of this paper is to contribute to its diagnosis, detecting the dissection edges inside the aorta. A subpixel accuracy edge detector based on the hypothesis of partial volume effect is used, where the intensity of an edge pixel is the sum of the contribution of each color weighted by its relative area inside the pixel. The method uses a floating window centred on the edge pixel and computes the edge features. The accuracy of our method is evaluated on synthetic images of different hickness and noise levels, obtaining an edge detection with a maximal mean error lower than 16 percent of a pixel.
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Recent progress in microelectronic and wireless communications have enabled the development of low cost, low power, multifunctional sensors, which has allowed the birth of new type of networks named wireless sensor networks (WSNs). The main features of such networks are: the nodes can be positioned randomly over a given field with a high density; each node operates both like sensor (for collection of environmental data) as well as transceiver (for transmission of information to the data retrieval); the nodes have limited energy resources. The use of wireless communications and the small size of nodes, make this type of networks suitable for a large number of applications. For example, sensor nodes can be used to monitor a high risk region, as near a volcano; in a hospital they could be used to monitor physical conditions of patients. For each of these possible application scenarios, it is necessary to guarantee a trade-off between energy consumptions and communication reliability. The thesis investigates the use of WSNs in two possible scenarios and for each of them suggests a solution that permits to solve relating problems considering the trade-off introduced. The first scenario considers a network with a high number of nodes deployed in a given geographical area without detailed planning that have to transmit data toward a coordinator node, named sink, that we assume to be located onboard an unmanned aerial vehicle (UAV). This is a practical example of reachback communication, characterized by the high density of nodes that have to transmit data reliably and efficiently towards a far receiver. It is considered that each node transmits a common shared message directly to the receiver onboard the UAV whenever it receives a broadcast message (triggered for example by the vehicle). We assume that the communication channels between the local nodes and the receiver are subject to fading and noise. The receiver onboard the UAV must be able to fuse the weak and noisy signals in a coherent way to receive the data reliably. It is proposed a cooperative diversity concept as an effective solution to the reachback problem. In particular, it is considered a spread spectrum (SS) transmission scheme in conjunction with a fusion center that can exploit cooperative diversity, without requiring stringent synchronization between nodes. The idea consists of simultaneous transmission of the common message among the nodes and a Rake reception at the fusion center. The proposed solution is mainly motivated by two goals: the necessity to have simple nodes (to this aim we move the computational complexity to the receiver onboard the UAV), and the importance to guarantee high levels of energy efficiency of the network, thus increasing the network lifetime. The proposed scheme is analyzed in order to better understand the effectiveness of the approach presented. The performance metrics considered are both the theoretical limit on the maximum amount of data that can be collected by the receiver, as well as the error probability with a given modulation scheme. Since we deal with a WSN, both of these performance are evaluated taking into consideration the energy efficiency of the network. The second scenario considers the use of a chain network for the detection of fires by using nodes that have a double function of sensors and routers. The first one is relative to the monitoring of a temperature parameter that allows to take a local binary decision of target (fire) absent/present. The second one considers that each node receives a decision made by the previous node of the chain, compares this with that deriving by the observation of the phenomenon, and transmits the final result to the next node. The chain ends at the sink node that transmits the received decision to the user. In this network the goals are to limit throughput in each sensor-to-sensor link and minimize probability of error at the last stage of the chain. This is a typical scenario of distributed detection. To obtain good performance it is necessary to define some fusion rules for each node to summarize local observations and decisions of the previous nodes, to get a final decision that it is transmitted to the next node. WSNs have been studied also under a practical point of view, describing both the main characteristics of IEEE802:15:4 standard and two commercial WSN platforms. By using a commercial WSN platform it is realized an agricultural application that has been tested in a six months on-field experimentation.
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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.
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Investigation on impulsive signals, originated from Partial Discharge (PD) phenomena, represents an effective tool for preventing electric failures in High Voltage (HV) and Medium Voltage (MV) systems. The determination of both sensors and instruments bandwidths is the key to achieve meaningful measurements, that is to say, obtaining the maximum Signal-To-Noise Ratio (SNR). The optimum bandwidth depends on the characteristics of the system under test, which can be often represented as a transmission line characterized by signal attenuation and dispersion phenomena. It is therefore necessary to develop both models and techniques which can characterize accurately the PD propagation mechanisms in each system and work out the frequency characteristics of the PD pulses at detection point, in order to design proper sensors able to carry out PD measurement on-line with maximum SNR. Analytical models will be devised in order to predict PD propagation in MV apparatuses. Furthermore, simulation tools will be used where complex geometries make analytical models to be unfeasible. In particular, PD propagation in MV cables, transformers and switchgears will be investigated, taking into account both irradiated and conducted signals associated to PD events, in order to design proper sensors.
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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.
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The purpose of this article is to assess the impact of large patient size on the detection of hypovascular liver tumors with MDCT and the effect of a noise filter on image quality and lesion detection in obese patients.