Application of noise analysis for sensor surveillance in Trillo NPP

It is a known fact that noise analysis is a suitable method for sensor performance surveillance. In particular, controlling the response time of a sensor is an efficient way to anticipate failures and to have the opportunity to prevent them. In this work the response times of several sensors of Trillo NPP are estimated by means of noise analysis. The procedure applied consists of modeling each sensor with autoregressive methods and getting the searched parameter by analyzing the response of the model when a ramp is simulated as the input signal. Core exit thermocouples and in core self-powered neutron detectors are the main sensors analyzed but other plant sensors are studied as well. Since several measurement campaigns have been carried out, it has been also possible to analyze the evolution of the estimated parameters during more than one fuel cycle. Some sensitivity studies for the sample frequency of the signals and its influence on the response time are also included. Calculations and analysis have been done in the frame of a collaboration agreement between Trillo NPP operator (CNAT) and the School of Mines of Madrid.

Time evolution of frequency components In a chaotic digital signal

The type of signals obtained has conditioned chaos analysis tools. Almost in every case, they have analogue characteristics. But in certain cases, a chaotic digital signal is obtained and theses signals need a different approach than conventional analogue ones. The main objective of this paper will be to present some possible approaches to the study of this signals and how information about their characteristics may be obtained in the more straightforward possible way. We have obtained digital chaotic signals from an Optical Logic Cell with some feedback between output and one of the possible control gates. This chaos has been reported in several papers and its characteristics have been employed as a possible method to secure communications and as a way to encryption. In both cases, the influence of some perturbation in the transmission medium gave problems both for the synchronization of chaotic generators at emitter and receiver and for the recovering of information data. A proposed way to analyze the presence of some perturbation is to study the noise contents of transmitted signal and to implement a way to eliminate it. In our present case, the digital signal will be converted to a multilevel one by grouping bits in packets of 8 bits and applying conventional methods of time-frequency analysis to them. The results give information about the change in signals characteristics and hence some information about the noise or perturbations present. Equivalent representations to the phase and to the Feigenbaum diagrams for digital signals are employed in this case.

Noise-agnostic adaptive image filtering without training references on an evolvable hardware platform

One of the main concerns of evolvable and adaptive systems is the need of a training mechanism, which is normally done by using a training reference and a test input. The fitness function to be optimized during the evolution (training) phase is obtained by comparing the output of the candidate systems against the reference. The adaptivity that this type of systems may provide by re-evolving during operation is especially important for applications with runtime variable conditions. However, fully automated self-adaptivity poses additional problems. For instance, in some cases, it is not possible to have such reference, because the changes in the environment conditions are unknown, so it becomes difficult to autonomously identify which problem requires to be solved, and hence, what conditions should be representative for an adequate re-evolution. In this paper, a solution to solve this dependency is presented and analyzed. The system consists of an image filter application mapped on an evolvable hardware platform, able to evolve using two consecutive frames from a camera as both test and reference images. The system is entirely mapped in an FPGA, and native dynamic and partial reconfiguration is used for evolution. It is also shown that using such images, both of them being noisy, as input and reference images in the evolution phase of the system is equivalent or even better than evolving the filter with offline images. The combination of both techniques results in the completely autonomous, noise type/level agnostic filtering system without reference image requirement described along the paper.

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Piezoelectric sensing and non-parametric statistical signal processing for health monitoring of hysteretic dampers used in seismic-resistant structures

The paper proposes a new application of non-parametric statistical processing of signals recorded from vibration tests for damage detection and evaluation on I-section steel segments. The steel segments investigated constitute the energy dissipating part of a new type of hysteretic damper that is used for passive control of buildings and civil engineering structures subjected to earthquake-type dynamic loadings. Two I-section steel segments with different levels of damage were instrumented with piezoceramic sensors and subjected to controlled white noise random vibrations. The signals recorded during the tests were processed using two non-parametric methods (the power spectral density method and the frequency response function method) that had never previously been applied to hysteretic dampers. The appropriateness of these methods for quantifying the level of damage on the I-shape steel segments is validated experimentally. Based on the results of the random vibrations, the paper proposes a new index that predicts the level of damage and the proximity of failure of the hysteretic damper

A clustering technique for partial discharge and noise sources identification in power cables by means of waveform parameters

On-line partial discharge (PD) measurements have become a common technique for assessing the insulation condition of installed high voltage (HV) insulated cables. When on-line tests are performed in noisy environments, or when more than one source of pulse-shaped signals are present in a cable system, it is difficult to perform accurate diagnoses. In these cases, an adequate selection of the non-conventional measuring technique and the implementation of effective signal processing tools are essential for a correct evaluation of the insulation degradation. Once a specific noise rejection filter is applied, many signals can be identified as potential PD pulses, therefore, a classification tool to discriminate the PD sources involved is required. This paper proposes an efficient method for the classification of PD signals and pulse-type noise interferences measured in power cables with HFCT sensors. By using a signal feature generation algorithm, representative parameters associated to the waveform of each pulse acquired are calculated so that they can be separated in different clusters. The efficiency of the clustering technique proposed is demonstrated through an example with three different PD sources and several pulse-shaped interferences measured simultaneously in a cable system with a high frequency current transformer (HFCT).

Perceptual learning reflects external noise filtering and internal noise reduction through channel reweighting

To investigate the nature of plasticity in the adult visual system, perceptual learning was measured in a peripheral orientation discrimination task with systematically varying amounts of external (environmental) noise. The signal contrasts required to achieve threshold were reduced by a factor or two or more after training at all levels of external noise. The strong quantitative regularities revealed by this novel paradigm ruled out changes in multiplicative internal noise, changes in transducer nonlinearites, and simple attentional tradeoffs. Instead, the regularities specify the mechanisms of perceptual learning at the behavioral level as a combination of external noise exclusion and stimulus enhancement via additive internal noise reduction. The findings also constrain the neural architecture of perceptual learning. Plasticity in the weights between basic visual channels and decision is sufficient to account for perceptual learning without requiring the retuning of visual mechanisms.

Titration of chaos with added noise

Deterministic chaos has been implicated in numerous natural and man-made complex phenomena ranging from quantum to astronomical scales and in disciplines as diverse as meteorology, physiology, ecology, and economics. However, the lack of a definitive test of chaos vs. random noise in experimental time series has led to considerable controversy in many fields. Here we propose a numerical titration procedure as a simple “litmus test” for highly sensitive, specific, and robust detection of chaos in short noisy data without the need for intensive surrogate data testing. We show that the controlled addition of white or colored noise to a signal with a preexisting noise floor results in a titration index that: (i) faithfully tracks the onset of deterministic chaos in all standard bifurcation routes to chaos; and (ii) gives a relative measure of chaos intensity. Such reliable detection and quantification of chaos under severe conditions of relatively low signal-to-noise ratio is of great interest, as it may open potential practical ways of identifying, forecasting, and controlling complex behaviors in a wide variety of physical, biomedical, and socioeconomic systems.

Rectification and signal averaging of weak electric fields by biological cells.

Oscillating electric fields can be rectified by proteins in cell membranes to give rise to a dc transport of a substance across the membrane or a net conversion of a substrate to a product. This provides a basis for signal averaging and may be important for understanding the effects of weak extremely low frequency (ELF) electric fields on cellular systems. We consider the limits imposed by thermal and "excess" biological noise on the magnitude and exposure duration of such electric field-induced membrane activity. Under certain circumstances, the excess noise leads to an increase in the signal-to-noise ratio in a manner similar to processes labeled "stochastic resonance." Numerical results indicate that it is difficult to reconcile biological effects with low field strengths.

Signal Processing Techniques for Chipless UWB RFID Thermal Threshold Detector Detection.

This letter presents signal processing techniques to detect a passive thermal threshold detector based on a chipless time-domain ultrawideband (UWB) radio frequency identification (RFID) tag. The tag is composed by a UWB antenna connected to a transmission line, in turn loaded with a biomorphic thermal switch. The working principle consists of detecting the impedance change of the thermal switch. This change occurs when the temperature exceeds a threshold. A UWB radar is used as the reader. The difference between the actual time sample and a reference signal obtained from the averaging of previous samples is used to determine the switch transition and to mitigate the interferences derived from clutter reflections. A gain compensation function is applied to equalize the attenuation due to propagation loss. An improved method based on the continuous wavelet transform with Morlet wavelet is used to overcome detection problems associated to a low signal-to-noise ratio at the receiver. The average delay profile is used to detect the tag delay. Experimental measurements up to 5 m are obtained.

Animal visual systems and the evolution of color patterns: Sensory processing illuminates signal evolution

Animal color pattern phenotypes evolve rapidly. What influences their evolution? Because color patterns are used in communication, selection for signal efficacy, relative to the intended receiver's visual system, may explain and predict the direction of evolution. We investigated this in bowerbirds, whose color patterns consist of plumage, bower structure, and ornaments and whose visual displays are presented under predictable visual conditions. We used data on avian vision, environmental conditions, color pattern properties, and an estimate of the bowerbird phylogeny to test hypotheses about evolutionary effects of visual processing. Different components of the color pattern evolve differently. Plumage sexual dimorphism increased and then decreased, while overall (plumage plus bower) visual contrast increased. The use of bowers allows relative crypsis of the bird but increased efficacy of the signal as a whole. Ornaments do not elaborate existing plumage features but instead are innovations (new color schemes) that increase signal efficacy. Isolation between species could be facilitated by plumage but not ornaments, because we observed character displacement only in plumage. Bowerbird color pattern evolution is at least partially predictable from the function of the visual system and from knowledge of different functions of different components of the color patterns. This provides clues to how more constrained visual signaling systems may evolve.

Is the method of signal analysis and test selection important for measuring standing balance in subjects with persistent whiplash?

Dizziness and or unsteadiness, associated with episodes of loss of balance, are frequent complaints in those suffering from persistent problems following a whiplash injury. Research has been inconclusive with respect to possible aetiology, discriminative tests and analyses used. The aim of this pilot research was to identify the test conditions and the most appropriate method for the analysis of sway that may differentiate subjects with persistent whiplash associated disorders (WAD) from healthy controls. The six conditions of the Clinical Test for Sensory Interaction in Balance was performed in both comfortable and tandem stance in 20 subjects with persistent WAD compared to 20 control subjects. The analyses were carried out using a traditional method of measurement, total sway distance, to results obtained from the use of wavelet analysis. Subjects with WAD were significantly less able to complete the tandem stance tests on a firm surface than controls. In comfortable stance, using wavelet analysis, significant differences between subjects with WAD and the control group were evident in total energy of the trace for all test conditions apart from eyes open on the firm surface. In contrast, the results of the analysis using total sway distance revealed no significant differences between groups across all six conditions. Wavelet analysis may be more appropriate for detecting disturbances in balance in whiplash subjects because the technique allows separation of the noise from the underlying systematic effect of sway. These findings will be used to direct future studies on the aeitiology of balance disturbances in WAD. (c) 2004 Elsevier B.V. All rights reserved.

The performance of the maximum ratio combining method in correlated Rician-fading channels for antenna-diversity signal combining

The performance of the maximum ratio combining method for the combining of antenna-diversity signals in correlated Rician-fading channels is rigorously studied. The distribution function of the normalized signal-to-noise ratio (SNR) is expanded in terms of a power series and calculated numerically. This power series can easily take into account the signal correlations and antenna gains and can be applied to any number of receiving antennas. An application of the method to dual-antenna diversity systems produces useful distribution curves for the normalized SNR which can be used to find the diversity gain. It is revealed that signal correlation in Rician-fading channels helps to increase the diversity gain rather than to decrease it as in the Rayleigh fading channels. It is also shown that with a relative strong direct signal component, the diversity gain can be much higher than that without a direct signal component.

Habitat type and density influence vocal signal design in satin bowerbirds

This study provided a thorough test of the acoustic adaptation hypothesis using a within-species comparison of call structure involving a wide range of habitat types, an objective measure of habitat density and direct measures of habitat-related attenuation. The structure of the bower advertisement call of the satin bowerbird was measured in 16 populations from throughout the species' range and related to the habitat type and density at each site. Transmission of white noise, pure tones and different bowerbird dialects was measured in five of six habitat types inhabited by satin bowerbirds. Bowerbird advertisement call structure converged in similar habitats but diverged among different habitats; this pattern was apparent at both continent-wide and local geographical scales. Bowerbirds' call structures differed with changes in habitat density, consistent with the acoustic adaptation hypothesis. Lower frequencies and less frequency modulation were utilized in denser habitats such as rainforest and higher frequencies and more frequency modulation were used in the more open eucalypt-dominated habitats. The white noise and pure tone transmission measurements indicated that different habitats varied in their sound transmission properties in a manner consistent with the observed variation in satin bowerbird vocalizations. There was no effect of geographical proximity of recording locations, nor was there the predicted inverse relationship between frequency and body size. These findings indicate that the transmission qualities of different habitats have had a major influence on variation in vocal phenotypes in this species. In addition, previously published molecular data for this species suggest that there is no effect of genetic relatedness on call similarity among satin bowerbird populations.

Adaptive Signal Processing for Power Line Communications

This thesis represents a significant part of the research activity conducted during the PhD program in Information Technologies, supported by Selta S.p.A, Cadeo, Italy, focused on the analysis and design of a Power Line Communications (PLC) system. In recent times the PLC technologies have been considered for integration in Smart Grids architectures, as they are used to exploit the existing power line infrastructure for information transmission purposes on low, medium and high voltage lines. The characterization of a reliable PLC system is a current object of research as well as it is the design of modems for communications over the power lines. In this thesis, the focus is on the analysis of a full-duplex PLC modem for communication over high-voltage lines, and, in particular, on the design of the echo canceller device and innovative channel coding schemes.