Fault diagnosis using noise modeling and a new artificial immune system based algorithm

A new fault classification/diagnosis method based on artificial immune system (AIS) algorithms for the structural systems is proposed. In order to improve the accuracy of the proposed method, i.e., higher success rate, Gaussian and non-Gaussian noise generating models are applied to simulate environmental noise. The identification of noise model, known as training process, is based on the estimation of the noise model parameters by genetic algorithms (GA) utilizing real experimental features. The proposed fault classification/diagnosis algorithm is applied to the noise contaminated features. Then, the results are compared to that obtained without noise modeling. The performance of the proposed method is examined using three laboratory case studies in two healthy and damaged conditions. Finally three different types of noise models are studied and it is shown experimentally that the proposed algorithm with non-Gaussian noise modeling leads to more accurate clustering of memory cells as the major part of the fault classification procedure.

A WYNER-ZIV VIDEO CODING METHOD UTILIZING MIXTURE CORRELATION NOISE MODEL

In Wyner-Ziv (WZ) Distributed Video Coding (DVC), correlation noise model is often used to describe the error distribution between WZ frame and the side information. The accuracy of the model can influence the performance of the video coder directly. A mixture correlation noise model in Discrete Cosine Transform (DCT) domain for WZ video coding is established in this paper. Different correlation noise estimation method is used for direct current and alternating current coefficients. Parameter estimation method based on expectation maximization algorithm is used to estimate the Laplace distribution center of direct current frequency band and Mixture Laplace-Uniform Distribution Model (MLUDM) is established for alternating current coefficients. Experimental results suggest that the proposed mixture correlation noise model can describe the heavy tail and sudden change of the noise accurately at high rate and make significant improvement on the coding efficiency compared with the noise model presented by DIStributed COding for Video sERvices (DISCOVER).

Bark-Band Residual Noise Model for Parametric Audio Coding

A Bark-band residual noise model integrated with the human hearing mechanism is proposed to efficiently complement sinusoidal model in parametric audio coding. The time-varying spectrum of the residual noise is retrieved by Bark-scale piecewise constant magnitude estimates along with random phases. In the proposed noise model, Bark bands information is obtained by short-time FFT method and window overlap-add technique is exploited to remove boundary discontinuities. SVQ is also incorporated into parameter quantization process for the low bit-rate coding demand. Simulation results and informal listening tests show that when the sinusoidal model is combined with the Bark-band noise model, better synthesis audio quality can be achieved compared with the original sinusoidal modeling audio codec.

Orbital pacing and secular evolution of lake-level changes reconstructed by sedimentary noise modeling during the Early Jurassic icehouses-(super)greenhouses

Lake-level changes can significantly affect paleoenvironmental evolution,resource occurrence,terrestrial carbon budget,and biodiversity in continental basins.Climate is one of the most critical factors controlling lake-level changes.Paleoclimate of the Early Jurassic has been evidenced by oscillating icehouses to(super)greenhouses with interrupted intermittent extreme climatic events(hyperthermal and cooling),e.g.,the Toarcian oceanic anoxic event(~183 Ma)and the late Pliensbachian cooling event(~185 Ma).Lake-level evolution and hydrologic cycling on Earth’s surface during the Early Jurassic icehouses-to-(super)greenhouses are thus far poorly understood due to a lack of continuous high-resolution nonmarine evidence.Here we present a super-long nonmarine lake level record for this pivotal interval from the early Pliensbachian to Toarcian by sedimentary noise modeling,and construct a 16.7-Myr-long astronomical time scale(174.2 Ma to 190.9 Ma)based on cyclostratigraphy analysis of rock color datasets(CIE b*)of the Qaidam Basin.Our results document lake-level oscillations on a 5-to 10-million-year(Myr)scale which shows a pronounced correlation with long-term climate variation and extreme climatic events,and 1-to 2.5-Myr-scale lake-level changes that are prominently paced by the 2.4-Myr long-eccentricity forcing and the 1.2-Myr obliquity forcing.At the Pliensbachian Stage,the 1.2-Myr-scale lake-level changes are in phase with the coeval sealevel variations.Orbitally forced growth and decay of the ephemeral or permanent ice sheets in polar regions are interpreted to control the synchronous ups-and-downs of continental lake level and global sea level.However,during the Toarcian ice-free greenhouses to(super)greenhouses,the 1.2-Myr-scale lake-level variations show an anti-phase relationship with global sea level,indicating a‘seesaw’interaction between continental reservoirs(lakes and groundwater)and global oceans.The 2.4-Myr longeccentricity cycles mainly regulate variations of lake level and sea level by controlling the growth and decay of small-scale continental ice sheets,which is especially notable during the Pliensbachian Stage.These findings indicate a remarkable transition of hydrological cycling pattern during the Pliensbachian-Toarcian icehouses to(super)greenhouses,which provides new perspectives and evidence for investigating the hypothesis of global sea-level changes(e.g.,glacio-eustasy and aquifer-eustasy)and long-period astronomical forcing in nonmarine stratigraphy.

Model/data comparison of typhoon-generated noise

Ocean noise recorded during a typhoon can be used to monitor the typhoon and investigate the mechanism of the wind- generated noise. An analytical expression for the typhoon-generated noise intensity is derived as a function of wind speed. A ＂bi-peak＂ structure was observed in an experiment during which typhoon-generated noise was recorded. Wind speed dependence and frequency dependence were also observed in the frequency range of 100 Hz-1000 Hz. The model/data comparison shows that results of the present model of 500 Hz and 1000 Hz are in reasonable agreement with the exper- imental data, and the typhoon-generated noise intensity has a dependence on frequency and a power-law dependence on wind speed.

Turbocharger Noise Prediction Using Broadband Noise Source Model

The noise prediction of the turbocharger is studied.The broadband noise source model is employed to predict the near-field noise of the turbocharger.The 3D software Solidworks is adopted to establish the model blades and inlet of turbocharger compressor,then this 3D model is introduced into the software CFD to calculate the flow-field under different inlet shapes,different blades shapes and different clearances between casing and impeller.On the base of the above simulation,the broadband noise source model is employed to calculate and analyze the near-field noise.The calculation shows that compressor static pressure values and the sound power values near the impeller outlet are the largest.Through the noise calculation by using broadband noise source model under different inlet shapes and blade shapes,we find that the noise level of the inlet of cylindrical and cone types are smaller.Compared with the current widespread used backward skewed or radial blades,there is little difference of the noise value of the inlet of the forward skewed blades.

Modeling random telegraph signal noise in CMOS image sensor under low light based on binomial distribution

The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result,the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated,and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures.

Revisiting the nonlinear Gaussian noise model for hybrid fiber spans

We rederive from first principles and generalize the theoretical framework of the nonlinear Gaussian noise model to the case of coherent optical systems with multiple fiber types per span and ideal Nyquist spectra.We focus on the accurate numerical evaluation of the integral for the nonlinear noise variance for hybrid fiber spans.This task consists in addressing four computational aspects:(1)Adopting a novel transformation of variables(other than using hyperbolic coordinates)that changes the integrand to a more appropriate form for numerical quadrature;(2)Evaluating analytically the integral at its lower limit,where the integrand presents a singularity;(3)Dividing the interval of integration into subintervals of size and approximating the integral over each subinterval by using various algorithms;and(4)Deriving an upper bound for the relative error when the interval of integration is truncated in order to accelerate computation.We apply the proposed analytical model to the performance evaluation of coherent optical communications systems with hybrid fiber spans composed of quasi-single-mode and single-mode fiber segments.More specifically,the model is used to optimize the lengths of the optical fiber segments that compose each span in order to maximize the system performance.We check the validity of the optimal fiber segment lengths per span provided by the analytical model by using Monte Carlo simulation,where the Manakov equation is solved numerically using the split-step Fourier method.We show that the analytical model predicts the lengths of the optical fiber segments per span with satisfactory accuracy so that the system performance,in terms of the Q-factor,is within 0.1 dB from the maximum given by Monte Carlo simulation.

A Review of a Study on Disc Brake Noise

With the development of the automotive industry, disc brake noise has become an issue of growing concern to the automotive industry and customers. In this paper, the types of disc brake noise have been discussed. After that, the theories and models that have been proposed as an explanation of brake squeal are reviewed. On the basis of these theories and models, some example simulations of disc brake squeal which use the Finite Element method and mathematical model have been introduced.

Langevin approach with rescaled noise for stochastic channel dynamics in Hodgkin–Huxley neurons

The Langevin approach has been applied to model the random open and closing dynamics of ion channels. It has long been known that the gate-based Langevin approach is not sufficiently accurate to reproduce the statistics of stochastic channel dynamics in Hodgkin–Huxley neurons. Here, we introduce a modified gate-based Langevin approach with rescaled noise strength to simulate stochastic channel dynamics. The rescaled independent gate and identical gate Langevin approaches improve the statistical results for the mean membrane voltage, inter-spike interval, and spike amplitude.

Design and Implementation of a Wideband HF Channel Simulator

The paper presents a wideband high frequency (HF) channel simulator. The simulation consists of a software simulation of a direct-sequence spread-spectrum (DSSS) HF system with RAKE receiver. The validity of the HF channel simulator is demonstrated by the analysis of the scattering function and example results of the simulator. The performance of DS system under HF channel and noise are also presented. The simulation results and theoretical analysis show that a straightforward DS system may properly mitigate the intersymbol interference (ISI) distortion of the HF channel while perform badly under the HF noise and interference.

Multi-scale expression of spatial activity anomalies of earthquakes and its indicative significance on the space and time attributes of strong earthquakes

The noise modei based on 6 trous wavelet algorithm produces a multi-scale expression of image through the combination of wavelet transform and a testing modei of statistical significance. This kind of expression not only gives the formation and location of image structure on different scales, but also eliminates the influence of noise. Since the algorithm does not need any priori hypotheses, it is suitable for the data with complex structure. The research line is employed in this paper to analyze the spatial activity of earthquake. The method of how to recognize and describe the multi-scale space activity of earthquake is emphatically discussed in this paper. Taking typical sequences in Southwest China as research cases, we systematically study the structure characters of spatial activity of earthquake on different scales. Results show that multi-scale space structure to some extent possesses indicative effect on strong epicenters. And the foreshock anomalies of Songpan seismic sequence also reveal interesting pattern during the spatial-temporal evolvement.

A transformed analytical model for thermal noise of FinFET based on fringing field approximation

This paper delineates the effect of nonplanar structure of Fin FETs on noise performance. We demonstrate the thermal noise analytical model that has been inferred by taking into account the presence of an additional inverted region in the extended（underlap） S/D region due to finite gate electrode thickness. Noise investigation includes the effects of source drain resistances which become significant as channel length becomes shorter. In this paper, we evaluate the additional noise caused by three dimensional（3-D） structure of the single fin device and then extended analysis of the multi-fin and multi-fingers structure. The addition of fringe field increases its minimum noise figure and noise resistance of approximately 1 d B and 100Ω respectively and optimum admittance increases to 5.45 mΩ at 20 GHz for a device operating under saturation region. Hence, our transformed model plays a significant function in evaluation of accurate noise performance at circuit level.

Scaling model for a speed-dependent vehicle noise spectrum

Considering the well-known features of the noise emitted by moving sources, a number of vehicle characteristics such as speed, unladen mass, engine size, year of registration, power and fuel were recorded in a dedicated monitoring campaign performed in three different places, each characterized by different number of lanes and the presence of nearby reflective surfaces. A full database of 144 vehicles （cars） was used to identify sta- tistically relevant features. In order to compare the vehicle transit noise in different environmental condition, all 1/3-octave band spectra were normalized and analysed. Un- supervised clustering algorithms were employed to group together spectrum levels with similar profiles. Our results corroborate the well-known fact that speed is the most rele- vant characteristic to discriminate between different vehicle noise spectrum. In keeping with this fact, we present a new approach to predict analytically noise spectra for a given vehicle speed. A set of speed-dependent analytical functions are suggested in order to fit the normalized average spectrum profile at different speeds. This approach can be useful for predicting vehicle speed based purely on its noise spectrum pattern. The present work is complementary to the accurate analysis of noise sources based on the beamforming technique.

Mesh Smoothing Method Based on Local Wave Analysis

As the mesh models usually contain noise data,it is necessary to eliminate the noises and smooth the mesh.But existed methods always lose geometric features during the smoothing process.Hence,the noise is considered as a kind of random signal with high frequency,and then the mesh model smoothing is operated with signal processing theory.Local wave analysis is used to deal with geometric signal,and then a novel mesh smoothing method based on the local wave is proposed.The proposed method includes following steps：Firstly,analyze the principle of local wave decomposition for 1D signal,and expand it to 2D signal and 3D spherical surface signal processing;Secondly,map the mesh to the spherical surface with parameterization,resample the spherical mesh and decompose the spherical signals by local wave analysis;Thirdly,propose the coordinate smoothing and radical radius smoothing methods,the former filters the mesh points＇ coordinates by local wave,and the latter filters the radical radius from their geometric center to mesh points by local wave;Finally,remove the high-frequency component of spherical signal,and obtain the smooth mesh model with inversely mapping from the spherical signal.Several mesh models with Gaussian noise are processed by local wave based method and other compared methods.The results show that local wave based method can obtain better smoothing performance,and reserve more original geometric features at the same time.

Fractal Brownian motion model of ship radiated noise

On the basis of the fractal geometry, a nactional Brownian Motion (FBM) model for the noise radiated by ship was established, under which its fractal dimension has been obtained and the Fractal Characteristic Vector (FCV) was constructed in the fractional Brownian random field (FBRF). By using of them, a new technique of the characteristic analysis for target recognition in the underwater acoustics was presented. A comparative experiment for classification shows us that the FCV can be used as essential quantity by which some defects existing in the methods to do the characteristic extraction elsewhere can be remedied.

An auditory periphery model for improving narrow-band noise recognition rate of underwater targets

The recognition rate of the auditory periphery features decreases when the model is used to identify underwater targets in practice. To solve this problem, an improved method based on Gammatone filter bank is proposed. Firstly, after the reason of the decreasing of the recognition results is analyzed, the mechanism of multichannel data acquisition in acoustic engineering may narrow down signal frequency range, which leads to time-frequency features distortion. Secondly, the Gammatone filter bank is implemented to simulate frequency decom- position characteristics of human ear basilar membrane. Since the class information of the underwater noise signal is mostly contained in low frequency range, the auditory features of the conventional model are interpolated and the channel number of the filter bank and the central frequency of each frequency band are adjusted accordingly to obtain a 27-dimensional feature vector of the narrow-band target signal. The adjusted model may reflect the target＇s time- frequency feature more precisely. Finally, the performance of the auditory features is tested by a Neural Network classifier. The experiment results show that the modified auditory model is more effective than the conventional ones. The major information contained in broadband signals is reserved and the classification ability for real targets is further enhanced. The recog- nition results are increased from 82.59% to 88.80%. The modified auditory features effectively improve the recognition rate for underwater target radiated noise signals.

General noise support vector regression with non-constant uncertainty intervals for solar radiation prediction

General noise cost functions have been recently proposed for support vector regression(SVR). When applied to tasks whose underlying noise distribution is similar to the one assumed for the cost function, these models should perform better than classical -SVR. On the other hand, uncertainty estimates for SVR have received a somewhat limited attention in the literature until now and still have unaddressed problems. Keeping this in mind,three main goals are addressed here. First, we propose a framework that uses a combination of general noise SVR models with naive online R minimization algorithm(NORMA) as optimization method, and then gives nonconstant error intervals dependent upon input data aided by the use of clustering techniques. We give theoretical details required to implement this framework for Laplace, Gaussian, Beta, Weibull and Marshall–Olkin generalized exponential distributions. Second, we test the proposed framework in two real-world regression problems using data of two public competitions about solar energy. Results show the validity of our models and an improvement over classical -SVR. Finally, in accordance with the principle of reproducible research, we make sure that data and model implementations used for the experiments are easily and publicly accessible.

A small signal coupling model for predicting the coupling between LNAs

A small signal coupling model is developed to analyze the coupling between two LNAs. The mutual inductance between the adjacent on-chip inductors is considered responsible for this coupling. A set of formulas have been derived to quantitatively predict the coupling effects. Based on our analysis, a quick estimation can be made to see which pair of inductors plays a key role in evaluating the coupling between the LNAs. Source inductors of two LNAs are placed closely while the load inductors are far apart according to the analysis. To validate the proposed theory, two 2 GHz LNAs are fabricated. The LNAs have a peak gain of 18 dB and NF of 1.4 dB. The coupling between the LNAs is –30 dB.

Multiple Input Multiple Output CDSK Chaotic Communication System and Its Performance Analysis

This paper propose a novel noncoherent chaotic com- munication scheme named multiple-input multiple-output correlation-delay-shill- keying （MIMO-CDSK）. In this scheme, multiple antennas are employed to strengthen the robustness in transmission, and to get more diversity gain. The bit error rate （BER） of the MIMO-CDSK is studied analytically in AWGN channel model and multipath fading channel model. The theory and simulation results show that, the performance gain can be obtained with multiple antennas allocated in the transmitter and receiver. Moreover, it is observed that MIMO-CDSK system can effectively reduce the multipath interference.