Analysis Of Spectrum Characteristics Research Articles

Spectrum Characteristics Analysis and Recognition of CHD Heart Sound in Five Auscultation Locations

Cardiac Auscultation is widely used in the diagnosis of congenital heart disease (CHD) due to its non-invasive and cost-effective procedure. Heart sound analysis can provide effective auxiliary diagnosis information and aid in automatically screening patients. However, there are different signal spectrum characteristics in different auscultation locations, and there are no unified standards in the selection of auscultation locations during the heart sound analysis. This paper addresses the problem of auscultation locations and the selection of spectrum characteristics in the heart sound identification of CHD patients. 385 cases of normal and CHD heart sound signals were used to extract three groups of representative spectral features: Power Spectral Density (PSD), Mel-Frequency Cepstrum Coefficients (MFCCs) and Instantaneous Frequency Cumulative(IFC) from five different auscultation locations which are Aortic area(A), Pulmonic area(P), Tricuspid area(T), Mitral area(M), and Second aortic valve area(E). Significance detections based on p-value and Gaussian kernel support vector machine (SVM) were used to test these spectrum characteristics in five auscultation locations. The results show that the spectrum energy and the difference of auscultation areas concentrated within the frequency range of 20-150Hz. There is no statistical significance in terms of the spectrum characteristics of CHD in area A (p>0.05) compared with the statistical significance in other auscultation areas (p<0.01). The classification performance of the SVM method that uses spectrum characteristics of area E was the best overall. The experiment and analysis results show that, in CHD heart sound recognition, E-area signals have the best recognition effect, signals from TMP areas could be used as a reference, and A-area signals should be used with cautions. This discovery provides a practical guide to the clinical auscultation and signal processing of Congenital Heart Disease.

Modulation spectrum analysis and optimization for closed-loop RFOG under dynamic condition

In this paper, the spectrum characteristics of the closed-loop RFOG, modulated by the digital sine and bipolar serrodyne wave, is analyzed under the dynamic condition. It is verified that the serious spectrum overlapping between the CCW and CW loops would be induced within a certain rotation rate range, which would increase the backscatter noise. Experimental tests indicate that the serious spectrum overlapping could more than double the standard deviation of gyro output signal, which badly deteriorates the gyro’s performance. According to the spectrum characteristics analysis result, to reduce the spectrum overlapping induced backscatter noise under the dynamic condition, a noise suppressing algorithm is proposed. This algorithm is realized by switching the initial reset frequency of the bipolar serrodyne wave at a crucial rotation rate to keep an enough frequency difference between the two modulation spectrums’ main harmonic components. Experimental test shows that when this algorithm is used, the decreased ratio of the standard deviation for gyro output signal can reach to about 70.5% at the rotation rates corresponding to the serious spectrum overlapping.

Hourly ambient air humidity fluctuation evaluation and forecasting based on the least-squares Fourier-model

Air humidity is one important measurement parameter involved in a wide range of fields of science and engineering. This study addresses Fourier-series-based evaluation and prediction of hourly ambient air humidity fluctuation. It is shown that hourly ambient humidity fluctuation displays a significant 24-hour cyclical variation. Then on the basis of daily periodic extension for hourly ambient air humidity fluctuation, a finite Fourier-series-based evaluation model is introduced for describing its hourly fluctuation. The Fourier-based analysis in its conventional form, however, cannot be straightly applicable to prediction. Then in combination with the least-squares method for coefficient-seeking based on finite observations of hourly air humidity, the extended version of the Fourier-series model in the least-squares is proposed for forecasting. The proposed Fourier-series-based method is applied to experiments of evaluating and forecasting hourly air humidity fluctuations at different monitoring stations with satisfying results. The experimental results, further mathematical analysis of the conjugate symmetry property and spectrum characteristic analysis for the Fourier-series involved in the Fourier-based model indicate that daily 24-hour air humidity fluctuation is well described by about 12-term harmonics and the extended Fourier-series forecasting model predicts the hourly humidity fluctuation best fitting with less than 6-term harmonics.

An adaptive three-phase reclosure scheme for shunt reactor-compensated transmission lines based on the change of current spectrum

In this paper, a new three-phase adaptive reclosing scheme for transmission lines with shunt reactors is proposed to identify fault nature and determine the arc extinction time under the single and double-phase-to-ground faults. According to the fact that the faulted phase currents of shunt reactors contain only one oscillating frequency before the fault extinction and contain other two different oscillating frequencies when the fault is extinguished, this change of current frequency can be used to distinguish transient faults. When sampling rate is an integral multiple of the faulted phase current frequency of shunt reactors under permanent faults, an abrupt increase of currents even harmonics which is caused by spectral leakage of the DFT algorithm under non-synchronous sampling can lead to identify transient faults and three-phase reclosing. Electromagnetic Transient Program simulation results verify the correctness of the frequency spectrum characteristic analysis of the faulted currents of shunt reactor. The feasibility of the proposed scheme is also tested under different fault condition.

Prediction Model of Machining Failure Trend Based on Large Data Analysis

The mechanical processing has high complexity, strong coupling, a lot of control factors in the machining process, it is prone to failure, in order to improve the accuracy of fault detection of large mechanical equipment, research on fault trend prediction requires machining, machining fault trend prediction model based on fault data. The characteristics of data processing using genetic algorithm K mean clustering for machining, machining feature extraction which reflects the correlation dimension of fault, spectrum characteristics analysis of abnormal vibration of complex mechanical parts processing process, the extraction method of the abnormal vibration of complex mechanical parts processing process of multi-component spectral decomposition and empirical mode decomposition Hilbert based on feature extraction and the decomposition results, in order to establish the intelligent expert system for the data base, combined with large data analysis method to realize the machining of the Fault trend prediction. The simulation results show that this method of fault trend prediction of mechanical machining accuracy is better, the fault in the mechanical process accurate judgment ability, it has good application value analysis and fault diagnosis in the machining process.

Analytic Study on the Characteristics of Infrared Spectrum of Oil Pool Flame.

In virtue of the severity and scale of the pollution caused by oil pool flame, space remote sensing can provide us a new way of monitoring in real time the oil pool flame pollution. Space remote sensing monitoring is based on the analysis of target spectrum characteristics. Due to lack of adequate researches on the characteristics of infrared spectrum of oil pool flame, this paper carries out the analytical study on flame spectrums of several types of oil, mixed oil and other combustible objects in outdoor space by establishing all-flame infrared testing system with the spectrum range of 1～14 μm. The results show that the spectrum curves of oil pool flame of 92# gasoline, 95# gasoline, 0# diesel, aviation kerosene and lube have similar features, that there exist characteristics emission peaks at the area of certain wave lengths—H2O characteristics emission peak for 1.1, 2.4, 2.8 and 6.3 μm, CO2 characteristics emission peak for 4.2 and 4.5 μm, C—H stretching vibration emission peak for 3.4 μm, and no obvious characteristics peak for spectrum curves of 6.3 μm and above; that there is no obvious difference in the spectrum of oil pool flame among the mixtures of 92# gasoline and 0# diesel at different proportions, that the comparison of the flame spectrum of 92# gasoline with that of wood and paper shows that there appears a characteristics emission peak at 3.4 μm; that though the flame spectrum of alcohol has similar radiated emission near 3.4 μm, the proportion of its radiation intensity to that of CO2 at 4.5 μm is far less than that for the flame spectrum of 92# gasoline; that the flame spectrum of honeycomb briquette is similar to that of gray body radiation. The differences in flame spectrum among all kinds of combustible materials are closely linked to their chemical compositions and burning reaction mechanisms. Comparative analysis on the spectrum characteristics at continuous area, intermission area and flue gas area shows that C—H stretching vibration peak only exists in continuous area, which proves that the emission peak is caused by the combustible reaction of oil and gas. This result is in line with the mechanism of oil pool combustion reaction. The experimental conclusion is of great significance in the remote-sensing recognition of oil pool flame based on the analysis of spectrum characteristics.

Research on remote sensing monitoring model of soil salinization based on spectrum characteristic analysis

To establish the remote sensing monitoring model for soil salinization,the authors chose the typical soil salinization area in Pingluo County of Ningxia as the study area,and measured the spectral data in the field. These data,together with the values of p H and salinity measured in the laboratory,were taken as the basic data.Hyperspectral data processing method was used to analyze the spectral characteristics of different levels of soil salinization. Spectral data were transformed with 11 different approaches,such as reciprocal,logarithm,root mean square and their first order differentials. After the transformation,the correlation analysis was carried out between the obtained soil spectra and soil salinity. The most sensitive band was selected,and the field spectral sensitive band and soil salinity were used and the multiple linear regression was employed to establish the spectral quantitative models for evaluating the soil salinization degrees. The results show that the reciprocal first order differential of measured soil spectral is most sensitive to soil salinization degrees. The spectral quantitative models based on the wavelengths of 940 nm and 1 094 nm are the best.

Support Vector Machine Based Method of Earthed Fault Location in Neutral Un-Effectual Grounded Power System

Abstract. Neutral un-effectual grounded system (NUGS) is widely used in Chinese medium voltage power distribution network. However, existing earthed fault location methods in NUGS are not satisfactory in practical application due to weak fault current and unstable arc. Based on analysis of spectrum characteristics of current signals in single-phase earthed fault feeder, this paper proposed an earthed fault location method based on support vector machine (SVM). Firstly, the zero sequence current signal was sampled, and its spectrum was gotten by discrete Fourier transform. Secondly, the three dimensional feature vector that constituted by fundament, harmonic, inter harmonic component, had been extracted as the input of SVM. Furthermore, the SVM was trained with the samples obtained by simulation under different fault distance, different fault resistance and different fault close angle. Finally, the earthed fault feeder is selected using the trained SVM. The simulation results indicate that the fault location by the presented method is more precise.

Spatial-Frequency Spectrum Characteristics Analysis With Different Lift-Offs for Microwave Nondestructive Testing and Evaluation Using Itakura-Saito Nonnegative Matrix Factorization

Microwave nondestructive testing and evaluation (NDTE 2) a full mathematical derivation for modeling the spatial-frequency characteristics in the presence of defects and without defects is provided; and 3) a spatial-frequency feature extraction algorithm using the Itakura-Saito nonnegative matrix factorization is developed and investigated. The algorithm has the unique property of scale-invariance, which enables extraction of spatial-frequency features that are characterized by large dynamic ranges of energy. To evaluate the proposed technique, four defects in an aluminium plate with different depths (from 2 to 8 mm) and one tiny defect on a steel sample (0.45-mm width and 0.43-mm depth) have been examined. Experimental results have demonstrated that the proposed microwave NDT&E technique is capable of detecting defects at large lift-offs, with the potential of estimating the width and depth of defects, as well as classifying the different defect and nondefect areas.

倾斜光纤光栅谱特性

Based on the mode coupling theory of the titled fiber Bragg grating with the numerical analysis methods,the tilted angle and modulation index on the effection of tilted fiber grating reflectivity spectra of front-back core mode coupling and characteristics of tilted fiber grating reflectivity and transmission spectra for core mode and radiation mode coupling on the condition of different tilted angle,index modulation and grating lengths for different polarization are discussed.The results of the study show that different incident lights with different polarizations are exactly the same for front and back core mode couplings.Incident light of s polarization and p polarization state should be taken into account for the radiation mode coupling,because reflectivity spectra envelope are affected by modulation of extinction coefficient and incident light with different polarizations have different extinction coefficients.Moreover,the greater tilted angle is,the more differences for the extinction coefficient of the incident light with difference ploarization is.

Waterline Extraction and DEM Reconstruction in Chongming Dongtan

Ground survey is restricted by the difficulty of access to wide-range and dynamic tidal flat.The lack of terrain handicaps exploration and development of tidal flat.In this article,we selected Chongming Dongtan as an experiment area.On the analysis of spectrum characteristics of multi-temporal remote sensing images(1999~2004),waterlines were extracted from different bands according to tidal conditions.The assignment of an elevation to the waterlines was performed according to two elevation survey profiles.The waterlines labeled elevation were used to construct TINs(Triangulated Irregular Networks).Then an interpolation for each grid elevation was performed in accordance with the associated triangle.Finally,quantitative check of the result was examined according as the other two measurement profiles.The results indicate that the standard deviation of the approach is 0.4 m and 0.7 m,respectively,which eliminates the effects of unavailable tidal height and discrepancy of waterlines on DEM precision.

Spectrum characteristics analysis of microseismic signals transmitting between coal bedding

This study was performed to investigate the propagation law of microseismic signals transmitting along the direction parallel and vertical to the bedding in the process of coal rock rupture under uniaxial compression. Microseismic signals during the whole process of coal-rock deformation fracture until burst failure was tested by using the coal rock rupture microseismic experimental system. The empirical mode decomposition graphic, Hilbert spectrum and time–frequency spectrum were obtained by using Hilbert-Huang Transform or HHT. Also the microseismic signals transmitting along the direction parallel and vertical to the bedding in the process of coal rock rupture were spectrum comparative analyzed with EMD analysis method. Results show that amplitude and velocity of microseismic signals changed very small along the parallel direction to bedding in the process of propagation, but microseismic signals delayed and amplitude weakened obviously along the vertical direction to bedding. Signal delay and signal attenuation were confirmed that bedding impact on microseismic wave transmitting.

Analysis of spectrum characteristics of optical scintillation in stack gas flow

Based on the analysis of spectrum characteristics of intensity fluctuations while light beams pass through stack gas flow in an industrial setting, this paper puts emphasis upon discussing the spectrum of optical intensity fluctuations by the variety of particle concentration in stack gas flow. This paper also gives the primary theoretical explanation of the measurement results in the stack of coal-fired utility boilers. Meanwhile, the cross-correlation formula is given as the theoretical basis of velocity measurement by using particle concentration scintillation.