Singular spectrum analysis is widely used in geodetic time series analysis.However,when extracting time-varying periodic signals from a large number of Global Navigation Satellite System(GNSS)time series,the selection...Singular spectrum analysis is widely used in geodetic time series analysis.However,when extracting time-varying periodic signals from a large number of Global Navigation Satellite System(GNSS)time series,the selection of appropriate embedding window size and principal components makes this method cumbersome and inefficient.To improve the efficiency and accuracy of singular spectrum analysis,this paper proposes an adaptive singular spectrum analysis method by combining spectrum analysis with a new trace matrix.The running time and correlation analysis indicate that the proposed method can adaptively set the embedding window size to extract the time-varying periodic signals from GNSS time series,and the extraction efficiency of a single time series is six times that of singular spectrum analysis.The method is also accurate and more suitable for time-varying periodic signal analysis of global GNSS sites.展开更多
The uncertainty of nuclide libraries in the analysis of the gamma spectra of low-and intermediate-level radioactive waste(LILW)using existing methods produces unstable results.To address this problem,a novel spectral ...The uncertainty of nuclide libraries in the analysis of the gamma spectra of low-and intermediate-level radioactive waste(LILW)using existing methods produces unstable results.To address this problem,a novel spectral analysis method is proposed in this study.In this method,overlapping peaks are located using a continuous wavelet transform.An improved quadratic convolution method is proposed to calculate the widths of the peaks and establish a fourth-order filter model to estimate the Compton edge baseline with the overlapping peaks.Combined with the adaptive sensitive nonlinear iterative peak,this method can effectively subtracts the background.Finally,a function describing the peak shape as a filter is used to deconvolve the energy spectrum to achieve accurate qualitative and quantitative analyses of the nuclide without the aid of a nuclide library.Gamma spectrum acquisition experiments for standard point sources of Cs-137 and Eu-152,a segmented gamma scanning experiment for a 200 L standard drum,and a Monte Carlo simulation experiment for triple overlapping peaks using the closest energy of three typical LILW nuclides(Sb-125,Sb-124,and Cs-134)are conducted.The results of the experiments indicate that(1)the novel method and gamma vision(GV)with an accurate nuclide library have the same spectral analysis capability,and the peak area calculation error is less than 4%;(2)compared with the GV,the analysis results of the novel method are more stable;(3)the novel method can be applied to the activity measurement of LILW,and the error of the activity reconstruction at the equivalent radius is 2.4%;and(4)The proposed novel method can quantitatively analyze all nuclides in LILW without a nuclide library.This novel method can improve the accuracy and precision of LILW measurements,provide key technical support for the reasonable disposal of LILW,and ensure the safety of humans and the environment.展开更多
Viscoelastic damper is an effective passive damping device,which can reduce the seismic response of the structure by increasing the damping and dissipating the vibration energy of structures.It has a wide application ...Viscoelastic damper is an effective passive damping device,which can reduce the seismic response of the structure by increasing the damping and dissipating the vibration energy of structures.It has a wide application prospect in actual structural vibration control because of simple device and economical material.In view of the poor seismic behaviors of assembled frame structure connections,various energy dissipation devices are proposed to improve the seismic performance.The finite element numerical analysis method is adopted to analyze relevant energy dissipation structural parameters.The response spectrum of a 7-story assembled frame structure combined the ordinary steel support,ordinary viscoelastic damper,and viscoelastic damper with displacement amplification device is analyzed.The analysis results show that the mechanical behavior of assembled frame structure with ordinary steel supports are not significantly different from those without energy dissipation devices.The assembled frame structure with viscoelastic damper has better seismic performance and energy dissipation,especially for the viscoelastic damper with displacement amplification devices.The maximum value of inter-story displacement angle decreases by 32.24%;the maximum floor displacement decreases by 31.91%,and the base shear decreases by 13.62%compared with the assembled frame structures without energy dissipation devices.The results show that the seismic fortification ability of the structure is significantly improved,and the overall structure is more uniformly stressed.The damping structure with viscoelastic damper mainly reduces the dynamic response of the structure by increasing the damping coefficient,rather than by changing the natural vibration period of the structure.This paper provides an effective theoretical basis and reference for improving the energy dissipation system and the seismic performance of assembled frame structures.展开更多
The power output state of photovoltaic power generation is affected by the earth’s rotation and solar radiation intensity.On the one hand,its output sequence has daily periodicity;on the other hand,it has discrete ra...The power output state of photovoltaic power generation is affected by the earth’s rotation and solar radiation intensity.On the one hand,its output sequence has daily periodicity;on the other hand,it has discrete randomness.With the development of new energy economy,the proportion of photovoltaic energy increased accordingly.In order to solve the problem of improving the energy conversion efficiency in the grid-connected optical network and ensure the stability of photovoltaic power generation,this paper proposes the short-termprediction of photovoltaic power generation based on the improvedmulti-scale permutation entropy,localmean decomposition and singular spectrum analysis algorithm.Firstly,taking the power output per unit day as the research object,the multi-scale permutation entropy is used to calculate the eigenvectors under different weather conditions,and the cluster analysis is used to reconstruct the historical power generation under typical weather rainy and snowy,sunny,abrupt,cloudy.Then,local mean decomposition(LMD)is used to decompose the output sequence,so as to extract more detail components of the reconstructed output sequence.Finally,combined with the weather forecast of the Meteorological Bureau for the next day,the singular spectrumanalysis algorithm is used to predict the photovoltaic classification of the recombination decomposition sequence under typical weather.Through the verification and analysis of examples,the hierarchical prediction experiments of reconstructed and non-reconstructed output sequences are compared.The results show that the algorithm proposed in this paper is effective in realizing the short-term prediction of photovoltaic generator,and has the advantages of simple structure and high prediction accuracy.展开更多
Part variation characterization is essential to analyze the variation propagation in flexible assemblies. Aiming at two governing types of surface variation,warping and waviness,a comprehensive approach of geometric c...Part variation characterization is essential to analyze the variation propagation in flexible assemblies. Aiming at two governing types of surface variation,warping and waviness,a comprehensive approach of geometric covariance modeling based on hybrid polynomial approximation and spectrum analysis is proposed,which can formulate the level and the correlation of surface variations accurately. Firstly,the form error data of compliant part is acquired by CMM. Thereafter,a Fourier-Legendre polynomial decomposition is conducted and the error data are approximated by a Legendre polynomial series. The weighting coefficient of each component is decided by least square method for extracting the warping from the surface variation. Consequently,a geometrical covariance expression for warping deformation is established. Secondly,a Fourier-sinusoidal decomposition is utilized to approximate the waviness from the residual error data. The spectrum is analyzed is to identify the frequency and the amplitude of error data. Thus,a geometrical covariance expression for the waviness is deduced. Thirdly,a comprehensive geometric covariance model for surface variation is developed by the combination the Legendre polynomials with the sinusoidal polynomials. Finally,a group of L-shape sheet metals is measured along a specific contour,and the covariance of the profile errors is modeled by the proposed method. Thereafter,the result is compared with the covariance from two other methods and the real data. The result shows that the proposed covariance model can match the real surface error effectively and represents a tighter approximation error compared with the referred methods.展开更多
An accurate landslide displacement prediction is an important part of landslide warning system. Aiming at the dynamic characteristics of landslide evolution and the shortcomings of traditional static prediction models...An accurate landslide displacement prediction is an important part of landslide warning system. Aiming at the dynamic characteristics of landslide evolution and the shortcomings of traditional static prediction models, this paper proposes a dynamic prediction model of landslide displacement based on singular spectrum analysis(SSA) and stack long short-term memory(SLSTM) network. The SSA is used to decompose the landslide accumulated displacement time series data into trend term and periodic term displacement subsequences. A cubic polynomial function is used to predict the trend term displacement subsequence, and the SLSTM neural network is used to predict the periodic term displacement subsequence. At the same time, the Bayesian optimization algorithm is used to determine that the SLSTM network input sequence length is 12 and the number of hidden layer nodes is 18. The SLSTM network is updated by adding predicted values to the training set to achieve dynamic displacement prediction. Finally, the accumulated landslide displacement is obtained by superimposing the predicted value of each displacement subsequence. The proposed model was verified on the Xintan landslide in Hubei Province, China. The results show that when predicting the displacement of the periodic term, the SLSTM network has higher prediction accuracy than the support vector machine(SVM) and auto regressive integrated moving average(ARIMA). The mean relative error(MRE) is reduced by 4.099% and 3.548% respectively, while the root mean square error(RMSE) is reduced by 5.830 mm and 3.854 mm respectively. It is concluded that the SLSTM network model can better simulate the dynamic characteristics of landslides.展开更多
Due to non-saturating magnetoresistance(MR)and the special compensation mechanism,the Weyl semimetal Ta As single crystal has attracted considerable attention in condensed matter physics.Herein,we use maximum entropy ...Due to non-saturating magnetoresistance(MR)and the special compensation mechanism,the Weyl semimetal Ta As single crystal has attracted considerable attention in condensed matter physics.Herein,we use maximum entropy mobility spectrum analysis(MEMSA)to extract charge carrier information by fitting the experimentally measured longitudinal and transverse electric transport curves of Ta As.The carrier types and the number of bands are obtained without any hypothesis.Study of the temperature dependence shows details of carrier property evolution.Our quantitative results explain the nonsaturated magnetoresistance and Hall sign change phenomena of TaAs.展开更多
The phase difference Δξ between locked islands(2/1 and 3/1) has been found to influence the heat transport on the thermal quench during disruptions by numerical modeling [Hu Q et al 2019Nucl.Fusion 59,016005].To ver...The phase difference Δξ between locked islands(2/1 and 3/1) has been found to influence the heat transport on the thermal quench during disruptions by numerical modeling [Hu Q et al 2019Nucl.Fusion 59,016005].To verify this experimentally,a set of resonant magnetic perturbation(RMP) coils is required to excite coupled magnetic islands with different Δξ.The spectrum analysis shows that the current RMP coils on J-TEXT can only produce sufficient 2/1 and 3/1RMP fields with a limited phase difference of Δξ∈[-75°,75°].In order to broaden the adjustable range of Δξ,a set of coils on the high field side(HFS) is proposed to generate 2/1 and 3/1 RMP fields with Δξ=180°.As a result,RMPs with adjustable Δξ∈[-180°,180°] and sufficient amplitudes could be achieved by applying the HFS coils and the low field side(LFS)coils.This work provides a feasible solution for flexible adjustment of the phase difference between m and m+1 RMP,which might facilitate the study of major disruptions and their control.展开更多
We present the research results on new CCD spectroscopic observations of three chromospherically active binary stars (BY Dra class), which were obtained by means of Coude echelle spectrograph fed by the 2 16m telescop...We present the research results on new CCD spectroscopic observations of three chromospherically active binary stars (BY Dra class), which were obtained by means of Coude echelle spectrograph fed by the 2 16m telescope at Beijing Astronomical Observatory. These spectrum images were reduced according to the standard fashion using IRAF package. With the aid of stellar model atmosphere, we have analyzed these spectra and derived the average metal abundance and Li abundance of three systems. Using two special spectral lines, we have also discussed the chromospheric activity indicators of them.展开更多
The realization of automatic anomaly detection of respiratory motion could be very useful to prevent accidental damage during radiation therapy. In this paper, we proposed an automatic anomaly detection method using s...The realization of automatic anomaly detection of respiratory motion could be very useful to prevent accidental damage during radiation therapy. In this paper, we proposed an automatic anomaly detection method using singular value decomposition analysis. Before applying this method, the investigator needs a normal respiratory motion data of a patient. From these data, a trajectory matrix representing normal time-series feature is created. Decomposing the matrix, we obtained the feature of normal time series. Then, we applied the same procedure to real-time data and obtained real-time features. Calculating the similarity of those feature matrixes, an anomaly score was obtained. Patient motion was observed by a depth camera. In our simulation, two types of motion e.g. cough and sudden stop of breathing were successfully detected, while gradual change of respiratory cycle frequency was not detected clearly.展开更多
Electrical power generation from wind technology is the most rapidly growing technology due to its ample characteristics.Nevertheless,because of its stochastic feature,it has the unnecessary impact on the operations a...Electrical power generation from wind technology is the most rapidly growing technology due to its ample characteristics.Nevertheless,because of its stochastic feature,it has the unnecessary impact on the operations and stability of the power grid system.The fluctuation of the grid frequency problem,for example,is more pronounced.The fluctuation of the frequency in turn impacts even the collapse of the power system.To minimize such problems,a droop-vector control strategy applied on a doubly-fed induction machine based(DFIM)variable speed pumped storage(VSPS)system is proposed in this paper.This method is should be used as a wind power fluctuation compensation solution in the wind farm-grid integration system.The system model is made on the basis of the technique called a phasor model.The frequency spectrum analysis approach is used in the VSPS plant for determining the dynamic performances of the grid in case of contingencies including wind power fluctuation compensation.The software platform MATLAB/Simulink is used for verifying the performance of the proposed system.The results show that the method of the frequency spectrum analysis technique is effective for determining the wind power fluctuation and stability requirements in large power networks.The control strategy proposed in this paper implementing the VSC-DFIM based VSPS plant integrated with the power gird and wind farm network achieves a well-controlled power flow and stable grid frequency with the deviations being in acceptable ranges.展开更多
Sampled fiber grating is a special superstructure fiber Bragg grating with a wide range of applications in many fields.In this work,based on drawing tower in-line fabrication system,a new preparation method of the sam...Sampled fiber grating is a special superstructure fiber Bragg grating with a wide range of applications in many fields.In this work,based on drawing tower in-line fabrication system,a new preparation method of the sampled fiber grating is proposed and experimentally demonstrated.Experimental result shows that the obtained sampled fiber gratings possess dense reflection spectra,with a minimum reflection peak interval of only 0.09 nm.This method exhibits promising application prospect in the fabrication of the high-quality sampled fiber grating.On the other hand,the spectral characteristics of the sampled fiber grating are analyzed when the sub-grating is affected by the external physical quantities such as,in this paper,strain.Wavelength shift and intensity change in the reflection peak of the spectra indicate that the grating is affected differently by micro strains,due to the different spatial positions along the axis of the sampled fiber grating.This work is aimed at exploring the potential applications of the sampled fiber grating in quasi-distributed micro-area sensing with the millimeter level.展开更多
Several procedures for non-linear static and dynamic analysis of structures have been developed in recent years. In this paper, the response spectrum analysis is performed on two different shapes i.e. regular and irre...Several procedures for non-linear static and dynamic analysis of structures have been developed in recent years. In this paper, the response spectrum analysis is performed on two different shapes i.e. regular and irregular shape of structure by using STAAD PRO. And the comparison results are studied and compared accounting for the earthquake characteristics and the structure dynamic characteristics. As the results show that the earthquake response peak values and the main response frequencies are very close and comparable. It can be referred to by the engineering applications.展开更多
In this paper,an algorithm based on a fractional time-frequency spectrum feature is proposed to improve the accuracy of synthetic aperture radar(SAR)target detection.By extending the fractional Gabor transform(FrGT)in...In this paper,an algorithm based on a fractional time-frequency spectrum feature is proposed to improve the accuracy of synthetic aperture radar(SAR)target detection.By extending the fractional Gabor transform(FrGT)into two dimensions,the fractional time-frequency spectrum feature of an image can be obtained.In the achievement process,we search for the optimal order and design the optimal window function to accomplish the two-dimensional optimal FrGT.Finally,the energy attenuation gradient(EAG)feature of the optimal time-frequency spectrum is extracted for high-frequency detection.The simulation results show the proposed algorithm has a good performance in SAR target detection and lays the foundation for recognition.展开更多
This paper analyzes current spectrum utilization from all aspects based on related methods of spectrum measurement. The measurement results show that some spectrum resources are not used effectively due to current fix...This paper analyzes current spectrum utilization from all aspects based on related methods of spectrum measurement. The measurement results show that some spectrum resources are not used effectively due to current fixed spectrum allocation policy, and the spectrum occupancy varies dramatically in terms of time and space. These results provide basis for the development of next generation wireless communication technologies such as Cognitive Radio (CR).展开更多
This study proposes a novel feature extraction approach for radionuclide identification to increase the precision of identification of the gamma-ray energy spectrum set.For easier utilization of the information contai...This study proposes a novel feature extraction approach for radionuclide identification to increase the precision of identification of the gamma-ray energy spectrum set.For easier utilization of the information contained in the spectra,the vectors of the gamma-ray energy spectra from Euclidean space,which are fingerprints of the different types of radionuclides,were mapped to matrices in the Banach space.Subsequently,to make the spectra in matrix form easier to apply to image-based deep learning frameworks,the matrices of the gamma-ray energy spectra were mapped to images in the RGB color space.A deep convolutional neural network(DCNN)model was constructed and trained on the ImageNet dataset.The mapped gamma-ray energy spectrum images were applied as inputs to the DCNN model,and the corresponding outputs of the convolution layers and fully connected layers were transferred as descriptors of the images to construct a new classification model for radionuclide identification.The transferred image descriptors consist of global and local features,where the activation vectors of fully connected layers are global features,and activations from convolution layers are local features.A series of comparative experiments between the transferred image descriptors,peak information,features extracted by the histogram of the oriented gradients(HOG),and scale-invariant feature transform(SIFT)using both synthetic and measured data were applied to 11 classical classifiers.The results demonstrate that although the gamma-ray energy spectrum images are completely unfamiliar to the DCNN model and have not been used in the pre-training process,the transferred image descriptors achieved good classification results.The global features have strong semantic information,which achieves an average accuracy of 92.76%and 94.86%on the synthetic dataset and measured dataset,respectively.The results of the statistical comparison of features demonstrate that the proposed approach outperforms the peak-searching-based method,HOG,and SIFT on the synthetic and measured datasets.展开更多
The accuracy of the velocity field will be affected by the noise model and common mode errors through GPS time series analysis.In order to analyze the influence of these two factors on the accuracy of the velocity fie...The accuracy of the velocity field will be affected by the noise model and common mode errors through GPS time series analysis.In order to analyze the influence of these two factors on the accuracy of the velocity field,two kinds of data are used,including the three-year observation from 20 permanent GPS stations with high spatial correlation in the Everest,which is about 650 km from north to south and 1068 km from east to west,and three-year 80 ascending images and 141 descending images from sentinel-1A,which are processed by GAMIT/GLOBK software and Small Baseline Subset-Interferometric Synthetic Aperture Radar method(SBAS-InSAR),respectively.The vertical deformation rate is solved by time series analysis through a self-made adaptive algorithm.In the analysis,the linear change rate,period,half period coefficient,and residual sequence of all stations are solved by using James L.Davis periodic model.The noise type of residual sequence is analyzed by the power spectrum model.The spatio-temporal correlated noise,Common Mode Error(CME),is extracted by the Principal Component Analysis(PCA)and Karhunen-Loeve(KLE)methods.The results show that noises can be best described by“flicker noise+white noise”model.After the removal of CME,the R^(2) estimates of all stations are above 0.8,with RMS value of velocity field decreasing from 1.428 mm/yr to 1.062 mm/yr and 1.063 mm/yr to 0.815 mm/yr,in N and E directions,respectively,indicating that the influence of CME can't be ignored in the extraction of the high-precision velocity field in the Nepal and Everest region.展开更多
The spectrum effect on the penetration of resonant magnetic perturbation(RMP) is studied with upgraded in-vessel RMP coils on J-TEXT.The poloidal spectrum of the RMP field,especially the amplitudes of 2/1 and 3/1 comp...The spectrum effect on the penetration of resonant magnetic perturbation(RMP) is studied with upgraded in-vessel RMP coils on J-TEXT.The poloidal spectrum of the RMP field,especially the amplitudes of 2/1 and 3/1 components,can be varied by the phase difference between the upper and lower coil rows,ΔΦ=Φ_(top)-Φ_(bottom),where Φ_(top)and Φ_(bottom)are the toroidal phases of the n=1 field of each coil row.The type of RMP penetration is found to be related to ΔΦ,including the RMP penetration of either 2/1 or 3/1 RMP and the successive penetrations of 3/1 RMP followed by the 2/1 RMP.For cases with penetration of only one RMP component,the penetration thresholds measured by the corresponding resonant component are close for variousΔΦ.However,the 2/1 RMP penetration threshold is significantly reduced if the 3/1 locked island is formed in advance.The changes in the rotation profile due to 3/1 locked island formation could partially contribute to the reduction of the 2/1 thresholds.展开更多
The proposed method deals with the emerging technique called as Motor Current Signature Analysis (MCSA) to diagnosis the stator faults of Induction Motors. The performance of the proposed method deals with the emergin...The proposed method deals with the emerging technique called as Motor Current Signature Analysis (MCSA) to diagnosis the stator faults of Induction Motors. The performance of the proposed method deals with the emerging technique called as Motor Current Signature Analysis (MCSA) and the Zero-Sequence Voltage Component (ZSVC) to diagnose the stator faults of Induction Motors. The unalleviated study of the robustness of the industrial appliances is obligatory to verdict the fault of the machines at precipitate stages and thwart the machine from brutal damage. For all kinds of industry, a machine failure escorts to a diminution in production and cost increases. The Motor Current Signature Analysis (MCSA) is referred as the most predominant way to diagnose the faults of electrical machines. Since the detailed analysis of the current spectrum, the method will portray the typical fault state. This paper aims to present dissimilar stator faults which are classified under electrical faults using MCSA and the comparison of simulation and hardware results. The magnitude of these fault harmonics analyzes in detail by means of Finite-Element Method (FEM). The anticipated method can effectively perceive the trivial changes too during the operation of the motor and it shows in the results.展开更多
A formalism of solid state physics has been applied to provide an additional tool for the research of cosmological problems. It is demonstrated how this new approach could be useful in the analysis of the Cosmic Micro...A formalism of solid state physics has been applied to provide an additional tool for the research of cosmological problems. It is demonstrated how this new approach could be useful in the analysis of the Cosmic Microwave Background (CMB) data. After a transformation of the anisotropy spectrum of relict radiation into a special two-fold reciprocal space it was possible to propose a simple and general description of the interaction of relict photons with the matter by a “relict radiation factor”. This factor enabled us to process the transformed CMB anisotropy spectrum by a Fourier transform and thus arrive to a radial electron density distribution function (RDF) in a reciprocal space. As a consequence it was possible to estimate distances between Objects of the order of ~102 [m] and the density of the ordinary matter ~10-22 [kg.m-3]. Another analysis based on a direct calculation of the CMB radiation spectrum after its transformation into a simple reciprocal space and combined with appropriate structure modelling confirmed the cluster structure. The internal structure of Objects may be formed by Clusters distant ~10 [cm], whereas the internal structure of a Cluster consisted of particles distant ~0.3 [nm]. The work points in favour of clustering processes and to a cluster-like structure of the matter and thus contributes to the understanding of the structure of density fluctuations. As a consequence it may shed more light on the structure of the universe in the moment when the universe became transparent for photons. On the basis of our quantitative considerations it was possible to derive the number of particles (protons, helium nuclei, electrons and other particles) in Objects and Clusters and the number of Clusters in an Object.展开更多
基金supported by the National Natural Science Foundation of China(Grants:42204006,42274053,42030105,and 41504031)the Open Research Fund Program of the Key Laboratory of Geospace Environment and Geodesy,Ministry of Education,China(Grants:20-01-03 and 21-01-04)。
文摘Singular spectrum analysis is widely used in geodetic time series analysis.However,when extracting time-varying periodic signals from a large number of Global Navigation Satellite System(GNSS)time series,the selection of appropriate embedding window size and principal components makes this method cumbersome and inefficient.To improve the efficiency and accuracy of singular spectrum analysis,this paper proposes an adaptive singular spectrum analysis method by combining spectrum analysis with a new trace matrix.The running time and correlation analysis indicate that the proposed method can adaptively set the embedding window size to extract the time-varying periodic signals from GNSS time series,and the extraction efficiency of a single time series is six times that of singular spectrum analysis.The method is also accurate and more suitable for time-varying periodic signal analysis of global GNSS sites.
基金supported by the National Natural Science Foundation of China(Nos.12205190,11805121)the Science and Technology Commission of Shanghai Municipality(No.21ZR1435400).
文摘The uncertainty of nuclide libraries in the analysis of the gamma spectra of low-and intermediate-level radioactive waste(LILW)using existing methods produces unstable results.To address this problem,a novel spectral analysis method is proposed in this study.In this method,overlapping peaks are located using a continuous wavelet transform.An improved quadratic convolution method is proposed to calculate the widths of the peaks and establish a fourth-order filter model to estimate the Compton edge baseline with the overlapping peaks.Combined with the adaptive sensitive nonlinear iterative peak,this method can effectively subtracts the background.Finally,a function describing the peak shape as a filter is used to deconvolve the energy spectrum to achieve accurate qualitative and quantitative analyses of the nuclide without the aid of a nuclide library.Gamma spectrum acquisition experiments for standard point sources of Cs-137 and Eu-152,a segmented gamma scanning experiment for a 200 L standard drum,and a Monte Carlo simulation experiment for triple overlapping peaks using the closest energy of three typical LILW nuclides(Sb-125,Sb-124,and Cs-134)are conducted.The results of the experiments indicate that(1)the novel method and gamma vision(GV)with an accurate nuclide library have the same spectral analysis capability,and the peak area calculation error is less than 4%;(2)compared with the GV,the analysis results of the novel method are more stable;(3)the novel method can be applied to the activity measurement of LILW,and the error of the activity reconstruction at the equivalent radius is 2.4%;and(4)The proposed novel method can quantitatively analyze all nuclides in LILW without a nuclide library.This novel method can improve the accuracy and precision of LILW measurements,provide key technical support for the reasonable disposal of LILW,and ensure the safety of humans and the environment.
基金supported by Foundation of Henan Educational Committee(20A560004,J.Z.)Foundation of Henan Science and Technology Project(182102311086,Y.W.)Foundation for University Key Teacher(YCJQNGGJS201901,J.Z.,YCJXSJSDTR201801,Y.W.,Henan University of Urban Construction).
文摘Viscoelastic damper is an effective passive damping device,which can reduce the seismic response of the structure by increasing the damping and dissipating the vibration energy of structures.It has a wide application prospect in actual structural vibration control because of simple device and economical material.In view of the poor seismic behaviors of assembled frame structure connections,various energy dissipation devices are proposed to improve the seismic performance.The finite element numerical analysis method is adopted to analyze relevant energy dissipation structural parameters.The response spectrum of a 7-story assembled frame structure combined the ordinary steel support,ordinary viscoelastic damper,and viscoelastic damper with displacement amplification device is analyzed.The analysis results show that the mechanical behavior of assembled frame structure with ordinary steel supports are not significantly different from those without energy dissipation devices.The assembled frame structure with viscoelastic damper has better seismic performance and energy dissipation,especially for the viscoelastic damper with displacement amplification devices.The maximum value of inter-story displacement angle decreases by 32.24%;the maximum floor displacement decreases by 31.91%,and the base shear decreases by 13.62%compared with the assembled frame structures without energy dissipation devices.The results show that the seismic fortification ability of the structure is significantly improved,and the overall structure is more uniformly stressed.The damping structure with viscoelastic damper mainly reduces the dynamic response of the structure by increasing the damping coefficient,rather than by changing the natural vibration period of the structure.This paper provides an effective theoretical basis and reference for improving the energy dissipation system and the seismic performance of assembled frame structures.
文摘The power output state of photovoltaic power generation is affected by the earth’s rotation and solar radiation intensity.On the one hand,its output sequence has daily periodicity;on the other hand,it has discrete randomness.With the development of new energy economy,the proportion of photovoltaic energy increased accordingly.In order to solve the problem of improving the energy conversion efficiency in the grid-connected optical network and ensure the stability of photovoltaic power generation,this paper proposes the short-termprediction of photovoltaic power generation based on the improvedmulti-scale permutation entropy,localmean decomposition and singular spectrum analysis algorithm.Firstly,taking the power output per unit day as the research object,the multi-scale permutation entropy is used to calculate the eigenvectors under different weather conditions,and the cluster analysis is used to reconstruct the historical power generation under typical weather rainy and snowy,sunny,abrupt,cloudy.Then,local mean decomposition(LMD)is used to decompose the output sequence,so as to extract more detail components of the reconstructed output sequence.Finally,combined with the weather forecast of the Meteorological Bureau for the next day,the singular spectrumanalysis algorithm is used to predict the photovoltaic classification of the recombination decomposition sequence under typical weather.Through the verification and analysis of examples,the hierarchical prediction experiments of reconstructed and non-reconstructed output sequences are compared.The results show that the algorithm proposed in this paper is effective in realizing the short-term prediction of photovoltaic generator,and has the advantages of simple structure and high prediction accuracy.
基金Supported by the National Natural Science Foundation of China(50905084,51275236)the Aeronautical Science Foundation of China(2010ZE52054)
文摘Part variation characterization is essential to analyze the variation propagation in flexible assemblies. Aiming at two governing types of surface variation,warping and waviness,a comprehensive approach of geometric covariance modeling based on hybrid polynomial approximation and spectrum analysis is proposed,which can formulate the level and the correlation of surface variations accurately. Firstly,the form error data of compliant part is acquired by CMM. Thereafter,a Fourier-Legendre polynomial decomposition is conducted and the error data are approximated by a Legendre polynomial series. The weighting coefficient of each component is decided by least square method for extracting the warping from the surface variation. Consequently,a geometrical covariance expression for warping deformation is established. Secondly,a Fourier-sinusoidal decomposition is utilized to approximate the waviness from the residual error data. The spectrum is analyzed is to identify the frequency and the amplitude of error data. Thus,a geometrical covariance expression for the waviness is deduced. Thirdly,a comprehensive geometric covariance model for surface variation is developed by the combination the Legendre polynomials with the sinusoidal polynomials. Finally,a group of L-shape sheet metals is measured along a specific contour,and the covariance of the profile errors is modeled by the proposed method. Thereafter,the result is compared with the covariance from two other methods and the real data. The result shows that the proposed covariance model can match the real surface error effectively and represents a tighter approximation error compared with the referred methods.
基金supported by the Natural Science Foundation of Shaanxi Province under Grant 2019JQ206in part by the Science and Technology Department of Shaanxi Province under Grant 2020CGXNG-009in part by the Education Department of Shaanxi Province under Grant 17JK0346。
文摘An accurate landslide displacement prediction is an important part of landslide warning system. Aiming at the dynamic characteristics of landslide evolution and the shortcomings of traditional static prediction models, this paper proposes a dynamic prediction model of landslide displacement based on singular spectrum analysis(SSA) and stack long short-term memory(SLSTM) network. The SSA is used to decompose the landslide accumulated displacement time series data into trend term and periodic term displacement subsequences. A cubic polynomial function is used to predict the trend term displacement subsequence, and the SLSTM neural network is used to predict the periodic term displacement subsequence. At the same time, the Bayesian optimization algorithm is used to determine that the SLSTM network input sequence length is 12 and the number of hidden layer nodes is 18. The SLSTM network is updated by adding predicted values to the training set to achieve dynamic displacement prediction. Finally, the accumulated landslide displacement is obtained by superimposing the predicted value of each displacement subsequence. The proposed model was verified on the Xintan landslide in Hubei Province, China. The results show that when predicting the displacement of the periodic term, the SLSTM network has higher prediction accuracy than the support vector machine(SVM) and auto regressive integrated moving average(ARIMA). The mean relative error(MRE) is reduced by 4.099% and 3.548% respectively, while the root mean square error(RMSE) is reduced by 5.830 mm and 3.854 mm respectively. It is concluded that the SLSTM network model can better simulate the dynamic characteristics of landslides.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11674054,U1932217,and 11704067)。
文摘Due to non-saturating magnetoresistance(MR)and the special compensation mechanism,the Weyl semimetal Ta As single crystal has attracted considerable attention in condensed matter physics.Herein,we use maximum entropy mobility spectrum analysis(MEMSA)to extract charge carrier information by fitting the experimentally measured longitudinal and transverse electric transport curves of Ta As.The carrier types and the number of bands are obtained without any hypothesis.Study of the temperature dependence shows details of carrier property evolution.Our quantitative results explain the nonsaturated magnetoresistance and Hall sign change phenomena of TaAs.
基金supported by the National Magnetic Confinement Fusion Energy R & D Program of China (Nos. 2018YFE0309102 and 2019YFE03010004)National Natural Science Foundation of China (Nos.12075096, 11905078,and 51821005)
文摘The phase difference Δξ between locked islands(2/1 and 3/1) has been found to influence the heat transport on the thermal quench during disruptions by numerical modeling [Hu Q et al 2019Nucl.Fusion 59,016005].To verify this experimentally,a set of resonant magnetic perturbation(RMP) coils is required to excite coupled magnetic islands with different Δξ.The spectrum analysis shows that the current RMP coils on J-TEXT can only produce sufficient 2/1 and 3/1RMP fields with a limited phase difference of Δξ∈[-75°,75°].In order to broaden the adjustable range of Δξ,a set of coils on the high field side(HFS) is proposed to generate 2/1 and 3/1 RMP fields with Δξ=180°.As a result,RMPs with adjustable Δξ∈[-180°,180°] and sufficient amplitudes could be achieved by applying the HFS coils and the low field side(LFS)coils.This work provides a feasible solution for flexible adjustment of the phase difference between m and m+1 RMP,which might facilitate the study of major disruptions and their control.
文摘We present the research results on new CCD spectroscopic observations of three chromospherically active binary stars (BY Dra class), which were obtained by means of Coude echelle spectrograph fed by the 2 16m telescope at Beijing Astronomical Observatory. These spectrum images were reduced according to the standard fashion using IRAF package. With the aid of stellar model atmosphere, we have analyzed these spectra and derived the average metal abundance and Li abundance of three systems. Using two special spectral lines, we have also discussed the chromospheric activity indicators of them.
文摘The realization of automatic anomaly detection of respiratory motion could be very useful to prevent accidental damage during radiation therapy. In this paper, we proposed an automatic anomaly detection method using singular value decomposition analysis. Before applying this method, the investigator needs a normal respiratory motion data of a patient. From these data, a trajectory matrix representing normal time-series feature is created. Decomposing the matrix, we obtained the feature of normal time series. Then, we applied the same procedure to real-time data and obtained real-time features. Calculating the similarity of those feature matrixes, an anomaly score was obtained. Patient motion was observed by a depth camera. In our simulation, two types of motion e.g. cough and sudden stop of breathing were successfully detected, while gradual change of respiratory cycle frequency was not detected clearly.
基金supported by the State Key Laboratory of the Smart Grid Protection and Control of China and“111”project:Large Scale Power Grid Protection and Safety Defense 2.0(BP0820024)。
文摘Electrical power generation from wind technology is the most rapidly growing technology due to its ample characteristics.Nevertheless,because of its stochastic feature,it has the unnecessary impact on the operations and stability of the power grid system.The fluctuation of the grid frequency problem,for example,is more pronounced.The fluctuation of the frequency in turn impacts even the collapse of the power system.To minimize such problems,a droop-vector control strategy applied on a doubly-fed induction machine based(DFIM)variable speed pumped storage(VSPS)system is proposed in this paper.This method is should be used as a wind power fluctuation compensation solution in the wind farm-grid integration system.The system model is made on the basis of the technique called a phasor model.The frequency spectrum analysis approach is used in the VSPS plant for determining the dynamic performances of the grid in case of contingencies including wind power fluctuation compensation.The software platform MATLAB/Simulink is used for verifying the performance of the proposed system.The results show that the method of the frequency spectrum analysis technique is effective for determining the wind power fluctuation and stability requirements in large power networks.The control strategy proposed in this paper implementing the VSC-DFIM based VSPS plant integrated with the power gird and wind farm network achieves a well-controlled power flow and stable grid frequency with the deviations being in acceptable ranges.
基金This work was supported by the National Natural Science Foundation of China(NSFC)(Grant Nos.61290311 and 61735013)the Major Scientific and Technological Innovation Project in Hubei Province(Grant No.2015AAA001).
文摘Sampled fiber grating is a special superstructure fiber Bragg grating with a wide range of applications in many fields.In this work,based on drawing tower in-line fabrication system,a new preparation method of the sampled fiber grating is proposed and experimentally demonstrated.Experimental result shows that the obtained sampled fiber gratings possess dense reflection spectra,with a minimum reflection peak interval of only 0.09 nm.This method exhibits promising application prospect in the fabrication of the high-quality sampled fiber grating.On the other hand,the spectral characteristics of the sampled fiber grating are analyzed when the sub-grating is affected by the external physical quantities such as,in this paper,strain.Wavelength shift and intensity change in the reflection peak of the spectra indicate that the grating is affected differently by micro strains,due to the different spatial positions along the axis of the sampled fiber grating.This work is aimed at exploring the potential applications of the sampled fiber grating in quasi-distributed micro-area sensing with the millimeter level.
文摘Several procedures for non-linear static and dynamic analysis of structures have been developed in recent years. In this paper, the response spectrum analysis is performed on two different shapes i.e. regular and irregular shape of structure by using STAAD PRO. And the comparison results are studied and compared accounting for the earthquake characteristics and the structure dynamic characteristics. As the results show that the earthquake response peak values and the main response frequencies are very close and comparable. It can be referred to by the engineering applications.
基金supported by the Natural Science Foundation of Sichuan Province of China under Grant No.2022NSFSC40574partially supported by the National Natural Science Foundation of China under Grants No.61571096 and No.61775030.
文摘In this paper,an algorithm based on a fractional time-frequency spectrum feature is proposed to improve the accuracy of synthetic aperture radar(SAR)target detection.By extending the fractional Gabor transform(FrGT)into two dimensions,the fractional time-frequency spectrum feature of an image can be obtained.In the achievement process,we search for the optimal order and design the optimal window function to accomplish the two-dimensional optimal FrGT.Finally,the energy attenuation gradient(EAG)feature of the optimal time-frequency spectrum is extracted for high-frequency detection.The simulation results show the proposed algorithm has a good performance in SAR target detection and lays the foundation for recognition.
文摘This paper analyzes current spectrum utilization from all aspects based on related methods of spectrum measurement. The measurement results show that some spectrum resources are not used effectively due to current fixed spectrum allocation policy, and the spectrum occupancy varies dramatically in terms of time and space. These results provide basis for the development of next generation wireless communication technologies such as Cognitive Radio (CR).
基金supported by the National Defense Fundamental Research Project(No.JCKY2020404C004)Sichuan Science and Technology Program(No.22NSFSC0044).
文摘This study proposes a novel feature extraction approach for radionuclide identification to increase the precision of identification of the gamma-ray energy spectrum set.For easier utilization of the information contained in the spectra,the vectors of the gamma-ray energy spectra from Euclidean space,which are fingerprints of the different types of radionuclides,were mapped to matrices in the Banach space.Subsequently,to make the spectra in matrix form easier to apply to image-based deep learning frameworks,the matrices of the gamma-ray energy spectra were mapped to images in the RGB color space.A deep convolutional neural network(DCNN)model was constructed and trained on the ImageNet dataset.The mapped gamma-ray energy spectrum images were applied as inputs to the DCNN model,and the corresponding outputs of the convolution layers and fully connected layers were transferred as descriptors of the images to construct a new classification model for radionuclide identification.The transferred image descriptors consist of global and local features,where the activation vectors of fully connected layers are global features,and activations from convolution layers are local features.A series of comparative experiments between the transferred image descriptors,peak information,features extracted by the histogram of the oriented gradients(HOG),and scale-invariant feature transform(SIFT)using both synthetic and measured data were applied to 11 classical classifiers.The results demonstrate that although the gamma-ray energy spectrum images are completely unfamiliar to the DCNN model and have not been used in the pre-training process,the transferred image descriptors achieved good classification results.The global features have strong semantic information,which achieves an average accuracy of 92.76%and 94.86%on the synthetic dataset and measured dataset,respectively.The results of the statistical comparison of features demonstrate that the proposed approach outperforms the peak-searching-based method,HOG,and SIFT on the synthetic and measured datasets.
基金This research was supported by national nature science foundation of china(gratnt Nos.41674015,41731071)Qinghai high score remote sensing data industrialization application fund project(94-Y40G14-9001-15/18).
文摘The accuracy of the velocity field will be affected by the noise model and common mode errors through GPS time series analysis.In order to analyze the influence of these two factors on the accuracy of the velocity field,two kinds of data are used,including the three-year observation from 20 permanent GPS stations with high spatial correlation in the Everest,which is about 650 km from north to south and 1068 km from east to west,and three-year 80 ascending images and 141 descending images from sentinel-1A,which are processed by GAMIT/GLOBK software and Small Baseline Subset-Interferometric Synthetic Aperture Radar method(SBAS-InSAR),respectively.The vertical deformation rate is solved by time series analysis through a self-made adaptive algorithm.In the analysis,the linear change rate,period,half period coefficient,and residual sequence of all stations are solved by using James L.Davis periodic model.The noise type of residual sequence is analyzed by the power spectrum model.The spatio-temporal correlated noise,Common Mode Error(CME),is extracted by the Principal Component Analysis(PCA)and Karhunen-Loeve(KLE)methods.The results show that noises can be best described by“flicker noise+white noise”model.After the removal of CME,the R^(2) estimates of all stations are above 0.8,with RMS value of velocity field decreasing from 1.428 mm/yr to 1.062 mm/yr and 1.063 mm/yr to 0.815 mm/yr,in N and E directions,respectively,indicating that the influence of CME can't be ignored in the extraction of the high-precision velocity field in the Nepal and Everest region.
基金supported by the National Magnetic Confinement Fusion Energy R&D Program of China(Nos.2019YFE03010004,2018YFE0309100)the National Key R&D Program of China(No.2017YFE0301100)National Natural Science Foundation of China(Nos.11905078,12075096 and 51821005)
文摘The spectrum effect on the penetration of resonant magnetic perturbation(RMP) is studied with upgraded in-vessel RMP coils on J-TEXT.The poloidal spectrum of the RMP field,especially the amplitudes of 2/1 and 3/1 components,can be varied by the phase difference between the upper and lower coil rows,ΔΦ=Φ_(top)-Φ_(bottom),where Φ_(top)and Φ_(bottom)are the toroidal phases of the n=1 field of each coil row.The type of RMP penetration is found to be related to ΔΦ,including the RMP penetration of either 2/1 or 3/1 RMP and the successive penetrations of 3/1 RMP followed by the 2/1 RMP.For cases with penetration of only one RMP component,the penetration thresholds measured by the corresponding resonant component are close for variousΔΦ.However,the 2/1 RMP penetration threshold is significantly reduced if the 3/1 locked island is formed in advance.The changes in the rotation profile due to 3/1 locked island formation could partially contribute to the reduction of the 2/1 thresholds.
文摘The proposed method deals with the emerging technique called as Motor Current Signature Analysis (MCSA) to diagnosis the stator faults of Induction Motors. The performance of the proposed method deals with the emerging technique called as Motor Current Signature Analysis (MCSA) and the Zero-Sequence Voltage Component (ZSVC) to diagnose the stator faults of Induction Motors. The unalleviated study of the robustness of the industrial appliances is obligatory to verdict the fault of the machines at precipitate stages and thwart the machine from brutal damage. For all kinds of industry, a machine failure escorts to a diminution in production and cost increases. The Motor Current Signature Analysis (MCSA) is referred as the most predominant way to diagnose the faults of electrical machines. Since the detailed analysis of the current spectrum, the method will portray the typical fault state. This paper aims to present dissimilar stator faults which are classified under electrical faults using MCSA and the comparison of simulation and hardware results. The magnitude of these fault harmonics analyzes in detail by means of Finite-Element Method (FEM). The anticipated method can effectively perceive the trivial changes too during the operation of the motor and it shows in the results.
文摘A formalism of solid state physics has been applied to provide an additional tool for the research of cosmological problems. It is demonstrated how this new approach could be useful in the analysis of the Cosmic Microwave Background (CMB) data. After a transformation of the anisotropy spectrum of relict radiation into a special two-fold reciprocal space it was possible to propose a simple and general description of the interaction of relict photons with the matter by a “relict radiation factor”. This factor enabled us to process the transformed CMB anisotropy spectrum by a Fourier transform and thus arrive to a radial electron density distribution function (RDF) in a reciprocal space. As a consequence it was possible to estimate distances between Objects of the order of ~102 [m] and the density of the ordinary matter ~10-22 [kg.m-3]. Another analysis based on a direct calculation of the CMB radiation spectrum after its transformation into a simple reciprocal space and combined with appropriate structure modelling confirmed the cluster structure. The internal structure of Objects may be formed by Clusters distant ~10 [cm], whereas the internal structure of a Cluster consisted of particles distant ~0.3 [nm]. The work points in favour of clustering processes and to a cluster-like structure of the matter and thus contributes to the understanding of the structure of density fluctuations. As a consequence it may shed more light on the structure of the universe in the moment when the universe became transparent for photons. On the basis of our quantitative considerations it was possible to derive the number of particles (protons, helium nuclei, electrons and other particles) in Objects and Clusters and the number of Clusters in an Object.
