In the methods of image thresholding segmentation, such methods based on two-dimensional （2D） histogram and optimal objective functions are important. However, when they are used for infrared image segmentation, the...In the methods of image thresholding segmentation, such methods based on two-dimensional （2D） histogram and optimal objective functions are important. However, when they are used for infrared image segmentation, they are weak in suppressing background noises and worse in segmenting targets with non-uniform gray level. The concept of 2D histogram shape modification is proposed, which is realized by target information prior restraint after enhancing target information using plateau histogram equalization. The formula of 2D minimum Renyi entropy is deduced for image segmentation, then the shape-modified 2D histogram is combined wfth four optimal objective functions （i.e., maximum between-class variance, maximum entropy, maximum correlation and minimum Renyi entropy） respectively for the appli- cation of infrared image segmentation. Simultaneously, F-measure is introduced to evaluate the segmentation effects objectively. The experimental results show that F-measure is an effective evaluation index for image segmentation since its value is fully consistent with the subjective evaluation, and after 2D histogram shape modification, the methods of optimal objective functions can overcome their original forms＇ deficiency and their segmentation effects are more or less improvements, where the best one is the maximum entropy method based on 2D histogram shape modification.展开更多
In this paper,shock train motion in a Mach number 2.7 duct is studied experimentally,and large numbers of schlieren images are obtained by a high-speed camera.An image processing method based on Maximum Correlation De...In this paper,shock train motion in a Mach number 2.7 duct is studied experimentally,and large numbers of schlieren images are obtained by a high-speed camera.An image processing method based on Maximum Correlation Detection(MCD)is proposed to detect shock train motion from the schlieren images,based on which the key structures,e.g.,separation positions and separation shock angles on the top and bottom walls,can be analysed in detail.The oscillations of the shock train are generated by rhombus and ellipse shafts at various excitation frequencies.According to the analysis of MCD results,the distributions of the frequency components of shock train oscillation generated by the two shafts are distinctly different,in which the motion generated by the ellipse shaft is much smoother;shock train motion is mainly characterized by the oscillation of separation position while the separation shock strength is not so sensitive to downstream disturbance;there is a hysteresis loop relation between the downstream pressure and separation position.展开更多
Recently, Chung et al. gave a general method to construct frequency-hopping sequence set(FHS set) with low-hit-zone(LHZ FHS set) by the Cartesian product. In their paper, Theorems 5 and 8 claim that k FHS sets whose m...Recently, Chung et al. gave a general method to construct frequency-hopping sequence set(FHS set) with low-hit-zone(LHZ FHS set) by the Cartesian product. In their paper, Theorems 5 and 8 claim that k FHS sets whose maximum periodic Hamming correlation is 0 at the origin result in an LHZ FHS set based on the Cartesian product, and Proposition 4 presented an upper bound of the maximum periodic Hamming correlation of FHSs. However, their statements are imperfect or incorrect. In this paper, we give counterexamples and make corrections to them. Furthermore, based on the Cartesian product, we construct two classes of LHZ FHS sets with optimal maximum periodic partial Hamming correlation property. It is shown that new FHS sets are optimal by the maximum periodic partial Hamming correlation bound of LHZ FHS set.展开更多
In this paper, we investigate the variable selection problem of the generalized regression models. To estimate the regression parameter, a procedure combining the rank correlation method and the adaptive lasso techniq...In this paper, we investigate the variable selection problem of the generalized regression models. To estimate the regression parameter, a procedure combining the rank correlation method and the adaptive lasso technique is developed, which is proved to have oracle properties. A modified IMO （iterative marginal optimization） algorithm which directly aims to maximize the penalized rank correlation function is proposed. The effects of the estimating procedure are illustrated by simulation studies.展开更多
In the paper, a novel practical approach to construct a composite indicator （CI） is pro- posed. The key idea is to decide the weights of sub-indicators in constructing a composite indicator by maximizing the sum of ...In the paper, a novel practical approach to construct a composite indicator （CI） is pro- posed. The key idea is to decide the weights of sub-indicators in constructing a composite indicator by maximizing the sum of squared correlations between the CI and sub-indicators. The CI obtained in this fashion has the maximum sum of squared correlations among all linear estimators. In addition, the simple, exact and explicit solutions of weights are proposed under the condition of non-negative irreducible matrix. Moreover, under this particular condition, the proposed method will become the principal component analysis. For illustration purpose, the proposed novel approach is utilized to cal- culate Sustainable Energy Index and Human Development Index which are two often-used cases to compare models in the literatures. The results the methods of Hatefi, et al. （2010） and Zhou all sub-indicators＇ correlations. show that the power of the proposed method outweigh et al. （2007） in terms of the sum of absolute values of展开更多
Recently, direct acquisition of GPS P-code has received considerable attention to enhance the anti-jamming and anti-spoofing capabilities of GPS receivers. This paper describes a P-code acquisition method that uses bl...Recently, direct acquisition of GPS P-code has received considerable attention to enhance the anti-jamming and anti-spoofing capabilities of GPS receivers. This paper describes a P-code acquisition method that uses block searches with large-scale FFT to search code phases and carrier frequency offsets in parallel. To limit memory use, especially when implemented in hardware, only the largest correlation result with its position information was preserved after searching a block of resolution cells in both the time and frequency domains. A second search was used to solve the code phase slip problem induced by the code frequency offset, Simulation results demonstrate that the probability of detection is above 0.99 for carrier-to-noise density ratios in excess of 40 dB. Hz when the predetection integration time is 0.8 ms and 6 non- coherent integrations are used in the analysis.展开更多
Ocean surface currents play a key role in the earth’s climate.They affect virtually all processes occurring in the ocean and can also directly affect many important socio-economic activities.Himawari-8 meteorological...Ocean surface currents play a key role in the earth’s climate.They affect virtually all processes occurring in the ocean and can also directly affect many important socio-economic activities.Himawari-8 meteorological satellite has an international advanced geostationary orbit imager sensor,AHI,with high time resolution and spatial coverage,Himawari-8 can be used to observe the subtle changes in marine environments.In this study,we used Himawari-8 data received from the Joint Receiving Station for Satellite Remote Sensing of Xiamen University to retrieve coastal currents in Hangzhou Bay.Particularly,the Maximum Correlation Coefficient(MCC)and the Generalized Hough Transform(GHT)methods were used to retrieve them respectively.The retrieved sea surface currents are analyzed and verified by the numerical model data of the Taiwan Strait current forecasting system(TFOR).The results show that(1)the Himawari-8 satellite data can be used to effectively estimate the ocean current;(2)The results of the two methods are in agreement with each other,and the error in the current measured using the GHT method is smaller in the Yangtze estuary and offshore areas,where the turbidity characteristic front is stronger.展开更多
To address the issue of accurately extracting fault characteristic information of railway freight car bearings under noisy conditions,this paper proposes a fault diagnosis method based on Adaptive Chirp Mode Decomposi...To address the issue of accurately extracting fault characteristic information of railway freight car bearings under noisy conditions,this paper proposes a fault diagnosis method based on Adaptive Chirp Mode Decomposition(ACMD)and an optimized Maximum Correlation Kurtosis Deconvolution(MCKD)using a Sparrow Search Algorithm Combining Sine-Cosine and Cauchy Mutation(SCSSA).Firstly,ACMD is used to decompose and reconstruct the original fault signal to obtain several Intrinsic Mode Functions(IMFs).Then,the IMFs are filtered according to the Gini coefficient indicator,with the IMF having the largest Gini coefficient selected as the optimal component.Secondly,the SCSSA is employed to iteratively optimize the filter length L,fault signal period T,and displacement parameter M in the MCKD algorithm,determining the optimal parameter combination for MCKD.This avoids the limitations of manual settings and enhances the accuracy of fault diagnosis.The optimized MCKD is then applied to the optimal component,and deconvolution is performed using maximum correlation kurtosis as the criterion to extract fault characteristic information through its envelope spectrum.To verify the effectiveness and generalizability of the proposed method,simulations,experimental signals from the Case Western Reserve University Bearing Center,and actual measured signals from railway freight car bearing 353130B are used to analyze inner ring faults.The experimental results demonstrate that the method can accurately extract fault characteristic information of railway freight car bearings under noise interference and identify the fault type.展开更多
To address the difficulty in extracting early fault feature signals of rolling bearings,this paper proposes a novel weak fault diagnosis method for rolling bearings.This method combines the Improved Complementary Ense...To address the difficulty in extracting early fault feature signals of rolling bearings,this paper proposes a novel weak fault diagnosis method for rolling bearings.This method combines the Improved Complementary Ensemble Empirical Mode Decomposition with Adaptive Noise(ICEEMDAN)and the Improved Maximum Correlated Kurtosis Deconvolution(IMCKD).Utilizing the kurtosis criterion,the intrinsic mode functions obtained through ICEEMDAN are reconstructed and denoised using IMCKD,which significantly reduces noise in the measured signal.This approach maximizes the energy amplitude at the fault characteristic frequency,facilitating fault feature identification.Experimental studies on two test benches demonstrate that this method effectively reduces noise interference and highlights the fault frequency components.Compared with traditional methods,it significantly improves the signal-to-noise ratio and more accurately identifies fault features,meeting the requirements for discriminating rolling bearing faults.The method proposed in this study was applied to the measured vibration signals of the gearbox bearings in the new high-speed wire department of a Long Products Mill.It successfully extracted weak characteristic information of early bearing faults,achieving the expected diagnostic results.This further validates the effectiveness of the ICEEMDAN–IMCKD method in practical engineering applications,demonstrating significant engineering value for detecting and extracting weak impact characteristics in rolling bearings.展开更多
基金supported by the China Postdoctoral Science Foundation(20100471451)the Science and Technology Foundation of State Key Laboratory of Underwater Measurement&Control Technology(9140C2603051003)
文摘In the methods of image thresholding segmentation, such methods based on two-dimensional （2D） histogram and optimal objective functions are important. However, when they are used for infrared image segmentation, they are weak in suppressing background noises and worse in segmenting targets with non-uniform gray level. The concept of 2D histogram shape modification is proposed, which is realized by target information prior restraint after enhancing target information using plateau histogram equalization. The formula of 2D minimum Renyi entropy is deduced for image segmentation, then the shape-modified 2D histogram is combined wfth four optimal objective functions （i.e., maximum between-class variance, maximum entropy, maximum correlation and minimum Renyi entropy） respectively for the appli- cation of infrared image segmentation. Simultaneously, F-measure is introduced to evaluate the segmentation effects objectively. The experimental results show that F-measure is an effective evaluation index for image segmentation since its value is fully consistent with the subjective evaluation, and after 2D histogram shape modification, the methods of optimal objective functions can overcome their original forms＇ deficiency and their segmentation effects are more or less improvements, where the best one is the maximum entropy method based on 2D histogram shape modification.
基金supported by the National Numerical Wind Tunnel Project of China,the National Natural Science Foundation of China(Nos.12002163 and 12072157)the Natural Science Foundation of Jiangsu Province,China(No.BK20200408)+1 种基金the China Postdoctoral Science Foundation(No.2022T150321)the Key Laboratory of Hypersonic Aerodynamic Force and Heat Technology,AVIC Aerodynamics Research Institute,China。
文摘In this paper,shock train motion in a Mach number 2.7 duct is studied experimentally,and large numbers of schlieren images are obtained by a high-speed camera.An image processing method based on Maximum Correlation Detection(MCD)is proposed to detect shock train motion from the schlieren images,based on which the key structures,e.g.,separation positions and separation shock angles on the top and bottom walls,can be analysed in detail.The oscillations of the shock train are generated by rhombus and ellipse shafts at various excitation frequencies.According to the analysis of MCD results,the distributions of the frequency components of shock train oscillation generated by the two shafts are distinctly different,in which the motion generated by the ellipse shaft is much smoother;shock train motion is mainly characterized by the oscillation of separation position while the separation shock strength is not so sensitive to downstream disturbance;there is a hysteresis loop relation between the downstream pressure and separation position.
基金supported by National Natural Science Foundation of China(Grant No.61271244)Key Grant Project of Ministry of Education of China(Grant No.311031 100)Young Innovative Research Team of Sichuan Province(Grant No.2011JTD0007)
文摘Recently, Chung et al. gave a general method to construct frequency-hopping sequence set(FHS set) with low-hit-zone(LHZ FHS set) by the Cartesian product. In their paper, Theorems 5 and 8 claim that k FHS sets whose maximum periodic Hamming correlation is 0 at the origin result in an LHZ FHS set based on the Cartesian product, and Proposition 4 presented an upper bound of the maximum periodic Hamming correlation of FHSs. However, their statements are imperfect or incorrect. In this paper, we give counterexamples and make corrections to them. Furthermore, based on the Cartesian product, we construct two classes of LHZ FHS sets with optimal maximum periodic partial Hamming correlation property. It is shown that new FHS sets are optimal by the maximum periodic partial Hamming correlation bound of LHZ FHS set.
基金supported by National Natural Science Foundation of China(10901162)supported by the Fundamental Research Funds for the Central Universities and the Research Funds of Renmin University of China(10XNF073)supported by China Postdoctoral Science Foundation(2014M550799)
文摘In this paper, we investigate the variable selection problem of the generalized regression models. To estimate the regression parameter, a procedure combining the rank correlation method and the adaptive lasso technique is developed, which is proved to have oracle properties. A modified IMO （iterative marginal optimization） algorithm which directly aims to maximize the penalized rank correlation function is proposed. The effects of the estimating procedure are illustrated by simulation studies.
基金supported by National Natural Science Foundation of China under Grant No.71003100the Fundamental Research Funds for the Central Universitiesthe Research Funds of Renmin University of China under Grant No.11XNK027
文摘In the paper, a novel practical approach to construct a composite indicator （CI） is pro- posed. The key idea is to decide the weights of sub-indicators in constructing a composite indicator by maximizing the sum of squared correlations between the CI and sub-indicators. The CI obtained in this fashion has the maximum sum of squared correlations among all linear estimators. In addition, the simple, exact and explicit solutions of weights are proposed under the condition of non-negative irreducible matrix. Moreover, under this particular condition, the proposed method will become the principal component analysis. For illustration purpose, the proposed novel approach is utilized to cal- culate Sustainable Energy Index and Human Development Index which are two often-used cases to compare models in the literatures. The results the methods of Hatefi, et al. （2010） and Zhou all sub-indicators＇ correlations. show that the power of the proposed method outweigh et al. （2007） in terms of the sum of absolute values of
文摘Recently, direct acquisition of GPS P-code has received considerable attention to enhance the anti-jamming and anti-spoofing capabilities of GPS receivers. This paper describes a P-code acquisition method that uses block searches with large-scale FFT to search code phases and carrier frequency offsets in parallel. To limit memory use, especially when implemented in hardware, only the largest correlation result with its position information was preserved after searching a block of resolution cells in both the time and frequency domains. A second search was used to solve the code phase slip problem induced by the code frequency offset, Simulation results demonstrate that the probability of detection is above 0.99 for carrier-to-noise density ratios in excess of 40 dB. Hz when the predetection integration time is 0.8 ms and 6 non- coherent integrations are used in the analysis.
基金supported by the SOA Global Change&Air-Sea Interaction Project(Grant Nos.GASI-02-PAC-YGST2-02 and GASI-IPOVAI-01-04)the Open Research Fund of State Key Laboratory of Information Engineering in Surveying,the Mapping and Remote Sensing,Wuhan University(Grant No.18T08)the National Natural Science Foundation of China(Grant Nos.91858202,41476007&41630963)。
文摘Ocean surface currents play a key role in the earth’s climate.They affect virtually all processes occurring in the ocean and can also directly affect many important socio-economic activities.Himawari-8 meteorological satellite has an international advanced geostationary orbit imager sensor,AHI,with high time resolution and spatial coverage,Himawari-8 can be used to observe the subtle changes in marine environments.In this study,we used Himawari-8 data received from the Joint Receiving Station for Satellite Remote Sensing of Xiamen University to retrieve coastal currents in Hangzhou Bay.Particularly,the Maximum Correlation Coefficient(MCC)and the Generalized Hough Transform(GHT)methods were used to retrieve them respectively.The retrieved sea surface currents are analyzed and verified by the numerical model data of the Taiwan Strait current forecasting system(TFOR).The results show that(1)the Himawari-8 satellite data can be used to effectively estimate the ocean current;(2)The results of the two methods are in agreement with each other,and the error in the current measured using the GHT method is smaller in the Yangtze estuary and offshore areas,where the turbidity characteristic front is stronger.
文摘To address the issue of accurately extracting fault characteristic information of railway freight car bearings under noisy conditions,this paper proposes a fault diagnosis method based on Adaptive Chirp Mode Decomposition(ACMD)and an optimized Maximum Correlation Kurtosis Deconvolution(MCKD)using a Sparrow Search Algorithm Combining Sine-Cosine and Cauchy Mutation(SCSSA).Firstly,ACMD is used to decompose and reconstruct the original fault signal to obtain several Intrinsic Mode Functions(IMFs).Then,the IMFs are filtered according to the Gini coefficient indicator,with the IMF having the largest Gini coefficient selected as the optimal component.Secondly,the SCSSA is employed to iteratively optimize the filter length L,fault signal period T,and displacement parameter M in the MCKD algorithm,determining the optimal parameter combination for MCKD.This avoids the limitations of manual settings and enhances the accuracy of fault diagnosis.The optimized MCKD is then applied to the optimal component,and deconvolution is performed using maximum correlation kurtosis as the criterion to extract fault characteristic information through its envelope spectrum.To verify the effectiveness and generalizability of the proposed method,simulations,experimental signals from the Case Western Reserve University Bearing Center,and actual measured signals from railway freight car bearing 353130B are used to analyze inner ring faults.The experimental results demonstrate that the method can accurately extract fault characteristic information of railway freight car bearings under noise interference and identify the fault type.
基金Inner Mongolia Autonomous Region Science and Technology Major Special Project,Grant/Award Number:2021ZD0019-4。
文摘To address the difficulty in extracting early fault feature signals of rolling bearings,this paper proposes a novel weak fault diagnosis method for rolling bearings.This method combines the Improved Complementary Ensemble Empirical Mode Decomposition with Adaptive Noise(ICEEMDAN)and the Improved Maximum Correlated Kurtosis Deconvolution(IMCKD).Utilizing the kurtosis criterion,the intrinsic mode functions obtained through ICEEMDAN are reconstructed and denoised using IMCKD,which significantly reduces noise in the measured signal.This approach maximizes the energy amplitude at the fault characteristic frequency,facilitating fault feature identification.Experimental studies on two test benches demonstrate that this method effectively reduces noise interference and highlights the fault frequency components.Compared with traditional methods,it significantly improves the signal-to-noise ratio and more accurately identifies fault features,meeting the requirements for discriminating rolling bearing faults.The method proposed in this study was applied to the measured vibration signals of the gearbox bearings in the new high-speed wire department of a Long Products Mill.It successfully extracted weak characteristic information of early bearing faults,achieving the expected diagnostic results.This further validates the effectiveness of the ICEEMDAN–IMCKD method in practical engineering applications,demonstrating significant engineering value for detecting and extracting weak impact characteristics in rolling bearings.
