With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic sy...With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations.展开更多
The concept of neutrosophic statistics is applied to propose two monitoring schemes which are an improvement of the neutrosophic exponentially weighted moving average(NEWMA)chart.In this study,two control charts are d...The concept of neutrosophic statistics is applied to propose two monitoring schemes which are an improvement of the neutrosophic exponentially weighted moving average(NEWMA)chart.In this study,two control charts are designed under the uncertain environment or neutrosophic statistical interval system,when all observations are undermined,imprecise or fuzzy.These are termed neutrosophic double and triple exponentially weighted moving average(NDEWMA and NTEWMA)control charts.For the proficiency of the proposed chart,Monte Carlo simulations are used to calculate the run-length characteristics(such as average run length(ARL),standard deviation of the run length(SDRL),percentiles(P_(25),P_(50),P_(75)))of the proposed charts.The structures of the proposed control charts are more effective in detecting small shifts while these are comparable with the other existing charts in detecting moderate and large shifts.The simulation study and real-life implementations of the proposed charts show that the proposed NDEWMA and NTEWMA charts perform better in monitoring the process of road traffic crashes and electric engineering data as compared to the existing control charts.Therefore,the proposed charts will be helpful in minimizing the road accident and minimizing the defective products.Furthermore,the proposed charts are more acceptable and actual to apply in uncertain environment.展开更多
As a useful alternative of Shewhart control chart, exponentially weighted moving average （EWMA） control chat has been applied widely to quality control, process monitoring, forecast, etc. In this paper, a method was...As a useful alternative of Shewhart control chart, exponentially weighted moving average （EWMA） control chat has been applied widely to quality control, process monitoring, forecast, etc. In this paper, a method was introduced for optimal design of EWMA and multivariate EWMA （MEWMA） control charts, in which the optimal parameter pair （ λ, k） or （ λ, h ） was searched by using the generalized regression neural network （GRNN）. The results indicate that the optimal parameter pair can be obtained effectively by the proposed strategy for a given in-control average running length （ARLo） and shift to detect under any conditions, removing the drawback of incompleteness existing in the tables that had been reported.展开更多
In this paper, the authors give a different and more precise analysis of the stability of the classical Gauss-Laguerre quadrature rule for the Cauchy P.V. integrals on the half line. Moreover, in order to obtain this ...In this paper, the authors give a different and more precise analysis of the stability of the classical Gauss-Laguerre quadrature rule for the Cauchy P.V. integrals on the half line. Moreover, in order to obtain this result they give some new estimates for the distance of the zeros of the Laguerre polynomials that can be useful also in other contests.展开更多
In this paper, a hybrid improved particle swarm optimization （IPSO） algorithm is proposed for the optimization of hydroelectric power scheduling in multi-reservoir systems. The conventional particle swarm optimizati...In this paper, a hybrid improved particle swarm optimization （IPSO） algorithm is proposed for the optimization of hydroelectric power scheduling in multi-reservoir systems. The conventional particle swarm optimization （PSO） algorithm is improved in two ways： （1） The linearly decreasing inertia weight coefficient （LDIWC） is replaced by a self-adaptive exponential inertia weight coefficient （SEIWC）, which could make the PSO algorithm more balanceable and more effective in both global and local searches. （2） The crossover and mutation idea inspired by the genetic algorithm （GA） is imported into the particle updating method to enhance the diversity of populations. The potential ability of IPSO in nonlinear numerical function optimization was first tested with three classical benchmark functions. Then, a long-term multi-reservoir system operation model based on IPSO was designed and a case study was carried out in the Minjiang Basin in China, where there is a power system consisting of 26 hydroelectric power plants. The scheduling results of the IPSO algorithm were found to outperform PSO and to be comparable with the results of the dynamic programming successive approximation （DPSA） algorithm.展开更多
In electrical impedance tomography （EIT）, distribution of the internal resistivity or conductivity of an unknown object is esti- mated using measured boundary voltage data induced by different current patterns with ...In electrical impedance tomography （EIT）, distribution of the internal resistivity or conductivity of an unknown object is esti- mated using measured boundary voltage data induced by different current patterns with various reconstruction algorithms. The reconstruction algorithms usually employ the Newton-Raphson iteration scheme to visualize the resistivity distribution inside the object. Accuracy of the imaging process depends not only on the algorithm used, but also on the scheme of finite element discretization. In this paper an adaptive mesh refinement is used in a modified reconstruction algorithm for the regularized Err. The method has a major impact on efficient solution of the forward problem as well as on achieving improved image resolution. Computer simulations indicate that the Newton-Raphson reconstruction algorithm for Err using adaptive mesh refinement performs better than the classical Newton-Raphson algorithm in terms of reconstructed image resolution.展开更多
Quality and robustness of grid deformation is of the most importance in the field of aircraft design, and grid in high quality is essential for improving the precision of numerical simulation. In order to maintain the...Quality and robustness of grid deformation is of the most importance in the field of aircraft design, and grid in high quality is essential for improving the precision of numerical simulation. In order to maintain the orthogonality of deformed grid, the displacement of grid points is divided into rotational and translational parts in this paper, and inverse distance weighted interpolation is used to transfer the changing location from boundary grid to the spatial grid. Moreover, the deformation of rotational part is implemented in combination with the exponential space mapping that improves the certainty and stability of quaternion interpolation. Furthermore, the new grid deformation technique named ‘‘layering blend deformation＇＇ is built based on the basic quaternion technique, which combines the layering arithmetic with transfinite interpolation（TFI） technique. Then the proposed technique is applied in the movement of airfoil, parametric modeling, and the deformation of complex configuration, in which the robustness of grid quality is tested. The results show that the new method has the capacity to deal with the problems with large deformation, and the ‘‘layering blend deformation＇＇ improves the efficiency and quality of the basic quaternion deformation method significantly.展开更多
The continuous monitoring of the machine is beneficial in improving its process reliability through reflected power function distribution.It is substantial for identifying and removing errors at the early stages of pr...The continuous monitoring of the machine is beneficial in improving its process reliability through reflected power function distribution.It is substantial for identifying and removing errors at the early stages of production that ultimately benefit the firms in cost-saving and quality improvement.The current study introduces control charts that help the manufacturing concerns to keep the production process in control.It presents an exponentially weighted moving average and extended exponentially weighted moving average and then compared their performance.The percentiles estimator and the modified maximum likelihood estimator are used to constructing the control charts.The findings suggest that an extended exponentially weighted moving average control chart based on the percentiles estimator performs better than exponentially weightedmoving average control charts based on the percentiles estimator and modified maximum likelihood estimator.Further,these results will help the firms in the early detection of errors that enhance the process reliability of the telecommunications and financing industry.展开更多
Consistent high-quality and defect-free production is the demand of the day. The product recall not only increases engineering and manufacturing cost but also affects the quality and the reliability of the product in ...Consistent high-quality and defect-free production is the demand of the day. The product recall not only increases engineering and manufacturing cost but also affects the quality and the reliability of the product in the eye of users. The monitoring and improvement of a manufacturing process are the strength of statistical process control. In this article we propose a process monitoring memory-based scheme for continuous data under the assumption of normality to detect small non-random shift patterns in any manufacturing or service process.The control limits for the proposed scheme are constructed. The in-control and out-of-control average run length(AVL) expressions have been derived for the performance evaluation of the proposed scheme. Robustness to non-normality has been tested after simulation study of the run length distribution of the proposed scheme, and the comparisons with Shewhart and exponentially weighted moving average(EWMA) schemes are presented for various gamma and t-distributions. The proposed scheme is effective and attractive as it has one design parameter which differentiates it from the traditional schemes. Finally, some suggestions and recommendations are made for the future work.展开更多
A novel nonlinear combination process monitoring method was proposed based on techniques with memo- ry effect （multivariate exponentially weighted moving average （MEWMA）） and kernel independent component analysis ...A novel nonlinear combination process monitoring method was proposed based on techniques with memo- ry effect （multivariate exponentially weighted moving average （MEWMA）） and kernel independent component analysis （KICA）. The method was developed for dealing with nonlinear issues and detecting small or moderate drifts in one or more process variables with autocorrelation. MEWMA charts use additional information from the past history of the process for keeping the memory effect of the process behavior trend. KICA is a recently devel- oped statistical technique for revealing hidden, nonlinear statistically independent factors that underlie sets of mea- surements and it is a two-phase algorithm., whitened kernel principal component analysis （KPCA） plus indepen- dent component analysis （ICA）. The application to the fluid catalytic cracking unit （FCCU） simulated process in- dicates that the proposed combined method based on MEWMA and KICA can effectively capture the nonlinear rela- tionship and detect small drifts in process variables. Its performance significantly outperforms monitoring method based on ICA, MEWMA-ICA and KICA, especially for lonu-term performance deterioration.展开更多
This paper describes procedure for estimation of travel time on signalized arterial roads based on multiple data sources with application of dimensionality reduction. Travel time estimation approach incorporates forec...This paper describes procedure for estimation of travel time on signalized arterial roads based on multiple data sources with application of dimensionality reduction. Travel time estimation approach incorporates forecast of transportation nodes impendence and travel time on network links. Forecasting period is two hours and the estimation is based on historical data and real time data on traffic conditions. Travel time estimation combines multivariate regression, principal component analysis, KNN （k-nearest neighbours）, cross validation and EWMA （exponentially weighted moving average） methods. When comparing estimation methodologies, relevantly better results were achieved by KNN method than with EWMA method. This is true for every time interval considered except for evening time interval when signalized arterial roads were uncongested.展开更多
With the advancement in the science and technology,cloud computing has become a recent trend in environment with immense requirement of infrastructure and resources.Load balancing of cloud computing environments is an...With the advancement in the science and technology,cloud computing has become a recent trend in environment with immense requirement of infrastructure and resources.Load balancing of cloud computing environments is an important matter of concern.The migration of the overloaded virtual machines(VMs)to the underloaded VM with optimized resource utilization is the effective way of the load balancing.In this paper,a new VM migration algorithm for the load balancing in the cloud is proposed.The migration algorithm proposed(EGSA-VMM)is based on exponential gravitational search algorithm which is the integration of gravitational search algorithm and exponential weighted moving average theory.In our approach,the migration is done based on the migration cost and QoS.The experimentation of proposed EGSA-based VM migration algorithm is compared with ACO and GSA.The simulation of experiments shows that the proposed EGSA-VMM algorithm achieves load balancing and reasonable resource utilization,which outperforms existing migration strategies in terms of number of VM migrations and number of SLA violations.展开更多
The research on rolling bearing early fault detection is mainly focused on degradation index extraction and adaptive setting of alarm threshold.The mainstream methods are to extract degradation indicators based on ada...The research on rolling bearing early fault detection is mainly focused on degradation index extraction and adaptive setting of alarm threshold.The mainstream methods are to extract degradation indicators based on adaptive features and set adaptive alarm thresholds based on the Shewhart control chart.However,the adaptive feature extraction method does not consider the correlation between features,and the Shewhart control chart is not sensitive to small fluctuations caused by early faults.In this study,a rolling bearing early fault detection method based on a feature clustering fusion degradation index is proposed.The multidomain statistical features are extracted to form the initial feature set,and the improved hierarchical clustering algorithm is combined with the feature evaluation index to select features to form a preferred feature subset,to ensure the richness of index information and reduce redundancy.After the construction of the degradation index,to suppress the interference caused by nonstationary and abnormal shocks in early fault detection,the accurate evaluation method and anomaly determination strategy of control chart parameters are studied,and an improved exponential weighted move average control chart is designed to monitor the degradation index.The effectiveness and superiority of the proposed method are verified by public data sets.This research provides a rolling bearing early fault detection method,which can provide comprehensive degradation indicators,eliminate interference caused by random anomalies and running in periods,and achieve an accurate detection of early bearing failures.展开更多
Let Wβ（x） = exp（-1/2｜x｜^β） be the Freud weight and pn（x） ∈ ∏n be the sequence of orthogonal polynomials with respect to W^2β（x）, that is,∫^∞ -∞pn（x）pm（x）W^2β（x）dx{0,n≠m,1,n=m.It is known that...Let Wβ（x） = exp（-1/2｜x｜^β） be the Freud weight and pn（x） ∈ ∏n be the sequence of orthogonal polynomials with respect to W^2β（x）, that is,∫^∞ -∞pn（x）pm（x）W^2β（x）dx{0,n≠m,1,n=m.It is known that all the zeros of pn（x） are distributed on the whole real line. The present paper investigates the convergence of Grfinwald interpolatory operators based on the zeros of orthogonal polynomials for the Freud weights. We prove that, if we take the zeros of Freud polynomials as the interpolation nodes, thenGn（f,x）→ f（x）,n→∞holds for every x ∈ （-∞, ∞）, where f（x） is any continous function on the real line satisfying ｜f（x）｜ = O（exp（1/2｜x｜^β）.展开更多
This research aimed to design the channel cross section with low water loss in irrigation areas.The traditional methods and models are based on explicit equations which neglect seepage and evaporation losses with low ...This research aimed to design the channel cross section with low water loss in irrigation areas.The traditional methods and models are based on explicit equations which neglect seepage and evaporation losses with low accuracy.To rectify this problem,in this research,an improved cat swarm optimization(ICSO)was obtained by adding exponential inertia weight coefficient and mutation to enhance the efficiency of conventional cat swarm optimization(CSO).Finally,the Fifth main channel of Jiangdong Irrigation area in Heilongjiang Province was taken as a study area to test the ability of ICSO.Comparing to the original design,the reduction of water loss was 20%with low flow errors.Furthermore,the ICSO was compared with genetic algorithm(GA),the particle swarm optimization(PSO)and cat swarm algorithm(CSO)to verify the effectiveness in the channel section optimization.The results are satisfactory and the method can be used for reliable design of artificial open channels.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.11572264,11172247,11402214,and 61373009)
文摘With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations.
基金This work was funded by the Deanship of Scientific Research(DSR),King Abdulaziz University,JeddahThe authors,therefore,gratefully acknowledge the DSR technical and financial support.
文摘The concept of neutrosophic statistics is applied to propose two monitoring schemes which are an improvement of the neutrosophic exponentially weighted moving average(NEWMA)chart.In this study,two control charts are designed under the uncertain environment or neutrosophic statistical interval system,when all observations are undermined,imprecise or fuzzy.These are termed neutrosophic double and triple exponentially weighted moving average(NDEWMA and NTEWMA)control charts.For the proficiency of the proposed chart,Monte Carlo simulations are used to calculate the run-length characteristics(such as average run length(ARL),standard deviation of the run length(SDRL),percentiles(P_(25),P_(50),P_(75)))of the proposed charts.The structures of the proposed control charts are more effective in detecting small shifts while these are comparable with the other existing charts in detecting moderate and large shifts.The simulation study and real-life implementations of the proposed charts show that the proposed NDEWMA and NTEWMA charts perform better in monitoring the process of road traffic crashes and electric engineering data as compared to the existing control charts.Therefore,the proposed charts will be helpful in minimizing the road accident and minimizing the defective products.Furthermore,the proposed charts are more acceptable and actual to apply in uncertain environment.
基金Funded by the National Key Technologies R&D Programs of China (No.2002BA105C)
文摘As a useful alternative of Shewhart control chart, exponentially weighted moving average （EWMA） control chat has been applied widely to quality control, process monitoring, forecast, etc. In this paper, a method was introduced for optimal design of EWMA and multivariate EWMA （MEWMA） control charts, in which the optimal parameter pair （ λ, k） or （ λ, h ） was searched by using the generalized regression neural network （GRNN）. The results indicate that the optimal parameter pair can be obtained effectively by the proposed strategy for a given in-control average running length （ARLo） and shift to detect under any conditions, removing the drawback of incompleteness existing in the tables that had been reported.
文摘In this paper, the authors give a different and more precise analysis of the stability of the classical Gauss-Laguerre quadrature rule for the Cauchy P.V. integrals on the half line. Moreover, in order to obtain this result they give some new estimates for the distance of the zeros of the Laguerre polynomials that can be useful also in other contests.
基金supported by the National Natural Science Foundation of China (Grant No. 50679011)
文摘In this paper, a hybrid improved particle swarm optimization （IPSO） algorithm is proposed for the optimization of hydroelectric power scheduling in multi-reservoir systems. The conventional particle swarm optimization （PSO） algorithm is improved in two ways： （1） The linearly decreasing inertia weight coefficient （LDIWC） is replaced by a self-adaptive exponential inertia weight coefficient （SEIWC）, which could make the PSO algorithm more balanceable and more effective in both global and local searches. （2） The crossover and mutation idea inspired by the genetic algorithm （GA） is imported into the particle updating method to enhance the diversity of populations. The potential ability of IPSO in nonlinear numerical function optimization was first tested with three classical benchmark functions. Then, a long-term multi-reservoir system operation model based on IPSO was designed and a case study was carried out in the Minjiang Basin in China, where there is a power system consisting of 26 hydroelectric power plants. The scheduling results of the IPSO algorithm were found to outperform PSO and to be comparable with the results of the dynamic programming successive approximation （DPSA） algorithm.
基金Project supported by National Natural Science Foundation of China（Grant No. 60075009）
文摘In electrical impedance tomography （EIT）, distribution of the internal resistivity or conductivity of an unknown object is esti- mated using measured boundary voltage data induced by different current patterns with various reconstruction algorithms. The reconstruction algorithms usually employ the Newton-Raphson iteration scheme to visualize the resistivity distribution inside the object. Accuracy of the imaging process depends not only on the algorithm used, but also on the scheme of finite element discretization. In this paper an adaptive mesh refinement is used in a modified reconstruction algorithm for the regularized Err. The method has a major impact on efficient solution of the forward problem as well as on achieving improved image resolution. Computer simulations indicate that the Newton-Raphson reconstruction algorithm for Err using adaptive mesh refinement performs better than the classical Newton-Raphson algorithm in terms of reconstructed image resolution.
文摘Quality and robustness of grid deformation is of the most importance in the field of aircraft design, and grid in high quality is essential for improving the precision of numerical simulation. In order to maintain the orthogonality of deformed grid, the displacement of grid points is divided into rotational and translational parts in this paper, and inverse distance weighted interpolation is used to transfer the changing location from boundary grid to the spatial grid. Moreover, the deformation of rotational part is implemented in combination with the exponential space mapping that improves the certainty and stability of quaternion interpolation. Furthermore, the new grid deformation technique named ‘‘layering blend deformation＇＇ is built based on the basic quaternion technique, which combines the layering arithmetic with transfinite interpolation（TFI） technique. Then the proposed technique is applied in the movement of airfoil, parametric modeling, and the deformation of complex configuration, in which the robustness of grid quality is tested. The results show that the new method has the capacity to deal with the problems with large deformation, and the ‘‘layering blend deformation＇＇ improves the efficiency and quality of the basic quaternion deformation method significantly.
文摘The continuous monitoring of the machine is beneficial in improving its process reliability through reflected power function distribution.It is substantial for identifying and removing errors at the early stages of production that ultimately benefit the firms in cost-saving and quality improvement.The current study introduces control charts that help the manufacturing concerns to keep the production process in control.It presents an exponentially weighted moving average and extended exponentially weighted moving average and then compared their performance.The percentiles estimator and the modified maximum likelihood estimator are used to constructing the control charts.The findings suggest that an extended exponentially weighted moving average control chart based on the percentiles estimator performs better than exponentially weightedmoving average control charts based on the percentiles estimator and modified maximum likelihood estimator.Further,these results will help the firms in the early detection of errors that enhance the process reliability of the telecommunications and financing industry.
文摘Consistent high-quality and defect-free production is the demand of the day. The product recall not only increases engineering and manufacturing cost but also affects the quality and the reliability of the product in the eye of users. The monitoring and improvement of a manufacturing process are the strength of statistical process control. In this article we propose a process monitoring memory-based scheme for continuous data under the assumption of normality to detect small non-random shift patterns in any manufacturing or service process.The control limits for the proposed scheme are constructed. The in-control and out-of-control average run length(AVL) expressions have been derived for the performance evaluation of the proposed scheme. Robustness to non-normality has been tested after simulation study of the run length distribution of the proposed scheme, and the comparisons with Shewhart and exponentially weighted moving average(EWMA) schemes are presented for various gamma and t-distributions. The proposed scheme is effective and attractive as it has one design parameter which differentiates it from the traditional schemes. Finally, some suggestions and recommendations are made for the future work.
基金The National Natural Science Foundation ofChina(No60504033)
文摘A novel nonlinear combination process monitoring method was proposed based on techniques with memo- ry effect （multivariate exponentially weighted moving average （MEWMA）） and kernel independent component analysis （KICA）. The method was developed for dealing with nonlinear issues and detecting small or moderate drifts in one or more process variables with autocorrelation. MEWMA charts use additional information from the past history of the process for keeping the memory effect of the process behavior trend. KICA is a recently devel- oped statistical technique for revealing hidden, nonlinear statistically independent factors that underlie sets of mea- surements and it is a two-phase algorithm., whitened kernel principal component analysis （KPCA） plus indepen- dent component analysis （ICA）. The application to the fluid catalytic cracking unit （FCCU） simulated process in- dicates that the proposed combined method based on MEWMA and KICA can effectively capture the nonlinear rela- tionship and detect small drifts in process variables. Its performance significantly outperforms monitoring method based on ICA, MEWMA-ICA and KICA, especially for lonu-term performance deterioration.
文摘This paper describes procedure for estimation of travel time on signalized arterial roads based on multiple data sources with application of dimensionality reduction. Travel time estimation approach incorporates forecast of transportation nodes impendence and travel time on network links. Forecasting period is two hours and the estimation is based on historical data and real time data on traffic conditions. Travel time estimation combines multivariate regression, principal component analysis, KNN （k-nearest neighbours）, cross validation and EWMA （exponentially weighted moving average） methods. When comparing estimation methodologies, relevantly better results were achieved by KNN method than with EWMA method. This is true for every time interval considered except for evening time interval when signalized arterial roads were uncongested.
文摘With the advancement in the science and technology,cloud computing has become a recent trend in environment with immense requirement of infrastructure and resources.Load balancing of cloud computing environments is an important matter of concern.The migration of the overloaded virtual machines(VMs)to the underloaded VM with optimized resource utilization is the effective way of the load balancing.In this paper,a new VM migration algorithm for the load balancing in the cloud is proposed.The migration algorithm proposed(EGSA-VMM)is based on exponential gravitational search algorithm which is the integration of gravitational search algorithm and exponential weighted moving average theory.In our approach,the migration is done based on the migration cost and QoS.The experimentation of proposed EGSA-based VM migration algorithm is compared with ACO and GSA.The simulation of experiments shows that the proposed EGSA-VMM algorithm achieves load balancing and reasonable resource utilization,which outperforms existing migration strategies in terms of number of VM migrations and number of SLA violations.
基金Supported by National Key Research and Development Program(Grant No.2023YFB4203402)National Natural Science Foundation of China(Grant No.52375042)+1 种基金Chongqing Technology Innovation and Application Development Project(Grant No.CSTB2022TIAD-KPX0078)Chongqing Transportation Technology Project(Grant No.CQJT-CZKJ2024-10).
文摘The research on rolling bearing early fault detection is mainly focused on degradation index extraction and adaptive setting of alarm threshold.The mainstream methods are to extract degradation indicators based on adaptive features and set adaptive alarm thresholds based on the Shewhart control chart.However,the adaptive feature extraction method does not consider the correlation between features,and the Shewhart control chart is not sensitive to small fluctuations caused by early faults.In this study,a rolling bearing early fault detection method based on a feature clustering fusion degradation index is proposed.The multidomain statistical features are extracted to form the initial feature set,and the improved hierarchical clustering algorithm is combined with the feature evaluation index to select features to form a preferred feature subset,to ensure the richness of index information and reduce redundancy.After the construction of the degradation index,to suppress the interference caused by nonstationary and abnormal shocks in early fault detection,the accurate evaluation method and anomaly determination strategy of control chart parameters are studied,and an improved exponential weighted move average control chart is designed to monitor the degradation index.The effectiveness and superiority of the proposed method are verified by public data sets.This research provides a rolling bearing early fault detection method,which can provide comprehensive degradation indicators,eliminate interference caused by random anomalies and running in periods,and achieve an accurate detection of early bearing failures.
基金Open Funds(No.PCN0613) of State Key Laboratory of Oil and Gas Reservoir and Exploitation(Southwest Petroleum University)the Foundation of Education of Zhejiang Province(No.Kyg091206029)
文摘Let Wβ（x） = exp（-1/2｜x｜^β） be the Freud weight and pn（x） ∈ ∏n be the sequence of orthogonal polynomials with respect to W^2β（x）, that is,∫^∞ -∞pn（x）pm（x）W^2β（x）dx{0,n≠m,1,n=m.It is known that all the zeros of pn（x） are distributed on the whole real line. The present paper investigates the convergence of Grfinwald interpolatory operators based on the zeros of orthogonal polynomials for the Freud weights. We prove that, if we take the zeros of Freud polynomials as the interpolation nodes, thenGn（f,x）→ f（x）,n→∞holds for every x ∈ （-∞, ∞）, where f（x） is any continous function on the real line satisfying ｜f（x）｜ = O（exp（1/2｜x｜^β）.
基金the National Natural Science Foundation of China(No.51579044,No.41071053,No.51479032)Specialized Research Fund for Innovative Talents of Harbin(Excellent Academic Leader)(No.2013RFXXJ001)Science and Technology Program of Water Conservancy of Heilongjiang Province(No.201319,No.201501,No.201503).
文摘This research aimed to design the channel cross section with low water loss in irrigation areas.The traditional methods and models are based on explicit equations which neglect seepage and evaporation losses with low accuracy.To rectify this problem,in this research,an improved cat swarm optimization(ICSO)was obtained by adding exponential inertia weight coefficient and mutation to enhance the efficiency of conventional cat swarm optimization(CSO).Finally,the Fifth main channel of Jiangdong Irrigation area in Heilongjiang Province was taken as a study area to test the ability of ICSO.Comparing to the original design,the reduction of water loss was 20%with low flow errors.Furthermore,the ICSO was compared with genetic algorithm(GA),the particle swarm optimization(PSO)and cat swarm algorithm(CSO)to verify the effectiveness in the channel section optimization.The results are satisfactory and the method can be used for reliable design of artificial open channels.
