The goal of this paper is to find an excellent adaptive window function for extracting the weak vibration signal and high frequency vibration signal under strong noise.The relationship between windowing transform andf...The goal of this paper is to find an excellent adaptive window function for extracting the weak vibration signal and high frequency vibration signal under strong noise.The relationship between windowing transform andfiltering is analyzed first in the paper.The advantage of adjustable time-frequency window of wavelet transform is introduced.Secondly the relationship between harmonic wavelet and multiple analytic band-pass filter is analyzed.The coherence of the multiple analytic band-pass filter and harmonic wavelet base function is discussed,and the characteristic that multiple analytic band-pass filter included in the harmonic wavelet transform is founded.Thirdly,by extending the harmonic wavelet transform,the concept of the adaptive harmonic window and its theoretical equation without decomposition are put forward in this paper.Then comparing with the Hanning window,the good performance of restraining side-lobe leakage possessed by adaptive harmonic window is shown,and the adaptive characteristics of window width changing and analytical center moving of the adaptive harmonic window are presented.Finally,the proposed adaptive harmonic window is applied to weak signal extraction and high frequency orbit extraction of high speed rotor under strong noise,and the satisfactory results are achieved.The application results show that the adaptive harmonic window function can be successfully applied to the actual engineering signal processing.展开更多
Due to the limited transmission resources for data relay in the tracking and data relay satellite system （TDRSS）, there are many job requirements in busy days which will be discarded in the conventional job scheduli...Due to the limited transmission resources for data relay in the tracking and data relay satellite system （TDRSS）, there are many job requirements in busy days which will be discarded in the conventional job scheduling model. Therefore, the improvement of scheduling efficiency in the TDRSS can not only help to increase the resource utilities, but also to reduce the scheduling failure ratio. A model of nonhomogeneous parallel machines scheduling problems with time window （NPM-TW） is firstly built up for the TDRSS, considering the distinct features of the variable preparation time and the nonhomogeneous transmission rates for different types of antennas on each tracking and data relay satellite （TDRS）. Then, an adaptive subsequence adjustment （ASA） framework with evolutionary asymmetric path-relinking （EvAPR） is proposed to solve this problem, in which an asymmetric progressive crossover operation is involved to overcome the local optima by the conventional job inserting methods. The numerical results show that, compared with the classical greedy randomized adaptive search procedure （GRASP） algorithm, the scheduling failure ratio of jobs can be reduced over 11% on average by the proposed ASA with EvAPR.展开更多
A self-adaptive large neighborhood search method for scheduling n jobs on m non-identical parallel machines with mul- tiple time windows is presented. The problems＇ another feature lies in oversubscription, namely no...A self-adaptive large neighborhood search method for scheduling n jobs on m non-identical parallel machines with mul- tiple time windows is presented. The problems＇ another feature lies in oversubscription, namely not all jobs can be scheduled within specified scheduling horizons due to the limited machine capacity. The objective is thus to maximize the overall profits of processed jobs while respecting machine constraints. A first-in- first-out heuristic is applied to find an initial solution, and then a large neighborhood search procedure is employed to relax and re- optimize cumbersome solutions. A machine learning mechanism is also introduced to converge on the most efficient neighborhoods for the problem. Extensive computational results are presented based on data from an application involving the daily observation scheduling of a fleet of earth observing satellites. The method rapidly solves most problem instances to optimal or near optimal and shows a robust performance in sensitive analysis.展开更多
Adaptive optimization is one of the means that agile organization of command and control resource （AOC2R） adapts for the dynamic battlefield environment. A math model of the adaptive optimization of AOC2R is put for...Adaptive optimization is one of the means that agile organization of command and control resource （AOC2R） adapts for the dynamic battlefield environment. A math model of the adaptive optimization of AOC2R is put forward by analyzing the interrelating concept and research. The model takes the adaptive process as a multi-stage decision making problem. The 2-phases method is presented to calculate the model, which obtains the related parameters by running the colored Petri net （CPN） model of AOC2R and then searches for the result by ant colony optimization （ACO） algorithm integrated with genetic optimization techniques. The simulation results demonstrate that the proposed algorithm greatly improves the performance of AOC2R.展开更多
针对复合电能质量扰动检测算法实时性差、时频分辨率低的问题,提出了一种基于改进自适应S变换(improved adaptive S transform, IAST)的电能质量扰动实时检测方法。构建全局自适应高斯窗作为IAST的核函数,可随检测频率变化自适应调整窗...针对复合电能质量扰动检测算法实时性差、时频分辨率低的问题,提出了一种基于改进自适应S变换(improved adaptive S transform, IAST)的电能质量扰动实时检测方法。构建全局自适应高斯窗作为IAST的核函数,可随检测频率变化自适应调整窗函数有效窗长及频谱,避免为提高时频分辨率频繁切换窗口参数,降低算法复杂度。以增强信号能量集中度为参数调优目标选取窗口参数,确保对各类扰动的精确时频定位。采用自动阈值法确定实际扰动信号的主频点,并对主频点进行时频变换,进一步提高算法执行效率。仿真和实测结果表明,相比于现有复合电能质量扰动检测算法,该检测方法实时性好、时频分辨能力强、计算复杂度低,适用于复杂电能质量扰动实时准确检测。展开更多
基金Project(51675262)supported by the National Natural Science Foundation of ChinaProject(6140210020102)supported by the Advance Research Field Fund Project of ChinaProject(2016YFD0700800)supported by the National Key Research and Development Plan of China
文摘The goal of this paper is to find an excellent adaptive window function for extracting the weak vibration signal and high frequency vibration signal under strong noise.The relationship between windowing transform andfiltering is analyzed first in the paper.The advantage of adjustable time-frequency window of wavelet transform is introduced.Secondly the relationship between harmonic wavelet and multiple analytic band-pass filter is analyzed.The coherence of the multiple analytic band-pass filter and harmonic wavelet base function is discussed,and the characteristic that multiple analytic band-pass filter included in the harmonic wavelet transform is founded.Thirdly,by extending the harmonic wavelet transform,the concept of the adaptive harmonic window and its theoretical equation without decomposition are put forward in this paper.Then comparing with the Hanning window,the good performance of restraining side-lobe leakage possessed by adaptive harmonic window is shown,and the adaptive characteristics of window width changing and analytical center moving of the adaptive harmonic window are presented.Finally,the proposed adaptive harmonic window is applied to weak signal extraction and high frequency orbit extraction of high speed rotor under strong noise,and the satisfactory results are achieved.The application results show that the adaptive harmonic window function can be successfully applied to the actual engineering signal processing.
基金supported by the National Natural Science Foundation of China(6113200291338101+3 种基金91338108)the National S&T Major Project(2011ZX03004-001-01)the Research Fund of Tsinghua University(2011Z05117)the Co-innovation Laboratory of Aerospace Broadband Network Technology
文摘Due to the limited transmission resources for data relay in the tracking and data relay satellite system （TDRSS）, there are many job requirements in busy days which will be discarded in the conventional job scheduling model. Therefore, the improvement of scheduling efficiency in the TDRSS can not only help to increase the resource utilities, but also to reduce the scheduling failure ratio. A model of nonhomogeneous parallel machines scheduling problems with time window （NPM-TW） is firstly built up for the TDRSS, considering the distinct features of the variable preparation time and the nonhomogeneous transmission rates for different types of antennas on each tracking and data relay satellite （TDRS）. Then, an adaptive subsequence adjustment （ASA） framework with evolutionary asymmetric path-relinking （EvAPR） is proposed to solve this problem, in which an asymmetric progressive crossover operation is involved to overcome the local optima by the conventional job inserting methods. The numerical results show that, compared with the classical greedy randomized adaptive search procedure （GRASP） algorithm, the scheduling failure ratio of jobs can be reduced over 11% on average by the proposed ASA with EvAPR.
基金supported by the National Natural Science Foundation of China (7060103570801062)
文摘A self-adaptive large neighborhood search method for scheduling n jobs on m non-identical parallel machines with mul- tiple time windows is presented. The problems＇ another feature lies in oversubscription, namely not all jobs can be scheduled within specified scheduling horizons due to the limited machine capacity. The objective is thus to maximize the overall profits of processed jobs while respecting machine constraints. A first-in- first-out heuristic is applied to find an initial solution, and then a large neighborhood search procedure is employed to relax and re- optimize cumbersome solutions. A machine learning mechanism is also introduced to converge on the most efficient neighborhoods for the problem. Extensive computational results are presented based on data from an application involving the daily observation scheduling of a fleet of earth observing satellites. The method rapidly solves most problem instances to optimal or near optimal and shows a robust performance in sensitive analysis.
文摘Adaptive optimization is one of the means that agile organization of command and control resource （AOC2R） adapts for the dynamic battlefield environment. A math model of the adaptive optimization of AOC2R is put forward by analyzing the interrelating concept and research. The model takes the adaptive process as a multi-stage decision making problem. The 2-phases method is presented to calculate the model, which obtains the related parameters by running the colored Petri net （CPN） model of AOC2R and then searches for the result by ant colony optimization （ACO） algorithm integrated with genetic optimization techniques. The simulation results demonstrate that the proposed algorithm greatly improves the performance of AOC2R.
文摘针对复合电能质量扰动检测算法实时性差、时频分辨率低的问题,提出了一种基于改进自适应S变换(improved adaptive S transform, IAST)的电能质量扰动实时检测方法。构建全局自适应高斯窗作为IAST的核函数,可随检测频率变化自适应调整窗函数有效窗长及频谱,避免为提高时频分辨率频繁切换窗口参数,降低算法复杂度。以增强信号能量集中度为参数调优目标选取窗口参数,确保对各类扰动的精确时频定位。采用自动阈值法确定实际扰动信号的主频点,并对主频点进行时频变换,进一步提高算法执行效率。仿真和实测结果表明,相比于现有复合电能质量扰动检测算法,该检测方法实时性好、时频分辨能力强、计算复杂度低,适用于复杂电能质量扰动实时准确检测。
