When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To o...When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To overcome this drawback, the zero phase filter is introduced to the mentioned filter, and a fault diagnosis method for speed-changing gearbox is proposed. Firstly, the gear meshing frequency of each gearbox is estimated by chirplet path pursuit. Then, according to the estimated gear meshing frequencies, an adaptive zero phase time-varying filter(AZPTF) is designed to filter the original signal. Finally, the basis for fault diagnosis is acquired by the envelope order analysis to the filtered signal. The signal consisting of two time-varying amplitude modulation and frequency modulation(AM-FM) signals is respectively analyzed by ATF and AZPTF based on MCSSD. The simulation results show the variances between the original signals and the filtered signals yielded by AZPTF based on MCSSD are 13.67 and 41.14, which are far less than variances (323.45 and 482.86) between the original signals and the filtered signals obtained by ATF based on MCSSD. The experiment results on the vibration signals of gearboxes indicate that the vibration signals of the two speed-changing gearboxes installed on one foundation bed can be separated by AZPTF effectively. Based on the demodulation information of the vibration signal of each gearbox, the fault diagnosis can be implemented. Both simulation and experiment examples prove that the proposed filter can extract a mono-component time-varying AM-FM signal from the multi-component time-varying AM-FM signal without distortion.展开更多
As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and m...As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.展开更多
Background: The Shelduck (Tadorna tadorna) is a characteristic waterbird species of inland wetlands in northeastern Algeria. Its wintering behavior in relation to changes of local abundances and foraging group density...Background: The Shelduck (Tadorna tadorna) is a characteristic waterbird species of inland wetlands in northeastern Algeria. Its wintering behavior in relation to changes of local abundances and foraging group density is poorly known. Objectives: This study aims at monitoring patterns of diurnal activities and the variation of behavioral time-budgets in relation to numbers of wintering Shelducks. We investigate temporal variations of diurnal activities across multipletime scales and consider their interrelationships. Methods: Assessments of local population abundance were weekly surveyed during two wintering seasons (2010– 2012), whereas diurnal activities (feeding, sleeping, swimming, preening, loafing, flying, courtship, and antagonism) were studied three times a month during seven hours (08:00–16:00) using the Scan method. Time budget variations of each behavioral activity were tested using nested ANOVAs following multiple time scales. Generalized linear mixedeffects models (GLMM) tested whether variations in diurnal activities were density-dependent. Results: During the wintering season, Shelduck’s numbers followed a bell-shaped trend, which indicated that the species was typically a wintering migrant in Sabkha Djendli. The first individuals arrived onsite in October–November then numbers reached a peak in January (up to 2400 individuals in 2012) with steady density during December–February, afterward individuals left the site progressively until late April when the site is deserted. During both wintering seasons, diurnal activities were dominated by feeding (60%), followed by sleeping (12%) then swimming and preening with 9% and 8%, respectively. The rest of the activities (loafing, flying, courtship and antagonistic behaviors) had low proportions of time budget. ANOVAs showed that activity time budgets varied significantly following multiple time scales (year, season, month, day, semi-hour). Time budgets of diurnal activities during each wintering season were significantly interrelated. Correlations patterns between the two seasons were similar. GLMMs revealed that the variations of diurnal activities were not density-dependent, except for preening and swimming. Conclusion: During the wintering season, habitats of Sabkha Djendli are important for waterbirds, including the Shelduck that used the lake mainly for food-foraging and resting. The 2400 individuals censused in mid-winter are important locally and at the North African scale. This stresses the need to strengthen the protection status of this wetland and mitigate degradation sources that threaten wintering waterfowl.展开更多
The improvements of high-throughput experimental devices such as microarray and mass spectrometry have allowed an effective acquisition of biological comprehensive data which include genome, transcriptome, proteome, a...The improvements of high-throughput experimental devices such as microarray and mass spectrometry have allowed an effective acquisition of biological comprehensive data which include genome, transcriptome, proteome, and metabolome (multi-layered omics data). In Systems Biology, we try to elucidate various dynamical characteristics of biological functions with applying the omics data to detailed mathematical model based on the central dogma. However, such mathematical models possess multi-time-scale properties which are often accompanied by time-scale differences seen among biological layers. The differences cause time stiff problem, and have a grave influence on numerical calculation stability. In the present conventional method, the time stiff problem remained because the calculation of all layers was implemented by adaptive time step sizes of the smallest time-scale layer to ensure stability and maintain calculation accuracy. In this paper, we designed and developed an effective numerical calculation method to improve the time stiff problem. This method consisted of ahead, backward, and cumulative algorithms. Both ahead and cumulative algorithms enhanced calculation efficiency of numerical calculations via adjustments of step sizes of each layer, and reduced the number of numerical calculations required for multi-time-scale models with the time stiff problem. Backward algorithm ensured calculation accuracy in the multi-time-scale models. In case studies which were focused on three layers system with 60 times difference in time-scale order in between layers, a proposed method had almost the same calculation accuracy compared with the conventional method in spite of a reduction of the total amount of the number of numerical calculations. Accordingly, the proposed method is useful in a numerical analysis of multi-time-scale models with time stiff problem.展开更多
柔性负荷参与新型电力系统的优化调度对于提高新能源的消纳能力具有显著作用,但目前柔性负荷潜力尚未充分挖掘。针对这一问题,提出一种基于源荷预测的日前-日内优化调度方法。首先,采用麻雀搜索算法优化卷积长短时记忆神经网络(sparrow ...柔性负荷参与新型电力系统的优化调度对于提高新能源的消纳能力具有显著作用,但目前柔性负荷潜力尚未充分挖掘。针对这一问题,提出一种基于源荷预测的日前-日内优化调度方法。首先,采用麻雀搜索算法优化卷积长短时记忆神经网络(sparrow search algorithm is used to optimize the convolutional long-term and short-term memory neural network,SSA-CNN-LSTM)对新能源和负荷进行日前和日内功率预测;其次,根据柔性负荷的特性和需求响应灵活性,将负荷分为可平移、可转移和可削减负荷等不同类型,以考虑阶梯式碳交易成本的系统运行成本和污染气体排放最优为目标构建源荷互动的日前-日内两阶段低碳环境经济调度模型;最后,利用改进多目标灰狼算法(multi-objective grey wolf algorithm,MOGWO)对模型进行求解。算例分析表明,通过对柔性负荷分类参与调度较传统方式总成本降低8.6%、污染物排放减少4.1%、新能源消纳能力提高4.2%,在多时间尺度内显著降低新能源和负荷响应的不确定性并提高新型电力系统的低碳环境经济综合效益。展开更多
基金supported by National Natural Science Foundation of China (Grant No. 71271078)National Hi-tech Research and Development Program of China (863 Program, Grant No. 2009AA04Z414)Integration of Industry, Education and Research of Guangdong Province, and Ministry of Education of China (Grant No. 2009B090300312)
文摘When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To overcome this drawback, the zero phase filter is introduced to the mentioned filter, and a fault diagnosis method for speed-changing gearbox is proposed. Firstly, the gear meshing frequency of each gearbox is estimated by chirplet path pursuit. Then, according to the estimated gear meshing frequencies, an adaptive zero phase time-varying filter(AZPTF) is designed to filter the original signal. Finally, the basis for fault diagnosis is acquired by the envelope order analysis to the filtered signal. The signal consisting of two time-varying amplitude modulation and frequency modulation(AM-FM) signals is respectively analyzed by ATF and AZPTF based on MCSSD. The simulation results show the variances between the original signals and the filtered signals yielded by AZPTF based on MCSSD are 13.67 and 41.14, which are far less than variances (323.45 and 482.86) between the original signals and the filtered signals obtained by ATF based on MCSSD. The experiment results on the vibration signals of gearboxes indicate that the vibration signals of the two speed-changing gearboxes installed on one foundation bed can be separated by AZPTF effectively. Based on the demodulation information of the vibration signal of each gearbox, the fault diagnosis can be implemented. Both simulation and experiment examples prove that the proposed filter can extract a mono-component time-varying AM-FM signal from the multi-component time-varying AM-FM signal without distortion.
基金supported by the State Grid Science and Technology Project (Title: Technology Research On Large Scale EMT Real-time simulation customized platform, FX71-17-001)
文摘As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.
文摘Background: The Shelduck (Tadorna tadorna) is a characteristic waterbird species of inland wetlands in northeastern Algeria. Its wintering behavior in relation to changes of local abundances and foraging group density is poorly known. Objectives: This study aims at monitoring patterns of diurnal activities and the variation of behavioral time-budgets in relation to numbers of wintering Shelducks. We investigate temporal variations of diurnal activities across multipletime scales and consider their interrelationships. Methods: Assessments of local population abundance were weekly surveyed during two wintering seasons (2010– 2012), whereas diurnal activities (feeding, sleeping, swimming, preening, loafing, flying, courtship, and antagonism) were studied three times a month during seven hours (08:00–16:00) using the Scan method. Time budget variations of each behavioral activity were tested using nested ANOVAs following multiple time scales. Generalized linear mixedeffects models (GLMM) tested whether variations in diurnal activities were density-dependent. Results: During the wintering season, Shelduck’s numbers followed a bell-shaped trend, which indicated that the species was typically a wintering migrant in Sabkha Djendli. The first individuals arrived onsite in October–November then numbers reached a peak in January (up to 2400 individuals in 2012) with steady density during December–February, afterward individuals left the site progressively until late April when the site is deserted. During both wintering seasons, diurnal activities were dominated by feeding (60%), followed by sleeping (12%) then swimming and preening with 9% and 8%, respectively. The rest of the activities (loafing, flying, courtship and antagonistic behaviors) had low proportions of time budget. ANOVAs showed that activity time budgets varied significantly following multiple time scales (year, season, month, day, semi-hour). Time budgets of diurnal activities during each wintering season were significantly interrelated. Correlations patterns between the two seasons were similar. GLMMs revealed that the variations of diurnal activities were not density-dependent, except for preening and swimming. Conclusion: During the wintering season, habitats of Sabkha Djendli are important for waterbirds, including the Shelduck that used the lake mainly for food-foraging and resting. The 2400 individuals censused in mid-winter are important locally and at the North African scale. This stresses the need to strengthen the protection status of this wetland and mitigate degradation sources that threaten wintering waterfowl.
文摘The improvements of high-throughput experimental devices such as microarray and mass spectrometry have allowed an effective acquisition of biological comprehensive data which include genome, transcriptome, proteome, and metabolome (multi-layered omics data). In Systems Biology, we try to elucidate various dynamical characteristics of biological functions with applying the omics data to detailed mathematical model based on the central dogma. However, such mathematical models possess multi-time-scale properties which are often accompanied by time-scale differences seen among biological layers. The differences cause time stiff problem, and have a grave influence on numerical calculation stability. In the present conventional method, the time stiff problem remained because the calculation of all layers was implemented by adaptive time step sizes of the smallest time-scale layer to ensure stability and maintain calculation accuracy. In this paper, we designed and developed an effective numerical calculation method to improve the time stiff problem. This method consisted of ahead, backward, and cumulative algorithms. Both ahead and cumulative algorithms enhanced calculation efficiency of numerical calculations via adjustments of step sizes of each layer, and reduced the number of numerical calculations required for multi-time-scale models with the time stiff problem. Backward algorithm ensured calculation accuracy in the multi-time-scale models. In case studies which were focused on three layers system with 60 times difference in time-scale order in between layers, a proposed method had almost the same calculation accuracy compared with the conventional method in spite of a reduction of the total amount of the number of numerical calculations. Accordingly, the proposed method is useful in a numerical analysis of multi-time-scale models with time stiff problem.
文摘柔性负荷参与新型电力系统的优化调度对于提高新能源的消纳能力具有显著作用,但目前柔性负荷潜力尚未充分挖掘。针对这一问题,提出一种基于源荷预测的日前-日内优化调度方法。首先,采用麻雀搜索算法优化卷积长短时记忆神经网络(sparrow search algorithm is used to optimize the convolutional long-term and short-term memory neural network,SSA-CNN-LSTM)对新能源和负荷进行日前和日内功率预测;其次,根据柔性负荷的特性和需求响应灵活性,将负荷分为可平移、可转移和可削减负荷等不同类型,以考虑阶梯式碳交易成本的系统运行成本和污染气体排放最优为目标构建源荷互动的日前-日内两阶段低碳环境经济调度模型;最后,利用改进多目标灰狼算法(multi-objective grey wolf algorithm,MOGWO)对模型进行求解。算例分析表明,通过对柔性负荷分类参与调度较传统方式总成本降低8.6%、污染物排放减少4.1%、新能源消纳能力提高4.2%,在多时间尺度内显著降低新能源和负荷响应的不确定性并提高新型电力系统的低碳环境经济综合效益。
