In the designed automatic balancing head, a non contact induction transformer is used to deliver driving energy to solve the problem of current fed and controlling on line. Computer controlled automatic balancing expe...In the designed automatic balancing head, a non contact induction transformer is used to deliver driving energy to solve the problem of current fed and controlling on line. Computer controlled automatic balancing experiments with phase magnitude control tactics were performed on a flexible rotor system. Results of the experiments prove that the energy feeding method and the control tactics are effective in the automatic balancing head for vibration controlling.展开更多
This paper analyzes the advantages and disadvantages of two techni-cal lines for automatic group generalization of contour lines.The author suggeststhat it is possible to get faster and better generalization results i...This paper analyzes the advantages and disadvantages of two techni-cal lines for automatic group generalization of contour lines.The author suggeststhat it is possible to get faster and better generalization results if we simulate theintelligence of human experts in program designing,retrieve geomorphologicalstructural information using the input data of 2-D contour lines and derive andoutput the generalied 2-D results directly.展开更多
Busbar Automatic Transfer Switch (BATS) is very important for power distribution reliability. However, BATS can’t consider whether it cause overloading of devices after it acts. In this paper, we introduce the design...Busbar Automatic Transfer Switch (BATS) is very important for power distribution reliability. However, BATS can’t consider whether it cause overloading of devices after it acts. In this paper, we introduce the design principle of Automatic BATS control from whole architecture including its function, strategy and a rule of on-off. On the other hand, the running experience and effect is also introduced. Site operation shows that the proposed method is feasible and it can ensure power grid reliability.展开更多
This paper presents an automatic system for failure detection in hydro-power generators. The main idea of this system is to detect failure using current and voltage signals acquired without any type of internal interf...This paper presents an automatic system for failure detection in hydro-power generators. The main idea of this system is to detect failure using current and voltage signals acquired without any type of internal interference in the generator operation. The detected failures could be mechanical or electrical origins, such as: problems in bearings, unwanted vibrations, partial discharges, misalignment, unbalancing, among others. It is possible because the generator acts as a transducer for mechanical problems, and they appear in current and voltage signals. This automatic system based on electric signature analysis has been installed in Itapebi Power Plant generators since 2012. Some results are presented in this paper.展开更多
Given the escalating intricacy and multifaceted nature of contemporary social systems,manually generating solutions to address pertinent social issues has become a formidable task.In response to this challenge,the rap...Given the escalating intricacy and multifaceted nature of contemporary social systems,manually generating solutions to address pertinent social issues has become a formidable task.In response to this challenge,the rapid development of artificial intelligence has spurred the exploration of computational methodologies aimed at automatically generating solutions.However,current methods for the auto-generation of solutions mainly concentrate on local social regulations that pertain to specific scenarios.Here,we report an automatic social operating system(ASOS)designed for general social solution generation built upon agent-based models that enables both global and local analyses and regulations of social problems across spatial and temporal dimensions.ASOS adopts a hypergraph with extensible social semantics for a comprehensive and structured representation of social dynamics.It also incorporates a generalized protocol for standardized hypergraph operations and a symbolic hybrid framework that delivers interpretable solutions,yielding a balance between regulatory efficacy and functional viability.To demonstrate the effectiveness of the ASOS,we apply it to the domain of averting extreme events within international oil futures markets.By generating a new trading role supplemented by new mechanisms,ASOS can adeptly discern precarious market conditions and make front-running interventions for nonprofit purposes.This study demonstrated that ASOS provides an efficient and systematic approach for generating solutions for enhancing our society.展开更多
Automatic generalization of geographic information is the core of multi_scale representation of spatial data,but the scale_dependent generalization methods are far from abundant because of its extreme complicacy.This ...Automatic generalization of geographic information is the core of multi_scale representation of spatial data,but the scale_dependent generalization methods are far from abundant because of its extreme complicacy.This paper puts forward a new consistency model about scale_dependent representations of relief based on wavelet analysis,and discusses the thresholds in the model so as to acquire the continual representations of relief with different details between scales.The model not only meets the need of automatic generalization but also is scale-dependent completely.Some practical examples are given.展开更多
Due to the influence of terrain structure,meteorological conditions and various factors,there are anomalous data in automatic dependent surveillance-broadcast(ADS-B)message.The ADS-B equipment can be used for position...Due to the influence of terrain structure,meteorological conditions and various factors,there are anomalous data in automatic dependent surveillance-broadcast(ADS-B)message.The ADS-B equipment can be used for positioning of general aviation aircraft.Aim to acquire the accurate position information of aircraft and detect anomaly data,the ADS-B anomaly data detection model based on deep learning and difference of Gaussian(DoG)approach is proposed.First,according to the characteristic of ADS-B data,the ADS-B position data are transformed into the coordinate system.And the origin of the coordinate system is set up as the take-off point.Then,based on the kinematic principle,the ADS-B anomaly data can be removed.Moreover,the details of the ADS-B position data can be got by the DoG approach.Finally,the long short-term memory(LSTM)neural network is used to optimize the recurrent neural network(RNN)with severe gradient reduction for processing ADS-B data.The position data of ADS-B are reconstructed by the sequence to sequence(seq2seq)model which is composed of LSTM neural network,and the reconstruction error is used to detect the anomalous data.Based on the real flight data of general aviation aircraft,the simulation results show that the anomaly data can be detected effectively by the proposed method of reconstructing ADS-B data with the seq2seq model,and its running time is reduced.Compared with the RNN,the accuracy of anomaly detection is increased by 2.7%.The performance of the proposed model is better than that of the traditional anomaly detection models.展开更多
The automatic detection and identification of electroencephalogram waves play an important role in the prediction, diagnosis and treatment of epileptic seizures. In this study, a nonlinear dynamics index–approximate ...The automatic detection and identification of electroencephalogram waves play an important role in the prediction, diagnosis and treatment of epileptic seizures. In this study, a nonlinear dynamics index–approximate entropy and a support vector machine that has strong generalization ability were applied to classify electroencephalogram signals at epileptic interictal and ictal periods. Our aim was to verify whether approximate entropy waves can be effectively applied to the automatic real-time detection of epilepsy in the electroencephalogram, and to explore its generalization ability as a classifier trained using a nonlinear dynamics index. Four patients presenting with partial epileptic seizures were included in this study. They were all diagnosed with neocortex localized epilepsy and epileptic foci were clearly observed by electroencephalogram. The electroencephalogram data form the four involved patients were segmented and the characteristic values of each segment, that is, the approximate entropy, were extracted. The support vector machine classifier was constructed with the approximate entropy extracted from one epileptic case, and then electroencephalogram waves of the other three cases were classified, reaching a 93.33% accuracy rate. Our findings suggest that the use of approximate entropy allows the automatic real-time detection of electroencephalogram data in epileptic cases. The combination of approximate entropy and support vector machines shows good generalization ability for the classification of electroencephalogram signals for epilepsy.展开更多
The high penetration of wind energy sources in power systems has substantially increased the demand for faster-ramping thermal units participating in the frequency regulation service.To fulfill the automatic generatio...The high penetration of wind energy sources in power systems has substantially increased the demand for faster-ramping thermal units participating in the frequency regulation service.To fulfill the automatic generation control(AGC)and compensate the influence of wind power fluctuations simultaneously,ramping capacity should be considered in the dispatch model of thermals.Meanwhile,conventional methods in this area do not take the impact of transmission loss into the dispatch model,or rely on offline network model and parameters,failing to reflect the real relationships between the wind farms and thermal generators.This paper proposes an online approach for AGC dispatch units considering the above issues.Firstly,the power loss sensitivity is online identified using recursive least square method based on the real-time data of phasor measurement units.It sets up power balance constraint and results in a more accurate dispatch model.Then,an improved multi-objective optimization model of dispatch is proposed and a connection is established between the thermal units with fast ramping capacity and the wind farms with rapid fluctuations.Genetic algorithm is used to solve the dispatch model.The proposed method is compared with conventional methods in simulation case in the IEEE 30-bus system.Finally,simulation results verify the validity and the feasibility of identification method and optimization model.展开更多
文摘In the designed automatic balancing head, a non contact induction transformer is used to deliver driving energy to solve the problem of current fed and controlling on line. Computer controlled automatic balancing experiments with phase magnitude control tactics were performed on a flexible rotor system. Results of the experiments prove that the energy feeding method and the control tactics are effective in the automatic balancing head for vibration controlling.
文摘This paper analyzes the advantages and disadvantages of two techni-cal lines for automatic group generalization of contour lines.The author suggeststhat it is possible to get faster and better generalization results if we simulate theintelligence of human experts in program designing,retrieve geomorphologicalstructural information using the input data of 2-D contour lines and derive andoutput the generalied 2-D results directly.
文摘Busbar Automatic Transfer Switch (BATS) is very important for power distribution reliability. However, BATS can’t consider whether it cause overloading of devices after it acts. In this paper, we introduce the design principle of Automatic BATS control from whole architecture including its function, strategy and a rule of on-off. On the other hand, the running experience and effect is also introduced. Site operation shows that the proposed method is feasible and it can ensure power grid reliability.
文摘This paper presents an automatic system for failure detection in hydro-power generators. The main idea of this system is to detect failure using current and voltage signals acquired without any type of internal interference in the generator operation. The detected failures could be mechanical or electrical origins, such as: problems in bearings, unwanted vibrations, partial discharges, misalignment, unbalancing, among others. It is possible because the generator acts as a transducer for mechanical problems, and they appear in current and voltage signals. This automatic system based on electric signature analysis has been installed in Itapebi Power Plant generators since 2012. Some results are presented in this paper.
基金supported by the National Key Research and Development Program of China(No.2021ZD0200300)the National Nature Science Foundation of China(Nos.61836004 and 62088102)the IDG/McGovern Institute for Brain Research at Tsinghua University,China.
文摘Given the escalating intricacy and multifaceted nature of contemporary social systems,manually generating solutions to address pertinent social issues has become a formidable task.In response to this challenge,the rapid development of artificial intelligence has spurred the exploration of computational methodologies aimed at automatically generating solutions.However,current methods for the auto-generation of solutions mainly concentrate on local social regulations that pertain to specific scenarios.Here,we report an automatic social operating system(ASOS)designed for general social solution generation built upon agent-based models that enables both global and local analyses and regulations of social problems across spatial and temporal dimensions.ASOS adopts a hypergraph with extensible social semantics for a comprehensive and structured representation of social dynamics.It also incorporates a generalized protocol for standardized hypergraph operations and a symbolic hybrid framework that delivers interpretable solutions,yielding a balance between regulatory efficacy and functional viability.To demonstrate the effectiveness of the ASOS,we apply it to the domain of averting extreme events within international oil futures markets.By generating a new trading role supplemented by new mechanisms,ASOS can adeptly discern precarious market conditions and make front-running interventions for nonprofit purposes.This study demonstrated that ASOS provides an efficient and systematic approach for generating solutions for enhancing our society.
基金ProjectsupportedbytheNationalScienceFoundationofSurveyingandMappingofChina (No .990 1 3) .
文摘Automatic generalization of geographic information is the core of multi_scale representation of spatial data,but the scale_dependent generalization methods are far from abundant because of its extreme complicacy.This paper puts forward a new consistency model about scale_dependent representations of relief based on wavelet analysis,and discusses the thresholds in the model so as to acquire the continual representations of relief with different details between scales.The model not only meets the need of automatic generalization but also is scale-dependent completely.Some practical examples are given.
基金supported by the National Key R&D Program of China(No.2018AAA0100804)the Talent Project of Revitalization Liaoning(No.XLYC1907022)+5 种基金the Key R&D Projects of Liaoning Province(No.2020JH2/10100045)the Capacity Building of Civil Aviation Safety(No.TMSA1614)the Natural Science Foundation of Liaoning Province(No.2019-MS-251)the Scientific Research Project of Liaoning Provincial Department of Education(Nos.L201705,L201716)the High-Level Innovation Talent Project of Shenyang(No.RC190030)the Second Young and Middle-Aged Talents Support Program of Shenyang Aerospace University.
文摘Due to the influence of terrain structure,meteorological conditions and various factors,there are anomalous data in automatic dependent surveillance-broadcast(ADS-B)message.The ADS-B equipment can be used for positioning of general aviation aircraft.Aim to acquire the accurate position information of aircraft and detect anomaly data,the ADS-B anomaly data detection model based on deep learning and difference of Gaussian(DoG)approach is proposed.First,according to the characteristic of ADS-B data,the ADS-B position data are transformed into the coordinate system.And the origin of the coordinate system is set up as the take-off point.Then,based on the kinematic principle,the ADS-B anomaly data can be removed.Moreover,the details of the ADS-B position data can be got by the DoG approach.Finally,the long short-term memory(LSTM)neural network is used to optimize the recurrent neural network(RNN)with severe gradient reduction for processing ADS-B data.The position data of ADS-B are reconstructed by the sequence to sequence(seq2seq)model which is composed of LSTM neural network,and the reconstruction error is used to detect the anomalous data.Based on the real flight data of general aviation aircraft,the simulation results show that the anomaly data can be detected effectively by the proposed method of reconstructing ADS-B data with the seq2seq model,and its running time is reduced.Compared with the RNN,the accuracy of anomaly detection is increased by 2.7%.The performance of the proposed model is better than that of the traditional anomaly detection models.
基金financially supported by the National Natural Science Foundation of China,No.61263011,81000554Program in Sun Yat-sen University supported by Fundamental Research Funds for the Central Universities,No.11ykpy07+1 种基金Natural Science Foundation of Guangdong Province,No.S2011010005309Innovation Fund of Xinjiang Medical University,No.XJC201209
文摘The automatic detection and identification of electroencephalogram waves play an important role in the prediction, diagnosis and treatment of epileptic seizures. In this study, a nonlinear dynamics index–approximate entropy and a support vector machine that has strong generalization ability were applied to classify electroencephalogram signals at epileptic interictal and ictal periods. Our aim was to verify whether approximate entropy waves can be effectively applied to the automatic real-time detection of epilepsy in the electroencephalogram, and to explore its generalization ability as a classifier trained using a nonlinear dynamics index. Four patients presenting with partial epileptic seizures were included in this study. They were all diagnosed with neocortex localized epilepsy and epileptic foci were clearly observed by electroencephalogram. The electroencephalogram data form the four involved patients were segmented and the characteristic values of each segment, that is, the approximate entropy, were extracted. The support vector machine classifier was constructed with the approximate entropy extracted from one epileptic case, and then electroencephalogram waves of the other three cases were classified, reaching a 93.33% accuracy rate. Our findings suggest that the use of approximate entropy allows the automatic real-time detection of electroencephalogram data in epileptic cases. The combination of approximate entropy and support vector machines shows good generalization ability for the classification of electroencephalogram signals for epilepsy.
基金This work is supported in part by Major State Basic Research Development Program of China(No.2012CB215206)National Natural Science Foundation of China(No.51107061).
文摘The high penetration of wind energy sources in power systems has substantially increased the demand for faster-ramping thermal units participating in the frequency regulation service.To fulfill the automatic generation control(AGC)and compensate the influence of wind power fluctuations simultaneously,ramping capacity should be considered in the dispatch model of thermals.Meanwhile,conventional methods in this area do not take the impact of transmission loss into the dispatch model,or rely on offline network model and parameters,failing to reflect the real relationships between the wind farms and thermal generators.This paper proposes an online approach for AGC dispatch units considering the above issues.Firstly,the power loss sensitivity is online identified using recursive least square method based on the real-time data of phasor measurement units.It sets up power balance constraint and results in a more accurate dispatch model.Then,an improved multi-objective optimization model of dispatch is proposed and a connection is established between the thermal units with fast ramping capacity and the wind farms with rapid fluctuations.Genetic algorithm is used to solve the dispatch model.The proposed method is compared with conventional methods in simulation case in the IEEE 30-bus system.Finally,simulation results verify the validity and the feasibility of identification method and optimization model.
