Data Center of Xinjiang Astronomical Observatory(XAO-DC)commenced operating in 2015,and provides services including archiving,releasing and retrieving precious astronomical data collected by the Nanshan 26 m Radio Tel...Data Center of Xinjiang Astronomical Observatory(XAO-DC)commenced operating in 2015,and provides services including archiving,releasing and retrieving precious astronomical data collected by the Nanshan 26 m Radio Telescope(NSRT)over the years,and realises the open sharing of astronomical observation data.The observation data from NSRT are transmitted to XAO-DC 100 km away through dedicated fiber for long-term storage.With the continuous increase of data,the static architecture of the current network cannot meet NSRT data-transmission requirements due to limited network bandwidth.To get high-speed data-transmission using the existing static network architecture,a method for reconstruction data-transmission network using Software-Defined Networks(SDN)is proposed.Benefit from the SDN’s data and control plane separation,and open programmable,combined with the Mininet simulation platform for experiments,the TCP throughput(of single thread)was improved by~24.7%,the TCP throughput(of multi threads)was improved by~9.8%,~40.9%,~35.5%and~11.7%.Compared with the current network architecture,the Latency was reduced by~63.2%.展开更多
Support vector machines and a Kalman-like observer are used for fault detection and isolation in a variable speed horizontalaxis wind turbine composed of three blades and a full converter. The support vector approach ...Support vector machines and a Kalman-like observer are used for fault detection and isolation in a variable speed horizontalaxis wind turbine composed of three blades and a full converter. The support vector approach is data-based and is therefore robust to process knowledge. It is based on structural risk minimization which enhances generalization even with small training data set and it allows for process nonlinearity by using flexible kernels. In this work, a radial basis function is used as the kernel. Different parts of the process are investigated including actuators and sensors faults. With duplicated sensors, sensor faults in blade pitch positions,generator and rotor speeds can be detected. Faults of type stuck measurements can be detected in 2 sampling periods. The detection time of offset/scaled measurements depends on the severity of the fault and on the process dynamics when the fault occurs. The converter torque actuator fault can be detected within 2 sampling periods. Faults in the actuators of the pitch systems represents a higher difficulty for fault detection which is due to the fact that such faults only affect the transitory state(which is very fast) but not the final stationary state. Therefore, two methods are considered and compared for fault detection and isolation of this fault: support vector machines and a Kalman-like observer. Advantages and disadvantages of each method are discussed. On one hand, support vector machines training of transitory states would require a big amount of data in different situations, but the fault detection and isolation results are robust to variations in the input/operating point. On the other hand, the observer is model-based, and therefore does not require training, and it allows identification of the fault level, which is interesting for fault reconfiguration. But the observability of the system is ensured under specific conditions, related to the dynamics of the inputs and outputs. The whole fault detection and isolation scheme is evaluated using a wind turbine benchmark with a real sequence of wind speed.展开更多
基金the National Natural Science Foundation of China(NSFC,Grant Nos.11803080,11873082 and 12003062)the National Key Research and Development Program of China(2018YFA0404704)+3 种基金the Youth Innovation Promotion Association,Chinese Academy of Sciences(CAS)the program of the Light in China’s Western Region(2019-XBQNXZ-B-018)supported by China National Astronomical Data Center(NADC)supported by Astronomical Big Data Joint Research Center,co-founded by National Astronomical Observatories,CAS。
文摘Data Center of Xinjiang Astronomical Observatory(XAO-DC)commenced operating in 2015,and provides services including archiving,releasing and retrieving precious astronomical data collected by the Nanshan 26 m Radio Telescope(NSRT)over the years,and realises the open sharing of astronomical observation data.The observation data from NSRT are transmitted to XAO-DC 100 km away through dedicated fiber for long-term storage.With the continuous increase of data,the static architecture of the current network cannot meet NSRT data-transmission requirements due to limited network bandwidth.To get high-speed data-transmission using the existing static network architecture,a method for reconstruction data-transmission network using Software-Defined Networks(SDN)is proposed.Benefit from the SDN’s data and control plane separation,and open programmable,combined with the Mininet simulation platform for experiments,the TCP throughput(of single thread)was improved by~24.7%,the TCP throughput(of multi threads)was improved by~9.8%,~40.9%,~35.5%and~11.7%.Compared with the current network architecture,the Latency was reduced by~63.2%.
文摘Support vector machines and a Kalman-like observer are used for fault detection and isolation in a variable speed horizontalaxis wind turbine composed of three blades and a full converter. The support vector approach is data-based and is therefore robust to process knowledge. It is based on structural risk minimization which enhances generalization even with small training data set and it allows for process nonlinearity by using flexible kernels. In this work, a radial basis function is used as the kernel. Different parts of the process are investigated including actuators and sensors faults. With duplicated sensors, sensor faults in blade pitch positions,generator and rotor speeds can be detected. Faults of type stuck measurements can be detected in 2 sampling periods. The detection time of offset/scaled measurements depends on the severity of the fault and on the process dynamics when the fault occurs. The converter torque actuator fault can be detected within 2 sampling periods. Faults in the actuators of the pitch systems represents a higher difficulty for fault detection which is due to the fact that such faults only affect the transitory state(which is very fast) but not the final stationary state. Therefore, two methods are considered and compared for fault detection and isolation of this fault: support vector machines and a Kalman-like observer. Advantages and disadvantages of each method are discussed. On one hand, support vector machines training of transitory states would require a big amount of data in different situations, but the fault detection and isolation results are robust to variations in the input/operating point. On the other hand, the observer is model-based, and therefore does not require training, and it allows identification of the fault level, which is interesting for fault reconfiguration. But the observability of the system is ensured under specific conditions, related to the dynamics of the inputs and outputs. The whole fault detection and isolation scheme is evaluated using a wind turbine benchmark with a real sequence of wind speed.
