To solve the fault diagnosis problem of liquid propellant rocket engine ground testing bed,a fault diagnosis approach based on self-organizing map(SOM)is proposed.The SOM projects the multidimensional ground testing b...To solve the fault diagnosis problem of liquid propellant rocket engine ground testing bed,a fault diagnosis approach based on self-organizing map(SOM)is proposed.The SOM projects the multidimensional ground testing bed data into a two-dimensional map.Visualization of the SOM is used to cluster the ground testing bed data.The out map of the SOM is divided to several regions.Each region is represented for one fault mode.The fault mode of testing data is determined according to the region of their labels belonged to.The method is evaluated using the testing data of a liquid-propellant rocket engine ground testing bed with sixteen fault states.The results show that it is a reliable and effective method for fault diagnosis with good visualization property.展开更多
Coordinated numerical ensemble experiments with six different state-of-the-art atmosphere models were used to evaluate and quantify the impact of global SST(from reanalysis data)on the early winter Arctic warming duri...Coordinated numerical ensemble experiments with six different state-of-the-art atmosphere models were used to evaluate and quantify the impact of global SST(from reanalysis data)on the early winter Arctic warming during 1982-2014.Two sets of experiments were designed:in the first set(EXP1),OISSTv2 daily sea-ice concentration and SST variations were used as the lower boundary forcing,while in the second set(EXP2)the SST data were replaced by the daily SST climatology.In the results,the multi-model ensemble mean of EXP1 showed a nearsurface(~850 hPa)warming trend of 0.4℃/10 yr,which was 80%of the warming trend in the reanalysis.The simulated warming trend was robust across the six models,with a magnitude of 0.36-0.50℃/10 yr.The global SST could explain most of the simulated warming trend in EXP1 in the mid and low troposphere over the Arctic,and accounted for 58%of the simulated near-surface warming.The results also suggest that the uppertropospheric warming(~200 hPa)over the Arctic in the reanalysis is likely not a forced signal;rather,it is caused by natural climate variability.The source regions that can potentially impact the early winter Arctic warming are explored and the limitations of the study are discussed.展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant No. NSFC-60572010)
文摘To solve the fault diagnosis problem of liquid propellant rocket engine ground testing bed,a fault diagnosis approach based on self-organizing map(SOM)is proposed.The SOM projects the multidimensional ground testing bed data into a two-dimensional map.Visualization of the SOM is used to cluster the ground testing bed data.The out map of the SOM is divided to several regions.Each region is represented for one fault mode.The fault mode of testing data is determined according to the region of their labels belonged to.The method is evaluated using the testing data of a liquid-propellant rocket engine ground testing bed with sixteen fault states.The results show that it is a reliable and effective method for fault diagnosis with good visualization property.
基金supported by the National Key R&D Program of China[grant number 2017YFE0111800]the National Natural Science Foundation of China[grant numbers 41790472 and 41661144005]partly supported by the EU H2020 Blue-Action project[grant number 727852]。
文摘Coordinated numerical ensemble experiments with six different state-of-the-art atmosphere models were used to evaluate and quantify the impact of global SST(from reanalysis data)on the early winter Arctic warming during 1982-2014.Two sets of experiments were designed:in the first set(EXP1),OISSTv2 daily sea-ice concentration and SST variations were used as the lower boundary forcing,while in the second set(EXP2)the SST data were replaced by the daily SST climatology.In the results,the multi-model ensemble mean of EXP1 showed a nearsurface(~850 hPa)warming trend of 0.4℃/10 yr,which was 80%of the warming trend in the reanalysis.The simulated warming trend was robust across the six models,with a magnitude of 0.36-0.50℃/10 yr.The global SST could explain most of the simulated warming trend in EXP1 in the mid and low troposphere over the Arctic,and accounted for 58%of the simulated near-surface warming.The results also suggest that the uppertropospheric warming(~200 hPa)over the Arctic in the reanalysis is likely not a forced signal;rather,it is caused by natural climate variability.The source regions that can potentially impact the early winter Arctic warming are explored and the limitations of the study are discussed.
