Based on previous research work,we present a spectrum deviation method to recognize a foreshock or generalized foreshock in this paper. The criterion to determine whether an event is a foreshock is a wide spectrum for...Based on previous research work,we present a spectrum deviation method to recognize a foreshock or generalized foreshock in this paper. The criterion to determine whether an event is a foreshock is a wide spectrum for an ordinary event,however,a moderate earthquake with foreshock or generalized foreshock has the characteristics of a narrow frequency band,and it deviates to the low frequency. It may be explained by metastable extension in the rupture source or related area of the main shock or regional fragmentation damage and crack nucleation process. The calculation results of two foreshocks,the M_S4. 7 event which occurred before the Yushu M_S7. 1 earthquake on April 14,2010 and the M_S5. 3 event which occurred before the Yutian M_S7. 3 earthquake on February 12,2014,show that the spectra of foreshocks shift,and they are quite different from the nonforeshock seismic spectrum of equivalent size. Therefore,this result can verify the validity of the spectrum deviation method.展开更多
A novel damage detection method is applied to a 3-story frame structure, to obtain statistical quantification control criterion of the existence, location and identification of damage. The mean, standard deviation, an...A novel damage detection method is applied to a 3-story frame structure, to obtain statistical quantification control criterion of the existence, location and identification of damage. The mean, standard deviation, and exponentially weighted moving average （EWMA） are applied to detect damage information according to statistical process control （SPC） theory. It is concluded that the detection is insignificant with the mean and EWMA because the structural response is not independent and is not a normal distribution. On the other hand, the damage information is detected well with the standard deviation because the influence of the data distribution is not pronounced with this parameter. A suitable moderate confidence level is explored for more significant damage location and quantification detection, and the impact of noise is investigated to illustrate the robustness of the method.展开更多
Based on Bishop's model and by applying the first and second order mean deviations method, an approximative solution method for the first and second order partial derivatives of functional function was deduced acc...Based on Bishop's model and by applying the first and second order mean deviations method, an approximative solution method for the first and second order partial derivatives of functional function was deduced according to numerical analysis theory. After complicated multi-independent variables implicit functional function was simplified to be a single independent variable implicit function and rule of calculating derivative for composite function was combined with principle of the mean deviations method, an approximative solution format of implicit functional function was established through Taylor expansion series and iterative solution approach of reliability degree index was given synchronously. An engineering example was analyzed by the method. The result shows its absolute error is only 0.78% as compared with accurate solution.展开更多
Standard deviation(SD)and standard error of the mean(SEM)have been applied widely as error bars in scientific plots.Unfortunately,there is no universally accepted principle addressing which of these 2 measures should ...Standard deviation(SD)and standard error of the mean(SEM)have been applied widely as error bars in scientific plots.Unfortunately,there is no universally accepted principle addressing which of these 2 measures should be used.Here we seek to fill this gap by outlining the reasoning for choosing SEM over SD and hope to shed light on this unsettled disagreement among the biomedical community.The utility of SEM and SD as error bars is further discussed by examining the figures and plots published in 2 research articles on pancreatic disease.展开更多
This paper considers the consensus problem of a group of homogeneous agents.These agents are governed by a general linear system and can only directly measure the output,instead of the state.In order to achieve the co...This paper considers the consensus problem of a group of homogeneous agents.These agents are governed by a general linear system and can only directly measure the output,instead of the state.In order to achieve the consensus goal,each agent estimates its state through a Luenberger observer,exchanges its estimated state with neighbors,and constructs the control input with the estimated states of its own and neighbors.Due to the existence of observation and process noises,only practical consensus,instead of asymptotical consensus,can be achieved in such multi-agent systems.The performance of the achieved practical consensus can be measured by the ultimate mean square deviation of the states of agents.That performance is closely related to the observation gains of the state observers and the control gains of agents.This paper proposes a method to optimize such performance with respect to the concerned observation and control gains.That method starts with a set of feasible observation and control gains and formulates a group of linear matrix inequalities(LMIs).Solving these LMIs gives some intermediate matrix variables.By perturbing observation and control gains,and the intermediate matrix variables,the original LMIs yield another group of LMIs,which can be solved to provide a descent direction of observation and control gains.Moving along that descent direction,observation and control gains can be improved to yield better performance and work as the starting point of the next iteration.By iteratively repeating this procedure,we can hopefully improve the consensus performance of the concerned multi-agent system.Simulations are done to demonstrate the effectiveness of the proposed method.展开更多
针对FasterVit网络存在的注意力机制失衡、池化策略缺陷导致部分重要特征无法保留和损失函数不能全面考虑所有类别的信息导致学习到的特征比较分散等问题,提出了一种基于CFasterVit-三并联分支融合注意力机制(triple-parallel fusion at...针对FasterVit网络存在的注意力机制失衡、池化策略缺陷导致部分重要特征无法保留和损失函数不能全面考虑所有类别的信息导致学习到的特征比较分散等问题,提出了一种基于CFasterVit-三并联分支融合注意力机制(triple-parallel fusion attention model,TFAM)与余弦均匀流形逼近与投影(cosineuniform manifold approximation and projection,COS-UMAP)模型的滚动轴承故障诊断方法。该模型由FasterVit-TFAM网络、COS-UMAP降维算法和激活函数类距均值标准差损失函数(class-distance mean standard deviation loss,CMSD)-Softmax组成。首先,提出了一种新的注意力机制TFAM,并与FasterVit网络结合,提升了FasterVit网络信息关注的均衡性和表征能力;其次,将基于COS-UMAP降维算法取代FasterVit网络全连接层前最后一次池化操作,有效筛选并保留多维数据中的重要特征;最后,将类距均值标准差损失函数替换Softmax激活函数中的交叉熵损失函数,更全面地学习特征并提高模型的泛化性。西安交通大学滚动轴承数据集滚动轴承故障试验结果表明,TFAM注意力机制和其他注意力机制相比诊断准确率最大提升8.0%,COS-UMAP对比其他降维算法诊断准确率最大提升15.8%,CMSD对比交叉熵损失函数诊断准确率提升0.5%,所提模型对故障样本的识别准确率达到了99.6%,相比FasterVit提升了1.4%,相较于其他网络模型最大提升7.8%;东南大学滚动轴承数据集仿真验证试验结果表明,所提模型对故障样本识别率达98.6%,相比FasterVit提升了2.2%,平均每轮训练时间缩短了16.92 s,对比其他网络模型最大提升12.2%,有效提高了滚动轴承故障诊断模型的准确率和泛化性能。展开更多
基金sponsored by the National Key Technology Support Program of China entitled "Application of Digital Seismic Technology to Mid-and Short-term Prediction of Strong Earthquake"(2012BAK19B02-01)
文摘Based on previous research work,we present a spectrum deviation method to recognize a foreshock or generalized foreshock in this paper. The criterion to determine whether an event is a foreshock is a wide spectrum for an ordinary event,however,a moderate earthquake with foreshock or generalized foreshock has the characteristics of a narrow frequency band,and it deviates to the low frequency. It may be explained by metastable extension in the rupture source or related area of the main shock or regional fragmentation damage and crack nucleation process. The calculation results of two foreshocks,the M_S4. 7 event which occurred before the Yushu M_S7. 1 earthquake on April 14,2010 and the M_S5. 3 event which occurred before the Yutian M_S7. 3 earthquake on February 12,2014,show that the spectra of foreshocks shift,and they are quite different from the nonforeshock seismic spectrum of equivalent size. Therefore,this result can verify the validity of the spectrum deviation method.
基金Natural Natural Science Foundation of China Under Grant No 50778077 & 50608036the Graduate Innovation Fund of Huazhong University of Science and Technology Under Grant No HF-06-028
文摘A novel damage detection method is applied to a 3-story frame structure, to obtain statistical quantification control criterion of the existence, location and identification of damage. The mean, standard deviation, and exponentially weighted moving average （EWMA） are applied to detect damage information according to statistical process control （SPC） theory. It is concluded that the detection is insignificant with the mean and EWMA because the structural response is not independent and is not a normal distribution. On the other hand, the damage information is detected well with the standard deviation because the influence of the data distribution is not pronounced with this parameter. A suitable moderate confidence level is explored for more significant damage location and quantification detection, and the impact of noise is investigated to illustrate the robustness of the method.
基金Project(50378036) supported by the National Natural Science Foundation of ChinaProject(200503) supported by Foundation of Communications Department of Hunan Province, China
文摘Based on Bishop's model and by applying the first and second order mean deviations method, an approximative solution method for the first and second order partial derivatives of functional function was deduced according to numerical analysis theory. After complicated multi-independent variables implicit functional function was simplified to be a single independent variable implicit function and rule of calculating derivative for composite function was combined with principle of the mean deviations method, an approximative solution format of implicit functional function was established through Taylor expansion series and iterative solution approach of reliability degree index was given synchronously. An engineering example was analyzed by the method. The result shows its absolute error is only 0.78% as compared with accurate solution.
基金Project supported by China Postdoctoral Science Foundation （20100481488）, Key Fund Project of Advanced Research of the Weapon Equipment （9140A33040512JB3401）.
基金BZ research was supported,in part,by the National Institutes of Health grant U24 AA026968the University of Massachusetts Center for Clinical and Translational Science grants UL1TR001453,TL1TR01454,and KL2TR01455.
文摘Standard deviation(SD)and standard error of the mean(SEM)have been applied widely as error bars in scientific plots.Unfortunately,there is no universally accepted principle addressing which of these 2 measures should be used.Here we seek to fill this gap by outlining the reasoning for choosing SEM over SD and hope to shed light on this unsettled disagreement among the biomedical community.The utility of SEM and SD as error bars is further discussed by examining the figures and plots published in 2 research articles on pancreatic disease.
基金The work of W.Zheng and Q.Ling was partially supported by the National Natural Science Foundation of China(No.61273112)the National Key Research and Development Project(No.2016YFC0201003).The work of H.Lin was partially supported by the National Science Foundation(Nos.NSF-CNS-1239222,NSF-CNS-1446288,NSF-EECS-1253488).
文摘This paper considers the consensus problem of a group of homogeneous agents.These agents are governed by a general linear system and can only directly measure the output,instead of the state.In order to achieve the consensus goal,each agent estimates its state through a Luenberger observer,exchanges its estimated state with neighbors,and constructs the control input with the estimated states of its own and neighbors.Due to the existence of observation and process noises,only practical consensus,instead of asymptotical consensus,can be achieved in such multi-agent systems.The performance of the achieved practical consensus can be measured by the ultimate mean square deviation of the states of agents.That performance is closely related to the observation gains of the state observers and the control gains of agents.This paper proposes a method to optimize such performance with respect to the concerned observation and control gains.That method starts with a set of feasible observation and control gains and formulates a group of linear matrix inequalities(LMIs).Solving these LMIs gives some intermediate matrix variables.By perturbing observation and control gains,and the intermediate matrix variables,the original LMIs yield another group of LMIs,which can be solved to provide a descent direction of observation and control gains.Moving along that descent direction,observation and control gains can be improved to yield better performance and work as the starting point of the next iteration.By iteratively repeating this procedure,we can hopefully improve the consensus performance of the concerned multi-agent system.Simulations are done to demonstrate the effectiveness of the proposed method.
文摘针对FasterVit网络存在的注意力机制失衡、池化策略缺陷导致部分重要特征无法保留和损失函数不能全面考虑所有类别的信息导致学习到的特征比较分散等问题,提出了一种基于CFasterVit-三并联分支融合注意力机制(triple-parallel fusion attention model,TFAM)与余弦均匀流形逼近与投影(cosineuniform manifold approximation and projection,COS-UMAP)模型的滚动轴承故障诊断方法。该模型由FasterVit-TFAM网络、COS-UMAP降维算法和激活函数类距均值标准差损失函数(class-distance mean standard deviation loss,CMSD)-Softmax组成。首先,提出了一种新的注意力机制TFAM,并与FasterVit网络结合,提升了FasterVit网络信息关注的均衡性和表征能力;其次,将基于COS-UMAP降维算法取代FasterVit网络全连接层前最后一次池化操作,有效筛选并保留多维数据中的重要特征;最后,将类距均值标准差损失函数替换Softmax激活函数中的交叉熵损失函数,更全面地学习特征并提高模型的泛化性。西安交通大学滚动轴承数据集滚动轴承故障试验结果表明,TFAM注意力机制和其他注意力机制相比诊断准确率最大提升8.0%,COS-UMAP对比其他降维算法诊断准确率最大提升15.8%,CMSD对比交叉熵损失函数诊断准确率提升0.5%,所提模型对故障样本的识别准确率达到了99.6%,相比FasterVit提升了1.4%,相较于其他网络模型最大提升7.8%;东南大学滚动轴承数据集仿真验证试验结果表明,所提模型对故障样本识别率达98.6%,相比FasterVit提升了2.2%,平均每轮训练时间缩短了16.92 s,对比其他网络模型最大提升12.2%,有效提高了滚动轴承故障诊断模型的准确率和泛化性能。
