In this paper, the ensemble empirical mode decomposition （EEMD） is applied to analyse accelerometer signals collected during normal human walking. First, the self-adaptive feature of EEMD is utilised to decompose th...In this paper, the ensemble empirical mode decomposition （EEMD） is applied to analyse accelerometer signals collected during normal human walking. First, the self-adaptive feature of EEMD is utilised to decompose the ac- celerometer signals, thus sifting out several intrinsic mode functions （IMFs） at disparate scales. Then, gait series can be extracted through peak detection from the eigen IMF that best represents gait rhythmicity. Compared with the method based on the empirical mode decomposition （EMD）, the EEMD-based method has the following advantages： it remarkably improves the detection rate of peak values hidden in the original accelerometer signal, even when the signal is severely contaminated by the intermittent noises; this method effectively prevents the phenomenon of mode mixing found in the process of EMD. And a reasonable selection of parameters for the stop-filtering criteria can improve the calculation speed of the EEMD-based method. Meanwhile, the endpoint effect can be suppressed by using the auto regressive and moving average model to extend a short-time series in dual directions. The results suggest that EEMD is a powerful tool for extraction of gait rhythmicity and it also provides valuable clues for extracting eigen rhythm of other physiological signals.展开更多
A series elastic actuator(SEA) is a powerful device in the area of human-machine integration, but it still suffers from difficult position control issues. Therefore, in this paper,an efficient approach is proposed to ...A series elastic actuator(SEA) is a powerful device in the area of human-machine integration, but it still suffers from difficult position control issues. Therefore, in this paper,an efficient approach is proposed to solve this problem. The approach design is divided into two steps: feedback linearization(FL) and global sliding mode(GSM) controller design. The bounded analysis is presented and global asymptotic convergence is analytically proven. Simulation and experiment results illustrate the effectiveness of the proposed scheme.展开更多
In this study, a reliability index vector formula is proposed for series system with two failure modes in term of the concept of reliability index vector and equivalent failure modes. Firstly, the reliability index ve...In this study, a reliability index vector formula is proposed for series system with two failure modes in term of the concept of reliability index vector and equivalent failure modes. Firstly, the reliability index vector is introduced to determine the correlation coefficient between two failure modes, and then, the reliability index vector of a series system can be obtained. Several numerical cases and an analysis on offshore platform are performed, and the results show that this scheme provided here has better computational accuracy, and its calculation process is simpler for the series systems reliability calculations compared with the other methods. Also this scheme is more convenient for the engineering applications.展开更多
A complex system contains generally many elements that are networked by their couplings.The time series of output records of the system's dynamical process is subsequently a cooperative result of the couplings.Dis...A complex system contains generally many elements that are networked by their couplings.The time series of output records of the system's dynamical process is subsequently a cooperative result of the couplings.Discovering the coupling structure stored in the time series is an essential task in time series analysis.However,in the currently used methods for time series analysis the structural information is merged completely by the procedure of statistical average.We propose a concept called mode network to preserve the structural information.Firstly,a time series is decomposed into intrinsic mode functions and residue by means of the empirical mode decomposition solution.The mode functions are employed to represent the contributions from different elements of the system.Each mode function is regarded as a mono-variate time series.All the mode functions form a multivariate time series.Secondly,the co-occurrences between all the mode functions are then used to construct a threshold network(mode network)to display the coupling structure.This method is illustrated by investigating gait time series.It is found that a walk trial can be separated into three stages.In the beginning stage,the residue component dominates the series,which is replaced by the mode function numbered M14 with peaks covering^680 strides(~12 min)in the second stage.In the final stage more and more mode functions join into the backbone.The changes of coupling structure are mainly induced by the co-occurrent strengths of the mode functions numbered as M11,M12,M13,and M14,with peaks covering 200-700 strides.Hence,the mode network can display the rich and dynamical patterns of the coupling structure.This approach can be extended to investigate other complex systems such as the oil price and the stock market price series.展开更多
The ZJC 480 series helium-neon laser blood vessel internal exposure apparatus was developed by the Changchun Zhongji Photoelectric Co, Ltd. It is used in the treatment of ischemic anoxic cardiovascular and cerebrovasc...The ZJC 480 series helium-neon laser blood vessel internal exposure apparatus was developed by the Changchun Zhongji Photoelectric Co, Ltd. It is used in the treatment of ischemic anoxic cardiovascular and cerebrovascular diseases, nervous system disorders, and respiratory and urinary system disorders. In 1995, the ZJC series was appraised as the "95 State-Grade Key New Product" by the State Science and Tech-展开更多
Power series is extensively used for engineering studies. To raise the synthesis efficiency and computation accuracy of vibration mode synthesis (MS), the choosing of power series as the component mode-function is stu...Power series is extensively used for engineering studies. To raise the synthesis efficiency and computation accuracy of vibration mode synthesis (MS), the choosing of power series as the component mode-function is studied in this paper, and emphasis is laid on its effect upon the system computation accuracy when using the mode synthesis method for a high speed compound rotating elastic system.展开更多
为提高采煤工作面涌水量预测准确度,收集大量工作面涌水量观测数据进行整理、统计、分析,将涌水量稳定性、周期性和季节性特征考虑在内,提出1种基于数据驱动的完全自适应模态分解算法(CEEMDAN)和改进的混合时间序列模型工作面涌水量预...为提高采煤工作面涌水量预测准确度,收集大量工作面涌水量观测数据进行整理、统计、分析,将涌水量稳定性、周期性和季节性特征考虑在内,提出1种基于数据驱动的完全自适应模态分解算法(CEEMDAN)和改进的混合时间序列模型工作面涌水量预测方法。该方法利用CEEMDAN处理涌水量数据,构建麻雀搜索算法(SSA)优化的长短期记忆网络(LSTM)和自回归移动平均模型(ARIMA)并行级联而成的混合时间序列模型对工作面涌水量进行预测。研究结果表明:该模型预测结果与真实数据相差更小,平均绝对误差为6.36 m 3/h,均方根误差为10.6 m 3/h,模型拟合系数为0.95,更适用于工作面涌水量预测。研究结果可为矿井工作面涌水量预测及防控提供参考。展开更多
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 60501003 and 60701002)
文摘In this paper, the ensemble empirical mode decomposition （EEMD） is applied to analyse accelerometer signals collected during normal human walking. First, the self-adaptive feature of EEMD is utilised to decompose the ac- celerometer signals, thus sifting out several intrinsic mode functions （IMFs） at disparate scales. Then, gait series can be extracted through peak detection from the eigen IMF that best represents gait rhythmicity. Compared with the method based on the empirical mode decomposition （EMD）, the EEMD-based method has the following advantages： it remarkably improves the detection rate of peak values hidden in the original accelerometer signal, even when the signal is severely contaminated by the intermittent noises; this method effectively prevents the phenomenon of mode mixing found in the process of EMD. And a reasonable selection of parameters for the stop-filtering criteria can improve the calculation speed of the EEMD-based method. Meanwhile, the endpoint effect can be suppressed by using the auto regressive and moving average model to extend a short-time series in dual directions. The results suggest that EEMD is a powerful tool for extraction of gait rhythmicity and it also provides valuable clues for extracting eigen rhythm of other physiological signals.
基金supported in part by the National Natural Science Foundation of China(61573198)
文摘A series elastic actuator(SEA) is a powerful device in the area of human-machine integration, but it still suffers from difficult position control issues. Therefore, in this paper,an efficient approach is proposed to solve this problem. The approach design is divided into two steps: feedback linearization(FL) and global sliding mode(GSM) controller design. The bounded analysis is presented and global asymptotic convergence is analytically proven. Simulation and experiment results illustrate the effectiveness of the proposed scheme.
文摘In this study, a reliability index vector formula is proposed for series system with two failure modes in term of the concept of reliability index vector and equivalent failure modes. Firstly, the reliability index vector is introduced to determine the correlation coefficient between two failure modes, and then, the reliability index vector of a series system can be obtained. Several numerical cases and an analysis on offshore platform are performed, and the results show that this scheme provided here has better computational accuracy, and its calculation process is simpler for the series systems reliability calculations compared with the other methods. Also this scheme is more convenient for the engineering applications.
基金the National Natural Science Foundation of China(Grant Nos.11805128,11875042,11505114,and 10975099)the Program for Professor of Special Appointment(Orientational Scholar)at Shanghai Institutions of Higher Learning,China(Grant Nos.D-USST02 and QD2015016)the Shanghai Project for Construction of Top Disciplines,China(Grant No.USST-SYS-01).
文摘A complex system contains generally many elements that are networked by their couplings.The time series of output records of the system's dynamical process is subsequently a cooperative result of the couplings.Discovering the coupling structure stored in the time series is an essential task in time series analysis.However,in the currently used methods for time series analysis the structural information is merged completely by the procedure of statistical average.We propose a concept called mode network to preserve the structural information.Firstly,a time series is decomposed into intrinsic mode functions and residue by means of the empirical mode decomposition solution.The mode functions are employed to represent the contributions from different elements of the system.Each mode function is regarded as a mono-variate time series.All the mode functions form a multivariate time series.Secondly,the co-occurrences between all the mode functions are then used to construct a threshold network(mode network)to display the coupling structure.This method is illustrated by investigating gait time series.It is found that a walk trial can be separated into three stages.In the beginning stage,the residue component dominates the series,which is replaced by the mode function numbered M14 with peaks covering^680 strides(~12 min)in the second stage.In the final stage more and more mode functions join into the backbone.The changes of coupling structure are mainly induced by the co-occurrent strengths of the mode functions numbered as M11,M12,M13,and M14,with peaks covering 200-700 strides.Hence,the mode network can display the rich and dynamical patterns of the coupling structure.This approach can be extended to investigate other complex systems such as the oil price and the stock market price series.
文摘The ZJC 480 series helium-neon laser blood vessel internal exposure apparatus was developed by the Changchun Zhongji Photoelectric Co, Ltd. It is used in the treatment of ischemic anoxic cardiovascular and cerebrovascular diseases, nervous system disorders, and respiratory and urinary system disorders. In 1995, the ZJC series was appraised as the "95 State-Grade Key New Product" by the State Science and Tech-
文摘Power series is extensively used for engineering studies. To raise the synthesis efficiency and computation accuracy of vibration mode synthesis (MS), the choosing of power series as the component mode-function is studied in this paper, and emphasis is laid on its effect upon the system computation accuracy when using the mode synthesis method for a high speed compound rotating elastic system.
文摘为提高采煤工作面涌水量预测准确度,收集大量工作面涌水量观测数据进行整理、统计、分析,将涌水量稳定性、周期性和季节性特征考虑在内,提出1种基于数据驱动的完全自适应模态分解算法(CEEMDAN)和改进的混合时间序列模型工作面涌水量预测方法。该方法利用CEEMDAN处理涌水量数据,构建麻雀搜索算法(SSA)优化的长短期记忆网络(LSTM)和自回归移动平均模型(ARIMA)并行级联而成的混合时间序列模型对工作面涌水量进行预测。研究结果表明:该模型预测结果与真实数据相差更小,平均绝对误差为6.36 m 3/h,均方根误差为10.6 m 3/h,模型拟合系数为0.95,更适用于工作面涌水量预测。研究结果可为矿井工作面涌水量预测及防控提供参考。
