Wave simulation was conducted for the period 1976 to 2005 in the South China Sea （SCS） using the wave model, WAVEWATCH-III. Wave characteristics and engineering environment were studied in the region. The wind input...Wave simulation was conducted for the period 1976 to 2005 in the South China Sea （SCS） using the wave model, WAVEWATCH-III. Wave characteristics and engineering environment were studied in the region. The wind input data are from the objective reanalysis wind datasets, which assimilate meteorological data from several sources. Comparisons of significant wave heights between simulation and TOPEX/Poseidon altimeter and buoy data show a good agreement in general. By statistical analysis, the wave characteristics, such as significant wave heights, dominant wave directions, and their seasonal variations, were discussed. The largest significant wave heights are found in winter and the smallest in spring. The annual mean dominant wave direction is northeast （NE） along the southwest （SW）-NE axis, east northeast in the northwest （NW） part of SCS, and north northeast in the southeast （SE） part of SCS. The joint distributions of wave heights and wave periods （directions） were studied. The results show a single peak pattern for joint significant wave heights and periods, and a double peak pattern for joint significant wave heights and mean directions. Furthermore, the main wave extreme parameters and directional extreme values, particularly for the 100-year return period, were also investigated. The main extreme values of significant wave heights are larger in the northern part of SCS than in the south- ern part, with the maximum value occurring to the southeast of Hainan Island. The direction of large directional extreme Hs values is focus in E in the northem and middle sea areas of SCS, while the direction of those is focus in N in the southeast sea areas of SCS.展开更多
为了解表面肌电信号(surface electromyography,sEMG)特征的变化规律,找出更加有效的疲劳特征参数组合,通过回归分析和皮尔逊相关系数分析的方法研究了6名受试者负重状态下,手臂表面肌电信号的时域、频域和时频域特征参数与主观疲劳感量...为了解表面肌电信号(surface electromyography,sEMG)特征的变化规律,找出更加有效的疲劳特征参数组合,通过回归分析和皮尔逊相关系数分析的方法研究了6名受试者负重状态下,手臂表面肌电信号的时域、频域和时频域特征参数与主观疲劳感量表(rating of perceived exertion,RPE)之间的关系。结果表明:随着负重时间的持续,sEMG的时域特征均方根值(root mean square,RMS)和积分肌电值(integrated electromyography,iEMG)有上升趋势,频域特征平均功率频率(mean power frequency,MPF)、中值频率(media frequency,MF)有下降趋势,而时频域特征瞬时平均频率(instantaneous mean power frequency,IMPF)、瞬时中值频率(instantaneous median frequency,IMF)出现先短暂上升然后下降趋势。对各特征参数进行非线性拟合,发现RMS和iEMG幂函数拟合优于指数函数拟合,而MPF、MF、IMPF和IMF指数函数拟合优于幂函数。对联合特征参数进行多元回归分析,发现RMS与MF组成的回归模型判定系数R2最大。可见RMS与MF相结合作为评估肌肉疲劳的联合参数更加合理有效。展开更多
基金supported by the National Natural Science Foundation of China (51279186)the Open Fund of the Shandong Province Key Laboratory of Ocean Engineering,Ocean University of China (201362045)
文摘Wave simulation was conducted for the period 1976 to 2005 in the South China Sea （SCS） using the wave model, WAVEWATCH-III. Wave characteristics and engineering environment were studied in the region. The wind input data are from the objective reanalysis wind datasets, which assimilate meteorological data from several sources. Comparisons of significant wave heights between simulation and TOPEX/Poseidon altimeter and buoy data show a good agreement in general. By statistical analysis, the wave characteristics, such as significant wave heights, dominant wave directions, and their seasonal variations, were discussed. The largest significant wave heights are found in winter and the smallest in spring. The annual mean dominant wave direction is northeast （NE） along the southwest （SW）-NE axis, east northeast in the northwest （NW） part of SCS, and north northeast in the southeast （SE） part of SCS. The joint distributions of wave heights and wave periods （directions） were studied. The results show a single peak pattern for joint significant wave heights and periods, and a double peak pattern for joint significant wave heights and mean directions. Furthermore, the main wave extreme parameters and directional extreme values, particularly for the 100-year return period, were also investigated. The main extreme values of significant wave heights are larger in the northern part of SCS than in the south- ern part, with the maximum value occurring to the southeast of Hainan Island. The direction of large directional extreme Hs values is focus in E in the northem and middle sea areas of SCS, while the direction of those is focus in N in the southeast sea areas of SCS.
文摘为了解表面肌电信号(surface electromyography,sEMG)特征的变化规律,找出更加有效的疲劳特征参数组合,通过回归分析和皮尔逊相关系数分析的方法研究了6名受试者负重状态下,手臂表面肌电信号的时域、频域和时频域特征参数与主观疲劳感量表(rating of perceived exertion,RPE)之间的关系。结果表明:随着负重时间的持续,sEMG的时域特征均方根值(root mean square,RMS)和积分肌电值(integrated electromyography,iEMG)有上升趋势,频域特征平均功率频率(mean power frequency,MPF)、中值频率(media frequency,MF)有下降趋势,而时频域特征瞬时平均频率(instantaneous mean power frequency,IMPF)、瞬时中值频率(instantaneous median frequency,IMF)出现先短暂上升然后下降趋势。对各特征参数进行非线性拟合,发现RMS和iEMG幂函数拟合优于指数函数拟合,而MPF、MF、IMPF和IMF指数函数拟合优于幂函数。对联合特征参数进行多元回归分析,发现RMS与MF组成的回归模型判定系数R2最大。可见RMS与MF相结合作为评估肌肉疲劳的联合参数更加合理有效。
