基于智能手机的行人荷载测试研究

Measurements of pedestrian's loads using smart phones

现代智能手机测试技术的飞速发展及其高普及性,为突破行人荷载测试的技术瓶颈提供了可能。研究首先利用小型振动台,通过对比不同型号的智能手机对正弦波、扫频波及地震动信号的测量精度,筛选出适合行人荷载测试的手机软硬件系统。随后利用三维动作捕捉技术,研究测试者进行步行、跳跃和屈伸运动时,手机的携带方式、位置以及自身转动等对加速度测试精度的影响,采用该携带方式和坐标转换算法,手机所获得人体运动加速度与试验对照值非常接近,主频特征则完全一致。进而,将手机记录的加速度与人体运动的动力学模型相结合,可获得对应的人致荷载时程,与测力板的记录结果对比表明,采用单刚体模型即可获得精度良好的跳跃和屈伸荷载时程,而步行荷载的精度一般。

The application of smartphones in human-induced loads measurements was explored. Shaking table tests were then conducted on selected smartphones combined with an appropriate data acquisition software to measure different types of waves,including sinusoidal waves of various frequencies,sinusoidal sweep waves and different earthquake waves.A comparison between the smartphones＇ measurements and real inputs shows that the smartphones used in the study give reliable measurements for harmonic waves in both time and frequency domains. For complex waves like earthquakes,however,the smartphones＇ measurements should be used with caution. Then,the motion capture technology was employed to explore two key technical issues for the application of smartphones for human-induced loads measurements. One is the carrying way for the smartphone and the other is the coordinate transformation of raw data. Experimental results on individual＇s jumping,walking and bouncing activities demonstrate that the carrying way and coordinate transformation have significant effects on the measurement accuracy of smartphones. When the phones are securely fastened and the original data are corrected to a right axis,the smartphones＇ measuring data agree well with the references. Encouraged by the above experimental validation results,the smartphones were attached to a moving person to measure the acceleration near the center-of-mass of his/her body. The human-induced loads were then reconstructed by the acceleration measurements in conjunction with a biomechanical model. Satisfactory agreements between the reconstructed forces and those measured by a force plate were observed for jumping and bouncing loads,clearly demonstrating the capability of the smartphones for human-induced loads measurements.