基于振动信号降噪的钢板件损伤定位

为了实现汽车船舶等行业中钢板件的结构健康监测,针对冲击、碰撞损伤发生时的振动信号,提出了一种结合小波包阈值降噪(WPT)和集合经验模态分解(EEMD)降噪的方法来提高损伤源的定位精度。首先,设计了动态环境下钢板件的冲击损伤试验系统并进行实验方案设计,采集了损伤时刻数据;其次,通过对损伤信号进行WPT-EEMD降噪有效提高信噪比,并利用阈值检测获得信号到达各传感器的时间;最后,基于延时叠加算法,完成了钢板件中损伤区域的定位成像。实验结果表明,该方法可在动态环境下有效定位出钢板件上冲击损伤发生的位置,为解决动态无损监测问题提供了思路。

Damage localization of steel plate based on vibration signal denoising

In order to realize the structural health monitoring of steel plate parts in automobile and ship industries, a method combining wavelet packet threshold denoising (WPT) and ensemble empirical mode decomposition (EEMD) denoising method was proposed to improve the locating accuracy of damage sources for the vibration signals during impact and collision damage. Firstly, the impact damage test system of steel plate under dynamic environment was designed and the experimental scheme was designed. The damage time data was collected. Secondly, the damage signal was denoising by WPT-EEMD and the signal to noise ratio was improved effectively. The time of the signal arriving at each sensor was obtained by threshold detection. Finally, based on the time-delay superposition algorithm, the localization imaging of the damage area in the steel plate was completed. The experimental results show that the method can effectively locate the position of impact damage on the steel plate under dynamic environment, which provides an idea for solving the problem of dynamic nondestructive monitoring.