一种水电厂房振动模态参数识别方法

水电厂房的振动是机械力、电磁力、水力脉动共同作用的结果,其动荷载很难测得,结构模态参数识别的难度不言自明。为解决以上困难,提高厂房结构振动模态参数识别的精度,在厂房结构各种荷载未知的情况下,将突然停机工况下动荷载释放后的振动信号,利用随机减量法提取自由衰减信号成分,以基于ARMA模型参数识别法实现了对某大型水电站厂房低阶模态参数的识别。识别结果表明,随机减量法和ARMA联合分析方法是解决大型复杂厂房结构动态参数识别的有效方法,识别结果可用于结构物的健康监测和振动控制中,同时该方法在大型水电站厂房振动模态参数的在线识别领域中具有广阔的工程应用前景。

A Method Based on ARMA Model for Modal Parameter Identification of A Power House

Mechanical force,magnetic force and water current pulse have effects on vibration of a power house,it is very difficult to identify its modal parameters due to the difficulty of dynamic load measurement.In order to identify modal parameters and improve identification precision,the components of free decay vibration of a power house are extracted from its vibration signals after its dynamic loads are suddenly released using the random decrement method.Modal parameters of the first several modes of the power house are identified with the ARMA model method.The identification results are compared with those of the modal analysis calculation.It shows that the method combing the random decrement method with the ARMA model method is an effective method for performing dynamic parameters identification of large power house structures,and the identification results can be used for their health monitoring and vibration control.The proposed method may be potential for online identification of modal parameters of large power house structures.