基于Kalman滤波的有限测点桁架结构疲劳损伤监测
Fatigue Monitoring of Limited Measured Truss Structure Based on Kalman Filtering

发展一种基于Kalman滤波的应变响应估计方法，采用自行研发的疲劳应变数字化线传感器，对有限测点桁架结构进行监测，实现桁架结构未测杆件的疲劳损伤评估。通过引入虚拟系统噪声对系统输入进行处理，在未知激励条件下对有限测点之外的拓展点应变响应进行估计；用平面主桁架数值模型验证了算法的可行性；设计平面钢桁架模型，进行桁架结构高周疲劳试验。试验结果表明，基于疲劳传感器的实测应变响应，该算法有效估计了拓展点应变响应，并与拓展点实测数据吻合良好；联合有限测点和估计点的应变响应数据，对该桁架结构实施了疲劳损伤评估。
Fatigue monitoring of the truss structure has been limited by the lack of amount of long-service sensors. This paper presents a more reflective strain-time histories estimation methodology based on Kalman filtering, which can be applied on the fatigue damage assessment of the unmeasured elements of the truss structure. Long-term fatigue information can be captured in real time through a digital wireless fatigue strain sensor. Non-white process noise is proccessed according to the virtual noise. The algorithm of the strain-time histories estimation has been verified by a numerical two-dimensional truss model. On this basis, the same experimental truss structure has been designed to demonstrate the methodology under a high-cycle fatigue testing. The results show a great deal of consistency between the estimated and measured strain values. Both the estimated and measured strain time histories are used for the fatigue damage assessment at the last section.