Modal macro-strain identification from operational macro-strain shape under changing loading conditions

To develop modal macro-strain （ MMS ） identification techniques and improve their applicability in a continuous health monitoring system for civil infrastructures, the concept of operational macro-strain shape （OMSS） and the corresponding identification method are proposed under unknown ever-changing loading conditions, and the MMS is then obtained. The core of the proposed technique is mainly based on the specific property that the macro-strain transmissibility tends to be independent of external excitations at the poles of the system and converges to a unique value. The proposed method is verified using the experimental data from a three-span continuous beam excited by an impact hammer at different locations. The identified results are also compared with the commonly used methods, such as the peak- picking （PP） method, the stochastic subspace identification （SSI） method, and numerical results, in the case of unknown input forces. Results show that the proposed technique has unique merits in accuracy and robustness due to its combining multiple tests under changing loading conditions, which also reveal the promising application of the distributed strain sensing system in identifying MMS of operational structures, as well as in the structural health monitoring （SHM） field.

一种基于V模型下针对三合一电驱总成的NVH优化型研发方案

本文针对新能源车用三合一电驱总成NVH系统研发,提出了一种基于V模式的优化型研发方案。通过建模与仿真不仅复现了电磁力和齿轮啮合刚度波动从激励源到传递路径(三合一电驱总成的结构)再到振动、噪声响应上的表现,而且追溯到了非声源的控制器的平板金属部件是噪声放大的主要原因。针对该现象,通过拓扑优化提升固有频率300~500 Hz,使平板件的噪声由结构噪声传递为主向空气噪声传递为主转变,再加上声学包裹等措施,综合性的降低噪声10~20 dB (A)。建模与仿真、测试和优化通过这种基于V模式的优化方案有机的结合到一起,节省了在子系统所占用的开发时间和开发成本。