Replicating Aerodynamic Excitation in the Laboratory

Abstract

Many structures experience random vibration caused by the rapid flow of air over the external surface of the structure. One example of this “aerodynamic excitation” occurs when missiles fly through the atmosphere en-route to target in powered flight, or slung to the undercarriage of an aircraft. In most cases, it is necessary to carry out laboratory testing in order to qualify the design of the structure and to assess the pedigree of the manufacturing and assembly process. The laboratory test should replicate, as closely as possible, the damage potential of the in-flight environment. The traditional method of replicating the aerodynamic induced vibration in the laboratory is to rigidly attach the structure to a large electrodynamic shaker and to subject the structure to random vibration. This testing methodology is inadequate and non-representative for two main reasons: (1) the excitation mechanisms are very different, i.e. through a distinct region when attached to a shaker compared to distributed excitation over the entire outer surface in-flight, (2) The boundary conditions are very dissimilar, i.e. attachment to a very high mechanical impedance shaker compared to “free” flight. There is much evidence to show that this testing methodology often leads to overly severe tests. Furthermore, the test program can be costly and time-consuming as tests are often carried out sequentially in three orthogonal axes. In addition, tests have to be repeated with different response control accelerometers as it is impossible to maintain in-flight responses all over the structure simultaneously due to the two reasons given previously. This paper details research carried out to replace the traditional rigid shaker approach to one with the structure “freely” supported and excited at multiple locations simultaneously using Multi Input Multi Output (MIMO) vibration control. The research focusses on analytical models in Matlab and Ansys to carry out “virtual tests” in order to demonstrate issues with the current testing methodology and to highlight the benefits of a new approach. Results from the analytical models show significant improvements in degree-of-replication and would result in faster and more cost effective laboratory testing.