A major activity in creating a test-analysis model (TAM) is to select the accelerometer (ASET) DOF. This is an extremely important process since a good set of master DOF will result in a good TAM and will optimize the amount of data obtained from a modal survey. Conversely, a poor DOF set will make it difficult to create a satisfactory TAM, devalue the data obtained from the modal survey, and make posttest correlation much more difficult. Thus, a good pretest analysis and TAM is a key step for a successful modal survey and posttest correlation.
Selecting the master DOF is not an exact science. There are several automated methods which can assist an engineer in selecting the more significant DOF. However, these methods have various strengths and weaknesses and do not replace the insight and experience of an engineer.
The following sections describe automated methods for assisting in the selection of ASET DOF, as implemented in Nastran. The first method is based on grid point kinetic energy. This provides a good starting point for finding important DOF. The second method is based on residual kinetic energy. This requires that the user start with an ASET, and helps identify DOF to add that will improve the accuracy of the TAM. The final method presented here is Iterative Guyan reduction. This is an automated method for iteratively selecting those DOF with the highest mass/stiffness ratio. It starts from a large candidate set of DOF (1,000 – 5,000) and reduces the model to a user-defined number of DOF.
A number of other algorithms exist for selecting ASET DOF, but these are not easily implemented in Nastran. An overview is provided in [11], with a related algorithm for selecting exciter locations presented in [12]. The Genetic Algorithm for accelerometer placement, which is a Matlab-based algorithm packaged with IMAT+TestKit, will be briefly discussed.
The recommended approach for selecting master DOF is to start with a combination of engineering judgment and kinetic energy sorting to select a candidate set. The candidate set will typically have between 1,000 and 5,000 DOF, will consist of only DOF that are accessible for instrumentation, and ideally will generate an “excellent” TAM. After generating a candidate set of master DOF, the best approach for selecting the final DOF will most likely be the Iterative Guyan Reduction (IGR). An alternative is to start with a small set of DOF and add to this set, from the candidate set, using the Residual Kinetic Energy (RKE) method. Also note that it is possible, and advisable, to generate TAMs using a number of different methods and then select the best among these.
Each of the automated methods can assist the engineer in selecting the important DOF to retain in the TAM. However, the engineer must provide the engineering judgment which determines the “best” set of accelerometer locations to meet the pretest, test, and posttest objectives and requirements.