A Comparison of Accelerometer Selection Methods for Modal Pretest Analysis

Abstract

Prior to performing a modal survey test, pretest analysis is typically performed to determine the optimal number and location of response measurements (usually acceleration) and reference measurements (dynamic loads). This pretest analysis begins with the preparation of an accurate finite element model (FEM). Typically, the test measurement set cannot practically contain more than several hundred degrees of freedom (DOF) (although some recent tests have used as many as a thousand), so any method of pretest analysis should extract the best possible candidate locations from the initial FEM. Automated sensor selection algorithms first up-select to a candidate set of potential degrees of freedom that are several times larger than the final set of sensors. The methods then down-select from this candidate set to an optimal set of sensors. This paper presents the methods used to arrive at an initial candidate set for measurements, from the perspective of a practicing test engineer. Specifically, the iterative residual kinetic energy (IRKE) method is compared to manual DOF selection, noting the advantages and drawbacks of each. While some test articles may lend themselves to simple manual DOF selection (i.e., symmetric structures such as aircraft), others are far more asymmetric and may require more rigorous analytic methods to complement or entirely replace any manual selection of a candidate set. This paper utilizes an "iron bird" demonstration test article as a tool to compare and contrast these candidate DOF selection methods.