Cancelation of transducer effects from frequency response functions: Experimental case study on the steel plate

Modal analysis is a progressive science in the experimental evaluation of dynamic properties of the structures. Mechanical devices such as accelerometers are one of the sources of lack of quality in measuring modal testing parameters. In this article, elimination of the accelerometer’s mass effect of the frequency response of the structure is studied. So, a strategy is used for eliminating the mass effect using sensitivity analysis. In this method, the amount of mass change and the place to measure the structure’s response with least error in frequency correction is chosen. Experimental modal testing is carried out on a steel plate, and the effect of accelerometer’s mass is omitted using this strategy. Finally, a good agreement is achieved between numerical and experimental results

Identification of modal parameters for complex structures by experimental modal analysis approach

In this research, we have proposed a methodology for experimental identification of modal parameters based on measurement of the frequency responses of structures with complex geometries and performed an overall investigation of structural behavior on a funnel-shaped inlet of magnetic resonance tomograph. Several identification methods are implemented and compared: complex exponential, least-squares complex exponential, and polyreference least-squares complex exponential. We have implemented the modal parameter identification methodology within our own graphical user interface supported by MATLAB to create an independent tool for modal analysis. The estimation methods are compared and the comparison results are summarized showing based on tabular representation and stabilization diagrams significant advantage of the proposed methodology for determining eigenfrequencies, damping coefficients, mode shapes, and residues for complex structures investigated in broad band of frequencies. Runtime for the execution of algorithms vary depending on the applied method, assumed order of the model used for estimation, and the number of measurements, that is, inputs and outputs