TABLE OF CONTENTS Acquisition of data that are used in the formulation of a modal model involves many important technical concerns. The primary concern is the digital signal processing, or the converting of analog signals into a corresponding sequence of digital values that accurately describe the time-varying characteristics of the inputs to and responses from a system. Once the data are available in digital form, the most common approach is to transform the data from the time domain to the frequency domain by use of a discrete Fourier transform algorithm. Since this algorithm involves discrete data over a limited time period, there are large potential problems with this approach that must be well understood. (Data acquisition and analysis are discussed in detail in Chap. 27.)
In order to determine modal parameters, the measured input (excitation) and response data must be processed and put into a form that is compatible with the test and modal parameter estimation methods. As a result, digital signal processing of the data is a very important step in structural testing. This is one of the technology areas where a clear understanding of the time-frequency-Laplace domain relationships is important. The conversion of the data from the time domain into the frequency and Laplace domains is important both in the measurement process and subsequently in the parameter estimation process.
Digital signal processing of the measured input and response data is used for the following reasons:
Condensation. In general, the amount of measured data tremendously...
