Operational Modal Analysis of Civil Engineering Structures

Operational Modal Analysis is the testing procedure yielding experimental estimates of the modal parameters from measurements of the structural response only. This book is intended as a guide through its most relevant theoretical and practical aspects, providing all the necessary information to develop an integrated system for output-only modal testing. The illustration of relevant theoretical aspects provides a general framework to acquire the ability and understanding of the techniques. The large attention devoted to the implementation details provides a valuable stimulus in approaching the study. The applicative perspective makes learning easy and the book suitable for a wide range of readers. A number of explanatory examples will help the reader in better understanding the concepts and potential of this testing procedure. This chapter provides basic notions to approach the topics analyzed in the rest of the book without ambiguities. Moreover, it illustrates the general structure and organization of the book. Finally, it gives an overview of the platform adopted for the implementation of systems and software described in the next chapters of this book.

This chapter starts from basic notions about complex numbers and the Fourier transform, due to their critical role in signal processing. Then, it summarizes the main definitions and concepts about random processes and random data. It introduces the main characteristics and properties of data and processes invoked in the discussion about the modal identification methods (Chap. 4). The mathematical and signal processing tools for the analysis of data and implementation of modal identification procedures are introduced according to the technical and practical approach followed in the book. As a consequence, applicative examples and an intuitive approach are preferred over heavy mathematical proofs in order to facilitate the reader in learning the most relevant concepts and gaining confidence in mathematical and signal processing tools. In particular, the chapter provides an overview about the descriptive properties of random processes (probability density function, correlation, spectrum) and relevant linear algebra tools. Sample applications are proposed to familiarize with the discussed topics. Relevant references are listed at the end of the chapter for the reader interested in a more detailed analysis of the herein outlined concepts.

This chapter provides essential concepts for a proper setup of the measurement hardware for OMA purposes. The main characteristics of different measurement schemes are summarized. Parameters characterizing the performance of sensors and data acquisition systems are illustrated, providing guidelines for their choice. Criteria for test planning and sensor installation are also discussed. Then, attention is focused on the main aspects concerning data acquisition and storage: setting of the sampling frequency, data streaming on file, and storage in MySQL relational databases. Tools for data validation and pretreatment are finally discussed. The applications proposed at the end of the chapter will guide the reader to the implementation of a customized measurement system based on programmable hardware.

This chapter is focused on the methods for modal parameter estimation from previously acquired and pretreated time histories of the structural response to ambient vibrations. The fundamental assumptions of OMA methods and the basic concepts of structural dynamics models in time and frequency domain are illustrated, pointing out the common mathematical background behind different and apparently unrelated procedures. Then, criteria for the classification of OMA methods are summarized and fundamental theoretical aspects of well-established and popular OMA techniques are illustrated, providing relevant details for their software implementation. Finally, additional aspects concerning post-processing of modal parameter estimates, validation of layout and modal identification results, and correlation with numerical models are discussed. The ultimate objective of this chapter is to provide the reader all relevant information for implementation and practical application of a number of OMA methods and post-processing tools for validation and correlation. In this sense the implementation details and the basic software provided with the book are intended to fit the needs of both the modal analysts on one hand and undergraduate/graduate students, researchers, and developers on the other. The latter, in fact, are usually interested in writing their own code for further developments or business opportunities, and the accompanying software serves as a reference. On the other hand, modal analysts can find here the tools and the fundamental information to promptly start the modal tests and properly interpret the results. Using the basic software accompanying the book they can take confidence with different OMA procedures and choose their favorite ones. Thus, the chapter can be also intended as a guide supporting the choice among the different commercial software packages available on the market and relying on different OMA methods.

The extensive discussion about OMA algorithms and tools for validation and postprocessing of modal identification results represents the background of the present chapter that is focused on a number of explanatory applications, including some special issues. Most of the reported applications refer to real experimental tests, which have been selected as representative of frequently tackled issues in modal testing and data processing. In particular, they illustrate a possible approach to assess the capability of the measurement chain of fitting the requirements of a specific application, methods for accurate estimation of damping ratios, and methods for identification of spurious harmonics. Additional examples concern the possible uses of the identified modal parameters, such as numerical–experimental correlation and tuning of a numerical model, development of empirical correlations for the estimation of the fundamental natural frequencies of selected typologies of structures, the estimation of modal masses by mass change methods. As a result, the present chapter provides a definite overview of opportunities and limitations of OMA and a guide for applications.

Vibration-based monitoring of structures is one of the most popular applications of OMA. In the past a relevant limitation to the extensive application of modal-based damage detection techniques and vibration-based monitoring was the lack of fully automated procedures for the estimation of the dynamic parameters of the monitored structure in its operational conditions. Only in the last few years the large research efforts on this topic have filled the gap by the development of a number of automated OMA procedures. This chapter provides an overview of the latest developments in this field. It represents a specific viewpoint about the matter, since a wide consensus in the definition of the “best methods” for automated output-only modal identification has not been reached, yet. The main development issues emerging from a literature review about automated OMA procedures are outlined, and three effective algorithms are described in detail. The discussion about automated OMA methods is complemented by the illustration of some applications. They remark the potential of automated OMA in solving a number of monitoring applications but also the drawbacks related to the influence of environmental and operational factors on the modal parameter estimates.