Review on the new development of vibration-based damage identification for civil engineering structures: 2010-2019

Comparative study of modal analysis techniques for bridge dynamic characteristics

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A statistical method with combined uncertain frequency and mode shape data for structural damage identification is proposed. By comparing the measured vibration data before damage or analytical finite element model of the intact structure with those measured after damage, the finite element model is updated so that its vibration characteristic changes are equal to the changes in the measured data as closely as possible. The effects of uncertainties in both the measured vibration data and finite element model are considered as random variables in model updating. The statistical variations of the updated finite element model are derived with perturbation method and Monte Carlo technique. The probabilities of damage existence in the structural members are then defined. The proposed method is applied to a laboratory tested steel cantilever beam and frame structure. The results show that all the damages are identified correctly with high probabilities of damage existence. Discussions are also made on the applicability of the method when no measurement data of intact structure are available. Copyright © 2002 John Wiley & Sons, Ltd.

Damage identification of structures with uncertain frequency and mode shape data

In this paper, we present a novel acoustic touch sensing technique called Touch & Activate. It recognizes a rich context of touches including grasp on existing objects by attaching only a vibration speaker and a piezo-electric microphone paired as a sensor. It provides easy hardware configuration for prototyping interactive objects that have touch input capability. We conducted a controlled experiment to measure the accuracy and trade-off between the accuracy and number of training rounds for our technique. From its results, per-user recognition accuracies with five touch gestures for a plastic toy as a simple example and six hand postures for the posture recognition as a complex example were 99.6% and 86.3%, respectively. Walk up user recognition accuracies for the two applications were 97.8% and 71.2%, respectively. Since the results of our experiment showed a promising accuracy for the recognition of touch gestures and hand postures, Touch & Activate should be feasible for prototype interactive objects that have touch input capability.

Touch & activate: adding interactivity to existing objects using active acoustic sensing

Experimental modal analysis has grown steadily in pop ularity since the advent of the digital FFT spectrum analyzer in the early 1970’s. Today, impact testing (or bump testing) has become widespread as a fast and economical means of finding the modes of vibration of a machine or structure. In this paper, we review all of the main topics associated with experimental modal analysis (or modal testing), including making FRF measurements with a FFT analyzer, modal excitation techniques, and modal parameter estimation from a set of FRFs (curve fitting).

EXPERIMENTAL MODAL ANALYSIS By

Mode shapes and operating deflection shapes (ODS’s) are related to one another. In fact, ODS’s are always measured in order to obtain mode shapes. Yet, they are quite different from one another in a number of ways. In this paper, we will discuss ODS measurements, and their relationship to experimental modal parameters.

INTRODUCTION TO OPERATING DEFLECTION SHAPES By

Modal testing, also referred to as Experimental Modal Analysis (EMA), underwent a revolutionary change during the early 1970s with the implementation of the Fast Fourier Transform (FFT) in computer-based FFT analyzers. Prior to that time, model testing had been done primarily with analog equipment. FFT-based EMA on the other hand, required the development of new digital signal processing methods. Modal parameter estimation is a key step in FFT-based EMA. This step, also called curve fitting, has received more attention than any other during the past 30 years. Numerous methods have been developed and the technical literature contains hundreds of papers documenting many different approaches. Modal analysis is used to characterize resonant vibration in machinery and structures. A mode of vibration is defined by three parameters; modal frequency, modal damping and mode shape. Modal parameter estimation is the process of determining these parameters from experimental data. Furthermore, a set of modal parameters can completely characterize the dynamic properties of a structure. This set of parameters is also called a modal model for the structure. Two recent SV one that relies on carefully controlled multishaker excitation,3 and the other that strongly suggests artificial excitation is not required at all.4 Regardless of whether artificial excitation is used or not, both approaches rely heavily on modal parameter estimation. Both articles devote the majority of their discussion to this subject.

Modal Parameter Estimation from Operating Data

In this paper, a new methodology is presented for post-processing non-stationary operating data as a prerequisite for displaying operating deflection shapes on a 3D spatial model of the test machine or structure. The traditional transmissibility measurement, which is a measure of each response normalized by a reference response, is discussed. Then, two new post-processing methods associated with two new types of measurements (the ODS FRF and the ODS Order Track) are introduced, and their use with data typical of realistic testing situations is illustrated.

Measuring operating deflection shapes under non-stationary conditions

In order to identify and display the operating deflection shapes or operating mode shapes of a machine or structure, data must be acquired and processed so that all shape DOFs have the correct magnitudes and phases relative to one another. If the data is simultaneously acquired the correct magnitudes and phases are guaranteed. However, in the majority of testing situations, data is acquired in multiple measurement sets, and only the data in each measurement set is simultaneously acquired. When using multiple measurement sets, the data must be processed to correct the magnitudes and phases between sets. In this paper several processing methods involving the Transmissibility, Auto spectrum, and Cross spectrum are presented for calculating the response spectra required for displaying ODS’s. The mathematics behind the processing methods is shown, and the sensitivity to noise and structural changes of the methods is also compared. Various ways of scaling data from multiple measurement sets is also discussed. In addition, it is shown how operating mode shapes are obtained by curve fitting a set of response spectrum data. Results from the various spectrum estimates are compared using data from several bridge tests. MEASUREMENTS ODS’s are displayed from response only measurements taken from two or more degrees-of-freedom (DOFs) of a machine or structure. This data is typically a measure of surface motion, and can be in displacement, velocity, or acceleration units.

Brian Schwarz

Papers

EXPERIMENTAL MODAL ANALYSIS By

INTRODUCTION TO OPERATING DEFLECTION SHAPES By

Modal Parameter Estimation from Operating Data

Measuring operating deflection shapes under non-stationary conditions

Measurements Required for Displaying Operating Deflection Shapes