Scott W. Doebling

Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review

This report contains a review of the technical literature concerning the detection, location, and characterization of structural damage via techniques that examine changes in measured structural vibration response. The report first categorizes the methods according to required measured data and analysis technique. The analysis categories include changes in modal frequencies, changes in measured mode shapes (and their derivatives), and changes in measured flexibility coefficients. Methods that use property (stiffness, mass, damping) matrix updating, detection of nonlinear response, and damage detection via neural networks are also summarized. The applications of the various methods to different types of engineering problems are categorized by type of structure and are summarized. The types of structures include beams, trusses, plates, shells, bridges, offshore platforms, other large civil structures, aerospace structures, and composite structures. The report describes the development of the damage-identification methods and applications and summarizes the current state-of-the-art of the technology. The critical issues for future research in the area of damage identification are also discussed.

A summary review of vibration-based damage identification methods

This paper provides an overview of methods to detect, locate, and characterize damage in structural and mechanical systems by examining changes in measured vibration response. Research in vibration-based damage identification has been rapidly expanding over the last few years. The basic idea behind this technology is that modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical properties of the structure (mass, damping, and stiffness). Therefore, changes in the physical properties will cause detectable changes in the modal properties. The motivation for the development of this technology is presented. The methods are categorized according to various criteria such as the level of damage detection provided, model-based versus non-model-based methods, and linear versus nonlinear methods. The methods are also described in general terms including difficulties associated with their implementation and their fidelity. Past, current, and future-planned applications of this technology to actual engineering systems are summarized. The paper concludes with a discussion of critical issues for future research in the area of vibration-based damage identification.

Vibration–based structural damage identification

Many aerospace, civil and mechanical systems continue to be used despite ageing and the associated potential for damage accumulation. Therefore, the ability to monitor the structural health of these systems is becoming increasingly important. A wide variety of highly effective local non–destructive evaluation tools is available. However, damage identification based upon changes in vibration characteristics is one of the few methods that monitor changes in the structure on a global basis. A summary of developments in the field of global structural health monitoring that have taken place over the last thirty years is first presented. Vibration–based damage detection is a primary tool that is employed for this monitoring. Next, the process of vibration based damage detection will be described as a problem in statistical pattern recognition. This process is composed of three portions: (i) data acquisition and cleansing; (ii) feature selection and data compression; and (iii) statistical model development. Current research regarding feature selection and statistical model development will be emphasized with the application of this technology to a large–scale laboratory structure.

Improved Damage Location Accuracy Using Strain Energy-Based Mode Selection Criteria

A method is presented for selecting the subset of identified structural vibration modes to be used in finite element model correlation for structural damage detection. The method is hased on a ranking of the modes using measured modal strain energy and is a function of only the measured modal parameters. It is shown that a mode selection strategy based on maximum modal strain energy produces more accurate update results than a strategy based on minimum frequency. Strategies that use the strain energy stored by modes in both the undamaged and damaged structural configuration are considered. It is demonstrated that more accurate results are obtained when the modes are selected using the maximum strain energy stored in the damaged structural configuration. The mode selection techniques are applied to the results of a damage detection experiment on a suspended truss structure that has a large amount of localized modal behavior.

Minimum-rank optimal update of elemental stiffness parameters for structural damage identification

A new optimal update method for the correlation of dynamic structural finite element models with modal data is presented. The method computes a minimum-rank solution for the perturbations of the elemental stiffness parameters while constraining the connectivity of the global stiffness matrix. The resulting model contains a more accurate representation of the dynamics of the test structure, and the changes between the original model and the updated model can be interpreted as modeling errors or as changes in the structure resulting from damage. The motivation for the method is presented in the context of existing optimal matrix update procedures. This method is distinct from past minimum-rank optimal update procedures because it computes minimum-rank updates directly to the elemental stiffness parameters. The method is demonstrated numerically on a spring-mass system and is also applied to experimental data from the NASA Langley Research Center eight-bay truss damage detection experiment. The results demonstrate that the proposed procedure may be useful for updating elemental stiffness parameters in the context of damage detection and model refinement.

Estimation of reciprocal residual flexibility from experimental modal data

A technique is presented for estimating the residual flexibility between nonexcited structural degrees of freedom from experimental structural vibration data. Using this method, one can include the residual flexibility estimated from modal measurements in the computation of measured flexibility for experiments with incomplete reciprocity, i.e., when the response and excitation measurement sensors are not fully collocated. The method can also be used to estimate the unknown entries in the residual flexibility matrix for experimental component mode synthesis when excitations are not provided at all interface degrees of freedom. A general solution is presented that contains an unknown positive semidefinite contribution. The general solution satisfies modal orthogonality in the limit that all of the structural degrees of freedom are instrumented and when the positive semidefinite contribution lies in a nullspace defined by the stiffness matrix and the modal flexibility. With a limited number of measurements, modal orthogonality is shown to be satisfied to the extent that the measured modes are preserved by static condensation. A rank-deficient solution is presented that allows the residual to be used in the computation of the flexibility matrix without further modeling assumptions. Numerical and experimental results that demonstrate the application of the method to both flexibility matrix convergence and experimental component mode synthesis are presented.

Overview of Uncertainty Assessment for Structural Health Monitoring

ABSTRACT Uncertainty quantification is an emergent field in engineering mechanics that makes use of statistical sampling, hypothesis testing and input-output effect analysis to characterize the effect that parametric and non-parametric uncertainty has on physical experiment or numerical simulation output. This publication overviews a project at Los Alamos National Laboratory that aims at developing a methodology for quantifying uncertainty and assessing the total predictability of structural dynamics simulations. The propagation of parametric variability through numerical simulations is discussed. Uncertainty assessment is also a critical component of model validation, where the total error between physical observation and model prediction must be characterized. The purpose of model validation is to assess the extent to which a model is an appropriate representation of reality, given the purpose intended for the numerical simulation and its domain of applicability. The discussion is illustrated with component-level and system-level validation experiments that feature the response of nonlinear models to impulse excitation sources. This publication is unclassified; it has been approved for unlimited, public release (number LA-UR-01-3828).

Estimation Of Statistical Distributions For Modal Parameters Identified From Averaged Frequency Response Function Data

An algorithm is presented to estimate the statistical distributions of identified modal parameters based on the random errors associated with averaged frequency response function (FRF) estimates. In this study, the modal parameters are assumed to be random variables and the objective is to estimate their dis tribution statistics (e.g., mean and variance). The algorithm first uses a classical approach to estimate the error on the averaged FRF using the coherence function averaged over an ensemble of measured samples. A Monte Carlo simulation approach is then used to propagate the estimated spectral function errors through the modal parameter identification process. A bootstrap estimate of the modal parameter distribution over the full ensemble of individual measurement samples is used to verify the accuracy of the Monte Carlo algo rithm. The statistics of the resulting modal parameter distribution are suitable for use as weights or filtering criteria in model correlation and damage identification schemes. Convergence criteria for determining how many Monte Carlo simulations are required are also presented and discussed. The technique is demonstrated via application to a simulated FRF with known parameter distributions and to experimental data from tests of an in situ bridge.

Selection of experimental modal data sets for damage detection via model update

When using a finite element model update algorithm for detecting damage in structures, it is important that the experimental modal data sets used in the update be selected in a coherent manner. In the case of a structure with extremely localized modal behavior, it is necessary to use both low and high frequency modes, but many of the modes in between may be excluded. In this paper, we examine two different mode selection strategies based on modal strain energy, and compare their success to the choice of an equal number of modes based merely on lowest frequency. Additionally, some parameters are introduced to enable a quantitative assessment of the success of our damage detection algorithm when using the various set selection criteria.

OVERVIEW OF STRUCTURAL DYNAMICS MODEL VALIDATION ACTIVITIES AT LOS ALAMOS NATIONAL LABORATORY

This presentation will provide a summary of the research and applications of structural dynamics model validation at Los Alamos National Laboratory. In this context model validation refers to the assessment of confidence in the usefulness of computational structural dynamics predictions for a particular application. The presentation will cover the problem definition, objectives, and motivation for studying model validation. Current paradigms for the model validation problem will also be presented. Supporting technologies such as uncertainty quantification, global sensitivity analysis, metamodeling, parameter updating, and design of experiments will be discussed, along with their role in the model validation process. The usefulness of model validation results for the computational modeling of system-level structural dynamics will be demonstrated. Examples of model validation techniques applied to transient structural dynamics problems of interest will be shown.