Douglas E. Adams

Transmissibility as a Differential Indicator of Structural Damage

This article discusses the use of frequency domain transmissibility functions for detecting, locating, and quantifying damage in linear and nonlinear structures. Structural damage affects both the system poles and zeros; however, zeros are much more sensitive than poles to localized damage. This is because zeros depend on the input and output locations whereas poles do not. It is demonstrated here that since transmissibility functions are determined solely by the system zeros, they are potentially better indicators of localized linear and nonlinear types of damage. Furthermore, excitation measurements are not required to compute transmissibility functions so damage indices can be calculated directly from response measurements. It is also demonstrated that sensor arrays can sometimes be used to yield mixed transmissibility functions that are differential in nature, that is, they are less sensitive to gross fluctuations in the dynamic loading or environmental variables.

A nonlinear dynamical systems framework for structural diagnosis and prognosis

Abstract This work aims to establish a nonlinear dynamics framework for diagnosis and prognosis in structural dynamic systems. The objective is to develop an analytically sound means for extracting features, which can be used to characterize damage, from modal-based input–output data in complex hybrid structures with heterogeneous materials and many components. Although systems like this are complex in nature, the premise of the work here is that damage initiates and evolves in the same phenomenological way regardless of the physical system according to nonlinear dynamic processes. That is, bifurcations occur in healthy systems as a result of damage. By projecting a priori the equations of motion of high-dimensional structural dynamic systems onto lower dimensional center, or so-called ‘damage’, manifolds, it is demonstrated that model reduction near bifurcations might be a useful way to identify certain features in the input–output data that are helpful in identifying damage. Normal forms describing local co-dimension one and two bifurcations (e.g. transcritical, subcritical pitchfork, and asymmetric pitchfork bifurcations) are assumed to govern the initiation and evolution of damage in a low-order model. Real-world complications in damage prognosis involving spatial bifurcations, global bifurcation phenomena, and the sensitivity of damage to small changes in initial conditions are also briefly discussed.

Directional piezoelectric phased array filters for detecting damage in isotropic plates

Phased array filters using piezoelectric sensors are presented as an approach to detect damage in isotropic plates. Plate dynamics can be described in terms of wave propagation. Boundaries and other discontinuities, such as damage, produce reflections from incident wavefronts. Phased arrays, acting as a directional filter, can be used along with a wave propagation approach to look in different directions on a plate. Damage to the plate can be inferred if there is a significant change in the transient response of the plate. The location of this damaged area can be determined using the phased sensor array response. This paper presents results from simulated damage on an isotropic plate. A piezoelectric sensor array is used to actively interrogate the plate to determine the presence and location of damage using low frequency Lamb waves.

Distributed structural health monitoring with a smart sensor array

Abstract This paper presents work on smart sensor arrays for distributed structural health monitoring (SHM) and damage diagnosis. The goal of the work was to implement local vibration-based diagnostic algorithms inside a smart ‘black box’ to demonstrate the feasibility of distributed health monitoring for damage detection and location. Dynamic transmissibility features for SHM and the smart-processing platform are described in detail and various damage configurations in two large test structures, a representative three-storey building and a rotorcraft fuselage, are diagnosed. The results show that the near real-time integrated monitoring system works well in spite of certain limited environmental fluctuations (e.g. temperature, input levels) and boundary condition non-linearities. Wired piezoelectric arrays of accelerometers are implemented in conjunction with the black box.

Vibro-Acoustic Modulation Utilizing a Swept Probing Signal for Robust Crack Detection

One practical issue that must be addressed prior to the implementation of a vibration-based structural health monitoring system is the influence that variations in the structure’s environmental and boundary conditions can have on the vibration response of the structure. This issue is especially prominent in the structural health monitoring of aircraft, which operate in a wide variety of different environmental conditions and possess complex structural components connected through various boundary conditions. However, many types of damage introduce nonlinear stiffness and damping restoring forces, which may be used to detect damage even in the midst of these varying conditions. Vibro-acoustic modulation is a nondestructive evaluation technique that is highly sensitivity to the presence of nonlinearities. One factor that complicates the use of vibro-acoustic modulation as a structural health monitoring technique is that the amount of measured modulation has been shown to be dependent on the frequency of the probing signal. The frequency dependence of the modulation was investigated and the magnitude of modulation was found to be correlated with the underlying vibration characteristics of the structure, which are influenced by environmental and boundary condition variations. To facilitate the use of nonlinear vibro-acoustics for the health monitoring of complex aerospace components in varying environments, a vibro-acoustic modulation technique utilizing a swept probing signal has been developed. The developed method was demonstrated on a steel beam in varying operational conditions. The presence of a crack in the beam was detected both through an increase in the amount of normalized modulation and without the use of historical data by utilizing generalized extreme value statistics.

Classifying Linear and Nonlinear Structural Damage Using Frequency Domain ARX Models

Structural health monitoring can be viewed as a problem in statistical pattern recognition involving operational evaluation, data cleansing, damage identification, and life prediction. In damage identification, damage features derived from available input-output and output-only time and frequency data are used to detect, locate, and quantify damage in structural dynamic systems. A new set of damage features and their implementation for damage detection and quantification are discussed in this article. These features are the autoregressive and exogenous coefficients in a frequency domain data model and can be used to distinguish between linear and nonlinear types of damage. In this work, autoregressive coefficients are used to characterize nonlinear damage and exogenous coefficients are used to characterize linear damage states. The ability to distinguish between linear and nonlinear types of damage and healthy system nonlinearities is critical when diagnosing structural health because damage initiation and growth are fundamentally nonlinear processes. It is shown that absolute damage severity can sometimes be determined solely from the degree of linearity-nonlinearity in the system. Experimental data from a three-story building model is analyzed using these features and some important application issues are discussed.

Structural Damage Identification in Homogeneous and Heterogeneous Structures Using Beamforming

In this study, beamformers consisting of phased sensor or actuator arrays are used in the nondestructive evaluation of homogeneous and heterogeneous structural components. Beamforming can be used to detect, locate, and quantify damage by suitably applying weights and time or phase delays to the tapped signals from a sensor array and/or actuator array in a narrow frequency band to obtain the desired directional sensitivities and optimal array gains. Some aspects about beamforming and wave propagation are discussed as a prelude to the experimental investigation. Design considerations for the phased arrays are also examined. The advantages of using adaptive over conventional beamforming are demonstrated with Frost constraint- and pilot signal-based adaptive techniques. Data from steel and composite plates are analyzed using propagating elastic waves and phased arrays of sensors and/or actuators. Damage, which can be characterized as a local change in impedance, is diagnosed by using propagating elastic waves as they are sensitive to small changes in impedance and do not require a large number of input/output transducers. Beamforming of sensor and/or actuator arrays is carried out to characterize damage in steel and composite plates by comparing the directivity patterns associated with the damage and baseline data.

Modal Analysis of CX-100 Rotor Blade and Micon 65/13 Wind Turbine

At the end of 2008 the United States became the largest producer of wind energy with 25,369 MW of electricity. This accounts for 1.25% of all U.S. electricity generated and enough to power 7 million homes. As wind energy becomes a key player in power generation and in the economy, so does the performance and reliability of wind turbines. To improve both performance and reliability, smart rotor blades are being developed that collocate reference measurements, aerodynamic actuation, and control on the rotor blade. Towards the development of a smart blade, SNL has fabricated a sensored rotor blade with embedded distributed accelerometer measurements to be used with operational loading methods to estimate the rotor blade deflection and dynamic excitation. These estimates would serve as observers for future smart rotor blade control systems. An accurate model of the rotor blade was needed for the development of the operational monitoring methods. An experimental modal analysis of the SNL sensored rotor blade (a modified CX-100 rotor blade) with embedded DC accelerometers was performed when hung with free boundary conditions and when mounted to a Micon 65/13 wind turbine. The modal analysis results and results from a static pull test were used to update an existing distributed parameter CX-100 rotor analytical blade model. This model was updated using percentage error estimates from cost functions of the weighted residuals. The model distributed stiffness parameters were simultaneously updated using the static and dynamic experimental results. The model updating methods decreased all of the chosen error metrics and will be used in future work to update the edge-wise model of the rotor blade and the full turbine model.

System-of-Systems Modeling and Simulation of a Ship Environment With Wireless and Intelligent Maintenance Technologies

Modeling and simulation environments are needed to support decision making in Navy Warfighters, which are emergent systems that pose a challenge to operations management. Ships consist of complex interconnected systems such as the infrastructure, crew, and workflow. A system-of-systems approach using agent-based modeling is applied here to develop workflow simulations involving a ships crew conducting routine maintenance, watch duty, and reporting functions. Simple models are used to describe basic behavioral traits and intelligence in crew members; machinery including sensors for intelligent maintenance; equipment consuming power; mobile and stationary communication network access points; models for data transfer over the network; crew mobility models; power distribution and trimming models for the electrical system; and a fire model to simulate emergency scenarios. The simulation results demonstrate an increase in machine availability due to the implementation of intelligent maintenance systems. The effects of wireless-network usage on crew resource utilization and overall ship capability in normal operational scenarios are also demonstrated. A simple rescheduling algorithm is used to improve crew utilization and estimate manning requirements. The effects of emergency scenarios such as fires in different locations are also studied. Sensitivity analysis is presented to verify the developed model, and a note on validation is given.

Equilibrium point damage prognosis models for structural health monitoring

Most structural dynamic systems are of high order; however, they often exhibit phenomena that can be dealt with effectively using low order models. This paper presents a method for describing certain kinds of damage evolution in mechanical systems. The method relies on a simple principle that as damage evolves in a structural dynamic system, the damage indicator (i.e., diagnostic feature) behaves like a stable quasi-stationary equilibrium point in a subsidiary non-linear bifurcating system within the so-called damage center manifold. It is shown that just as linear normal modes govern the behavior of linear structures with idealized damping, so too do non-linear normal forms govern the evolution of damage within structures in many instances. The method is justified with citations from the literature on certain types of mechanical failure and then applied in an experimental case involving reversible damage in a bolted fastener. Off-line experiments on a rotorcraft fuselage show that the evolution of damage is sensitive to both temporal and spatial bifurcation parameters. A diagnostic sensing strategy whereby output-only transmissibility features are used to decrease the order of high order structural dynamic measurements is also described.