Vibration based baseline updating method to localize crack formation and propagation in reinforced concrete members

Structural Health Monitoring (SHM) schemes are useful for proper management of the performance of structures and for preventing their catastrophic failures. Vibration based SHM schemes has gained popularity during the past two decades resulting in significant research. It is hence evitable that future SHM schemes will include robust and automated vibration based damage assessment techniques (VBDAT) to detect, localize and quantify damage. In this context, the Damage Index (DI) method which is classified as non-model or output based VBDAT, has the ability to automate the damage assessment process without using a computer or numerical model along with actual measurements. Although damage assessment using DI methods have been able to achieve reasonable success for structures made of homogeneous materials such as steel, the same success level has not been reported with respect to Reinforced Concrete (RC) structures. The complexity of flexural cracks is claimed to be the main reason to hinder the applicability of existing DI methods in RC structures. Past research also indicates that use of a constant baseline throughout the damage assessment process undermines the potential of the Modal Strain Energy based Damage Index (MSEDI). To address this situation, this paper presents a novel method that has been developed as part of a comprehensive research project carried out at Queensland University of Technology, Brisbane, Australia. This novel process, referred to as the baseline updating method, continuously updates the baseline and systematically tracks both crack formation and propagation with the ability to automate the damage assessment process using output only data. The proposed method is illustrated through examples and the results demonstrate the capability of the method to achieve the desired outcomes.

Structural damage alarming and localization of cable-supported bridges using multi-novelty indices: A feasibility study

This paper presents a feasibility study on structural damage alarming and localization of long-span cable-supported bridges using multi-novelty indices formulated by monitoring-derived modal parameters. The proposed method which requires neither structural model nor damage model is applicable to structures of arbitrary complexity. With the intention to enhance the tolerance to measurement noise/uncertainty and the sensitivity to structural damage, an improved novelty index is formulated in terms of auto-associative neural networks (ANNs) where the output vector is designated to differ from the input vector while the training of the ANNs needs only the measured modal properties of the intact structure under in-service conditions. After validating the enhanced capability of the improved novelty index for structural damage alarming over the commonly configured novelty index, the performance of the improved novelty index for damage occurrence detection of large-scale bridges is examined through numerical simulation studies of the suspension Tsing Ma Bridge (TMB) and the cable-stayed Ting Kau Bridge (TKB) incurred with different types of structural damage. Then the improved novelty index is extended to formulate multi-novelty indices in terms of the measured modal frequencies and incomplete modeshape components for damage region identification. The capability of the formulated multi-novelty indices for damage region identification is also examined through numerical simulations of the TMB and TKB.

Sense of modern heritage

As the society matures, there was an increasing pressure to preserve historic buildings. The economic cost in maintaining these important heritage legacies has become the prime consideration of every state. Dedicated intelligent monitoring systems supplementing the traditional building inspections will enable the stakeholder to carry out not only timely reactive response but also plan the maintenance in a more vigilant approach; thus, preventing further degradation which was very costly and difficult to address if neglected. The application of the intelligent structural health monitoring system in this case studies of ‘modern heritage’ buildings is on its infancy but it is an innovative approach in building maintenance. ‘Modern heritage’ buildings were the product of technological change and were made of synthetic materials such as reinforced concrete and steel. Architectural buildings that was very common in Oceania and The Pacific. Engineering problems that arose from this type of building calls for immediate engineering solution since the deterioration rate is exponential. The application of this newly emerging monitoring system will improve the traditional maintenance system on heritage conservation. Savings in time and resources can be achieved if only pathological results were on hand. This case study will validate that approach. This publication will serve as a position paper to the on-going research regarding application of (Structural Health Monitoring) SHM systems to heritage buildings in Brisbane, Australia. It will be investigated with the application of the SHM systems and devices to validate the integrity of the recent structural restoration of the newly re-strengthened heritage building, the Brisbane City Hall.

Model updating of real structures with ambient vibration data

It is important to develop reliable finite element models for real structures not only in the design phase but also for the structural health monitoring and structural maintenance purposes. This paper describes the experience of the authors in using ambient vibration model identification techniques together with model updating tools to develop reliable finite element models of real civil engineering structures. Case studies of two real structures are presented in this paper. One is a 10 storey concrete building which is considered as a non-slender structure with complex boundary conditions. The other is a single span concrete foot bridge which is also a relatively inflexible planar structure with complex boundary conditions. Both structures are located at the Queensland University of Technology (QUT) and equipped with continuous structural health monitoring systems.

Structural identification of a laboratory-based steel through truss cantilevered bridge with suspended span using a layered genetic algorithm with patternsearch step (GAPS)

Structural identification (St-Id) can be considered as the process of updating a finite element (FE) model of a structural system to match the measured response of the structure. This paper presents the St-Id of a laboratory-based steel through-truss cantilevered bridge with suspended span. There are a total of 600 degrees of freedom (DOFs) in the superstructure plus additional DOFs in the substructure. The St-Id of the bridge model used the modal parameters from a preliminary modal test in the objective function of a global optimisation technique using a layered genetic algorithm with patternsearch step (GAPS). Each layer of the St-Id process involved grouping of the structural parameters into a number of updating parameters and running parallel optimisations. The number of updating parameters was increased at each layer of the process. In order to accelerate the optimisation and ensure improved diversity within the population, a patternsearch step was applied to the fittest individuals at the end of each generation of the GA. The GAPS process was able to replicate the mode shapes for the first two lateral sway modes and the first vertical bending mode to a high degree of accuracy and, to a lesser degree, the mode shape of the first lateral bending mode. The mode shape and frequency of the torsional mode did not match very well. The frequencies of the first lateral bending mode, the first longitudinal mode and the first vertical mode matched very well. The frequency of the first sway mode was lower and that of the second sway mode was higher than the true values, indicating a possible problem with the FE model. Improvements to the model and the St-Id process will be presented at the upcoming conference and compared to the results presented in this paper. These improvements will include the use of multiple FE models in a multi-layered, multi-solution, GAPS St-Id approach.

A new twist on mode indicator functions

Mode indicator functions (MIFs) are used in modal testing and analysis as a means of identifying modes of vibration, often as a precursor to modal parameter estimation. Various methods have been developed since the MIF was introduced four decades ago. These methods are quite useful in assisting the analyst to identify genuine modes and, in the case of the complex mode indicator function, have even been developed into modal parameter estimation techniques. Although the various MIFs are able to indicate the existence of a mode, they do not provide the analyst with any descriptive information about the mode. This paper uses the simple summation type of MIF to develop five averaged and normalised MIFs that will provide the analyst with enough information to identify whether a mode is longitudinal, vertical, lateral or torsional. The first three functions, termed directional MIFs, have been noted in the literature in one form or another; however, this paper introduces a new twist on the MIF by introducing two MIFs, termed torsional MIFs, that can be used by the analyst to identify torsional modes and, moreover, can assist in determining whether the mode is of a pure torsion or sway type (i.e., having a rigid cross-section) or a distorted twisting type. The directional and torsional MIFs are tested on a finite element model based simulation of an experimental modal test using an impact hammer. Results indicate that the directional and torsional MIFs are indeed useful in assisting the analyst to identify whether a mode is longitudinal, vertical, lateral, sway, or torsion.

Use of modal flexibility method to detect damage in suspended cables and the effects of cable parameters

Modal flexibility is a widely accepted technique to detect structural damage using vibration characteristics. Its application to detect damage in long span large diameter cables such as those used in suspension bridge main cables has not received much attention. This paper uses the modal flexibility method incorporating two damage indices (DIs) based on lateral and vertical modes to localize damage in such cables. The competency of those DIs in damage detection is tested by the numerically obtained vibration characteristics of a suspended cable in both intact and damaged states. Three single damage cases and one multiple damage case are considered. The impact of random measurement noise in the modal data on the damage localization capability of these two DIs is next examined. Long span large diameter cables are characterized by the two critical cable parameters named bending stiffness and sag-extensibility. The influence of these parameters in the damage localization capability of the two DIs is evaluated by a parametric study with two single damage cases. Results confirm that the damage index based on lateral vibration modes has the ability to successfully detect and locate damage in suspended cables with 5% noise in modal data for a range of cable parameters. This simple approach therefore can be extended for timely damage detection in cables of suspension bridges and thereby enhance their service during their life spans.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Oesophagogastric ulceration in pigs: A visual morphological scoring guide

Objective: To provide a visual guide for oesophagogastric ulcer scoring and recognition of different morphological changes in the pars oesophagea. Design: Pig stomachs were collected at slaughter and visually evaluated and scored for parakeratosis, erosion and ulceration in the pars oesophagea. Results: A visual and descriptive guide is presented that will aid in the objective assessment and scoring of oesophagogastric ulceration in pigs within the pig health monitoring system (PHMS), namely to the four categories of 0 = normal stomach, 1 = parakeratosis and thickened epithelium, 2 = erosions and 3 = developed ulcers with and without stenosis. Conclusion: A visual guide has been developed that illustrates the full range of morphological changes that can occur in the pars oesophagea of the stomach within the few currently recognised stages of the disease.

Structural Damage Detection Using Modal Curvature and Fuzzy Logic

A fuzzy logic system (FLS) with a new sliding window defuzzifier is proposed for structural damage detection using modal curvatures. Changes in the modal curvatures due to damage are fuzzified using Gaussian fuzzy sets and mapped to damage location and size using the FLS. The first four modal vectors obtained from finite element simulations of a cantilever beam are used for identifying the location and size of damage. Parametric studies show that modal curvatures can be used to accurately locate the damage; however, quantifying the size of damage is difficult. Tests with noisy simulated data show that the method detects damage very accurately at different noise levels and when some modal data are missing.

Optimal dynamic inversion-based semi-active control of benchmark bridge using MR dampers

A new two-stage state feedback control design approach has been developed to monitor the voltage supplied to magnetorheological (MR) dampers for semi-active vibration control of the benchmark highway bridge. The first stage contains a primary controller, which provides the force required to obtain a desired closed-loop response of the system. In the second stage, an optimal dynamic inversion (ODI) approach has been developed to obtain the amount of voltage to be supplied to each of the MR dampers such that it provides the required force prescribed by the primary controller. ODI is formulated by optimization with dynamic inversion, such that an optimal voltage is supplied to each damper in a set. The proposed control design has been simulated for both phase-I and phase-II study of the recently developed benchmark highway bridge problem. The efficiency of the proposed controller is analyzed in terms of the performance indices defined in the benchmark problem definition. Simulation results demonstrate that the proposed approach generally reduces peak response quantities over those obtained from the sample semi-active controller, although some response quantities have been seen to be increasing. Overall, the proposed control approach is quite competitive as compared with the sample semi-active control approach.

Finite element modelling of lamb wave propagation in prestress concrete and effect of the prestress force on the wave’s characteristic

In order to assess the structural reliability of bridges, an accurate and cost effective Non-Destructive Evaluation (NDE) technology is required to ensure their safe and reliable operation. Over 60% of the Australian National Highway System is prestressed concrete (PSC) bridges according to the Bureau of Transport and Communication Economics (1997). Most of the in-service bridges are more than 30 years old and may experience a heavier traffic load than their original intended level. Use of Ultrasonic waves is continuously increasing for (NDE) and Structural Health Monitoring (SHM) in civil, aerospace, electrical, mechanical applications. Ultrasonic Lamb waves are becoming more popular for NDE because it can propagate long distance and reach hidden regions with less energy loses. The purpose of this study is to numerically quantify prestress force (PSF) of (PSC) beam using the fundamental theory of acoustic-elasticity. A three-dimension finite element modelling approach is set up to perform parametric studies in order to better understand how the lamb wave propagation in PSC beam is affected by changing in the PSF level. Results from acoustic-elastic measurement on prestressed beam are presented, showing the feasibility of the lamb wave for PSF evaluation in PSC bridges.

Time Domain Characteristics of Electrical Measures for a Piezoelectric Thin Film to Identify Defects in the Substrate

A reduced 3D continuum model of dynamic piezoelectricity in a thin-film surface-bonded to the substrate/host is presented in this article. While employing large area flexible thin piezoelectric films for novel applications in device/diagnostics, the feasibility of the proposed model in sensing the surface and/or sub-surface defects is demonstrated through simulations - which involve metallic beams with cracks and composite beam with delaminations of various sizes. We have introduced a set of electrical measures to capture the severity of the damage in the existing structures. Characteristics of these electrical measures in terms of the potential difference and its spatial gradients are illustrated in the time domain. Sensitivity studies of the proposed measures in terms of the defected areas and their region of occurence relative to the sensing film are reported. The simulations' results for electrical measures for damaged hosts/substrates are compared with those due to undamaged hosts/substrates, which show monotonicity with high degree of sensitivity to variations in the damage parameters.

Evaluation of material crack using acoustic emission technique

Cracks in civil structures can result in premature failure due to material degradation and can result in both financial loss and environmental consequences. This thesis reports an effective technique using Acoustic Emission (AE) technique to assess the severity of the crack propagation in steel structures. The outcome of this work confirms that combination of AE parametric analysis and signal processing techniques can be used to evaluate crack propagation under different loading configurations. The technique has potential application to assess and monitor the condition of civil structures.

Sensitivity of Eigen Value to Damage and Its Identification

The reduction in natural frequencies,however small, of a civil engineering structure, is the first and the easiest method of estimating its impending damage. As a first level screening for health-monitoring, information on the frequency reduction of a few fundamentalmodes can be used to estimate the positions and the magnitude of damage in a smeared fashion. The paper presents the Eigen value sensitivity equations, derived from first-order perturbation technique, for typical infra-structural systems like a simply supported bridge girder, modelled as a beam, an endbearing pile, modelled as an axial rod and a simply supported plate as a continuum dynamic system. A discrete structure, like a building frame is solved for damage using Eigen-sensitivity derived by a computationalmodel. Lastly, neural network based damage identification is also demonstrated for a simply supported bridge beam, where the known-pairs of damage-frequency vector is used to train a neural network. The performance of these methods under the influence of measurement error is outlined. It is hoped that the developed method could be integrated in a typical infra-structural management program, such that magnitudes of damage and their positions can be obtained using acquired natural frequencies, synthesized from the excited/ambient vibration signatures.