A signal processing approach for elastic wave-based structural health monitoring using active piezoelectrics

A series of digital frequency filters (DFFs) were designed to screen diverse noises and the spectrographic analysis was conducted to isolate complex boundary reflection, which obscures the damage-induced signals. The scale-averaged wavelet power (SAP) technique was applied to enhance
the measurement accuracy of Time of Flight (TOF). As an example, the propagation characteristics of elastic wave in a structural beam of square cross-section were analyzed using such an approach and verified experimentally and numerically, with the consideration of the complicated wave scatter caused by the non-ignorable section dimensions.

Functionalised roving for structural health monitoring of composites

Here, we investigated photochromic glass fibre threads produced with the sol-gel coating technique and used it as sewing threads to produce stitched glass-polypropylene composites. The possibility of making sol-gel photochromic glass fibre threads, the morphology of the glass fibre thread and the tensile property of glass fibre sewing threads before and after sol-gel treatment have been studied in this work. The photochromic glass fibre thread was successfully stitched into glass-polypropylene composites as sewing threads and showed an efficient and effective response to UV light. Our results indicate that sol-gel coating is an efficient way to produce photochromic glass fibre. In addition, the sol-gel coating does not significantly affect the tensile performance of the glass fibre.

Structural health monitoring: a practical approach to achieving in-situ and site-specific warning of pipeline corrosion and coating failure

An approach to achieving the ambitious goal of cost effectively extending the safe operation life of energy pipelines to, for instance, 100 years is the application of structural health monitoring and life prediction tools that are able to provide long-term remnant pipeline life prediction and in-situ pipeline condition monitoring. A critical step in pipeline structural health monitoring is the enhancement of technological capabilities that are required for quantifying the effects of key factors influencing buried pipeline corrosion and environmentally assisted materials degradation, and the development of condition monitoring technologies that are able to provide in-situ monitoring and site-specific warning of pipeline damage. This paper provides an overview of our current research aimed at developing new sensors for monitoring, categorising and quantifying the level and nature of external pipeline and coating damages under the combined effects of various inter-related variables and processes such as localised corrosion, coating damage and disbondment, cathodic shielding. The concept of in-situ monitoring and site-specific warning of pipeline corrosion is illustrated by a case of monitoring localised corrosion under disbonded coatings using a new corrosion monitoring probe. A basic principle that underpins the use of sensors to monitor localised corrosion has been presented: Localised corrosion and coating failure are not an accidental occurrence, it occurs as the result of fundamental thermodynamic instability of a metal exposed to a specific environment. Therefore corrosion and coating disbondment occurring on a pipeline will also occur on a sensor made of the same material and exposed to the same pipeline condition. Although the exact location of localised corrosion or coating disbondment could be difficult to pinpoint along the length of a buried pipeline, the ‘worst-case scenario’ and high risk pipeline sections and sites are predictable. Sensors can be embedded at these strategic sites to collect data that contain ‘predictor features’ signifying the occurrence of localised corrosion, CP failure, coating disbondment and degradation. Information from these sensors will enable pipeline owners to prioritise site survey and inspection operations, and to develop maintenance strategy to manage aged pipelines, rather than replace them.

Integrated health monitoring for reinforced concrete beams: an experimental study

Civil infrastructures begin to deteriorate once they are built and used. Detecting the damages in a structure to maintain its safety is a topic that has received considerable attention in the literature in recent years. In vibration-based methods, the first few modes are used to assess the locations and the amount of damage. However, a small number of the global modes are not sufficient to reliably detect minor damage in the structure. Also, a common limitation of these techniques is that they require a high-fidelity model of the structure to start with, which is usually not available. Recently, guided waves (GW) have been found as an effective and efficient way to detect incipient damages due to its capacity of relatively long propagation range as well as its flexibility in selecting sensitive mode-frequency combinations. In this paper, an integrated structural health monitoring test scheme is developed to detect damages in reinforced concrete (RC) beams. Each beam is loaded at the middle span progressively to damage. During each loading step, acoustic emission (AE) method is used as a passive monitoring method to catch the AE signals caused by the crack opening and propagation. After each loading step, vibration tests and guided wave tests are conducted as a combined active monitoring measure. The modal parameters and wave propagation results are used to derive the damage information. Experimental results show that the integrated method is efficient to detect incipient damages in RC structures.

Vibration based damage identification of a scale-model steel frame structure subjected to bolt connection failures

Large-span steel frame structures prove to be an ideal choice for their speed of construction, relatively low cost, strength, durability and structural design flexibility. For this type of structure, the beam-column connections are critical for its structural integrity and overall stability. This is because a steel frame generally fails first at its connectors, due to the change in stress redistribution with adjacent members and material related failures, caused by various factors such as fire, seismic activity or material deterioration. Since particular attention is required at a steel frame’s connection points, this study explores the applicability of a comprehensive structural health monitoring (SHM) method to identify early damage and prolong the lifespan of connection points of steel frames. An impact hammer test was performed on a scale-model steel frame structure, recording its dynamic response to the hammer strike via an accelerometer. The testing procedure included an intact scenario and two damage scenarios by unfastening four bolt connections in an accumulating order. Based entirely on time-domain experimental data for its calibration, an Auto Regressive Average Exogenous (ARMAX) model is used to create a simple and accurate model for vibration simulation. The calibrated ARMAX model is then used to identify various bolt-connection related damage scenarios via R² value. The findings in this study suggest that the proposed time-domain approach is capable of identifying structural damage in a parsimonious manner and can be used as a quick or initial solution.

Investigating strain transfer in polymer coated structures for the health monitoring of aerospace vehicles using polymer photonic waveguides

In this work, we present the concept of planar polymer photonic waveguides for the health monitoring of aerospace structures. Here a polymer layer is deposited onto the material/structure to be monitored. Within the polymer layer, waveguides are created after deposition. These waveguides can then be used as 'optical fibres' for optical fibre sensing methodologies. In investigating the use of polymer photonic waveguides the question to be answered is: does the strain in the test material transfer to the polymer layer, such that the value to be measured optically is reliable and indicative of the true strain in the test structure? To answer this question we have conducted a preliminary structural analysis with finite element analysis, utilising ANSYS. A simple aluminium cantilever was used as the test structure, and layers of polyethylene with different thicknesses were added to this. Result show that the thinner the layer of polymer, the more accurate the measured strain will be. For a 100um coating, the difference is strain was observed to be on the order of 3.3%. © 2014 IEEE.

Structural damage identification based on self-fitting ARMAX model and multi-sensor data fusion

Statistical time series methods have proven to be a promising technique in structural health monitoring, since it provides a direct form of data analysis and eliminates the requirement for domain transformation. Latest research in structural health monitoring presents a number of statistical models that have been successfully used to construct quantified models of vibration response signals. Although a majority of these studies present viable results, the aspects of practical implementation, statistical model construction and decision-making procedures are often vaguely defined or omitted from presented work. In this article, a comprehensive methodology is developed, which essentially utilizes an auto-regressive moving average with exogenous input model to create quantified model estimates of experimentally acquired response signals. An iterative self-fitting algorithm is proposed to construct and fit the auto-regressive moving average with exogenous input model, which is capable of integrally finding an optimum set of auto-regressive moving average with exogenous input model parameters. After creating a dataset of quantified response signals, an unlabelled response signal can be identified according to a 'closest-fit' available in the dataset. A unique averaging method is proposed and implemented for multi-sensor data fusion to decrease the margin of error with sensors, thus increasing the reliability of global damage identification. To demonstrate the effectiveness of the developed methodology, a steel frame structure subjected to various bolt-connection damage scenarios is tested. Damage identification results from the experimental study suggest that the proposed methodology can be employed as an efficient and functional damage identification tool. © The Author(s) 2014.

Damage identification scheme based on compressive sensing

Civil infrastructures are critical to every nation, due to their substantial investment, long service period, and enormous negative impacts after failure. However, they inevitably deteriorate during their service lives. Therefore, methods capable of assessing conditions and identifying damage in a structure timely and accurately have drawn increasing attention. Recently, compressive sensing (CS), a significant breakthrough in signal processing, has been proposed to capture and represent compressible signals at a rate significantly below the traditional Nyquist rate. Due to its sound theoretical background and notable influence, this methodology has been successfully applied in many research areas. In order to explore its application in structural damage identification, a new CS-based damage identification scheme is proposed in this paper, by regarding damage identification problems as pattern classification problems. The time domain structural responses are transferred to the frequency domain as sparse representation, and then the numerical simulated data under various damage scenarios will be used to train a feature matrix as input information. This matrix can be used for damage identification through an optimization process. This will be one of the first few applications of this advanced technique to structural engineering areas. In order to demonstrate its effectiveness, numerical simulation results on a complex pipe soil interaction model are used to train the parameters and then to identify the simulated pipe degradation damage and free-spanning damage. To further demonstrate the method, vibration tests of a steel pipe laid on the ground are carried out. The measured acceleration time histories are used for damage identification. Both numerical and experimental verification results confirm that the proposed damage identification scheme will be a promising tool for structural health monitoring.

Evidence-based public health: what does it offer developing countries?

The global burden of disease and illness is primarily situated in developing countries. As developing countries have limited resources, it is particularly important to invest in public health and health promotion strategies that are effective. Systematic reviews are central to evidence-based public health and health promotion practice and policy. This paper discusses issues surrounding the relevance of evidence-based public health and systematic reviews to the health of developing countries. It argues that there is a lack of systematic reviews relevant to the health priorities of developing countries; many interventions reviewed can not be implemented in resource-poor situations; and, a limited amount of primary research is conducted in developing countries. The paper further argues that improvements in public health are determined not only by effective health services and interventions, but through an approach that includes other sectors and influences broader structural and systematic barriers to health. Given the social complexity of human development, and the inter-sections amongst different development goals, there is no question that gains in developing country public health are unlikely to emerge from systematic reviews alone, but will require decisions about inter-sectoral collaboration and social policy initiatives. Nonetheless, evidence around intervention effectiveness has an important role to play in addressing health priorities in developing countries and resource-poor areas. The public health evidence base urgently needs strengthening, with dedicated effort towards increasing the relevance of primary evidence and systematic reviews.

Sea search : a community-based citizen science monitoring program for Victoria, Australia, Marine National Parks and Marine Sanctuaries

Community involvement in monitoring Victoria’s Marine Protected Areas (MPAs) engages coastal volunteers in looking after their marine ‘front yards”. The Management Strategy for Victoria’s System of Marine National Parks and Marine Sanctuaries dedicates an entire theme to community engagement with core key performance areas. This includes community participation. The Sea Search community based monitoring program was developed in 2003 to engage volunteers in meaningful ecological data collection for future sustainability of Victoria’s MPAs. Deakin University, an academic institute, and Parks Victoria, the management agency for Victoria’s MPAs, through a research partner program, trialled three different habitat monitoring methodologies. The trails assessed volunteer ability to collect scientific data, and social science aspects for their involvement in a community-based monitoring program. Information collected by volunteers, feeds directly into their local MPA management strategies to address issues such as climate change, introduced pests and human impacts and natural ecological variation.

The Sea Search program addresses the two action programmes, Agenda 21 and the Rio Declaration on Environment and Development, created at the United Nations Earth Summit, held in 1992. Both documents highlight the need for community engagement and capacity building for sustainability, health and integrity of the earth. Involvement in the Sea Search program builds the volunteer’s capacity by learning scientific skills, interacting with other like minded community members, and creating relationships with all organisations involved in the delivery of the program. In this regard, Sea Search is a citizen science program involving all sectors in society by promoting public-interest and research for decision making and planning of Victoria’s system of Marine National Parks and Marine Sanctuaries.

Modelling of guided wave propagation with spectral element: application in structural engineering

Among many structural health monitoring (SHM) methods, guided wave (GW) based method has been found as an effective and efficient way to detect incipient damages. In comparison with other widely used SHM methods, it can propagate in a relatively long range and be sensitive to small damages. Proper use of this technique requires good knowledge of the effects of damage on the wave characteristics. This needs accurate and computationally efficient modeling of guide wave propagation in structures. A number of different numerical computational techniques have been developed for the analysis of wave propagation in a structure. Among them, Spectral Element Method (SEM) has been proposed as an efficient simulation technique. This paper will focus on the application of GW method and SEM in structural health monitoring. The GW experiments on several typical structures will be introduced first. Then, the modeling techniques by using SEM are discussed. © (2014) Trans Tech Publications, Switzerland.

Some aspects of numerical simulation for lamb wave propogation in composite laminates

Some aspects of numerical simulation of Lamb wave propagation in composite laminates using the finite element models with explicit dynamic analysis are addressed in this study. To correctly and efficiently describe the guided-wave excited/received by piezoelectric actuators/sensors, effective models of surface-bounded flat PZT disks based on effective force, moment and displacement are developed. Different finite element models for Lamb wave excitation, collection and propagation in isotropic plate and quasi-isotropic laminated composite are evaluated using continuum elements (3-D solid element) and structural elements (3-D shell element), to elaborate the validity and versatility of the proposed actuator/sensor models.

Evidence-based mental health nursing in Australia: our history and our future

This paper will develop a discussion related to evidence-based knowledge for mental health nursing, arguing for a historical component to be included in the comprehensive degree programme that will offer significant insights into mental health nursing knowledge from historical information and constructing implications for contemporary practice. Our understanding of the present is clearer by this looking back and forth and by adding meaning (and what the meanings mean) to what historically preceded. It allows the history of psychiatry to be a much more productive, useful, and a continual source of wisdom for the here and now. This blending of past knowledge with contemporary inquiry can offer depth in mental health nursing practices by forming a context for practice for the beginning nurse practitioner.