Use of acoustic emission technique for structural health monitoring of bridges

Bridges are valuable assets of every nation. They deteriorate with age and often are subjected to additional loads or different load patterns than originally designed for. These changes in loads can cause localized distress and may result in bridge failure if not corrected in time. Early detection of damage and appropriate retrofitting will aid in preventing bridge failures. Large amounts of money are spent in bridge maintenance all around the world. A need exists for a reliable technology capable of monitoring the structural health of bridges, thereby ensuring they operate safely and efficiently during the whole intended lives. Monitoring of bridges has been traditionally done by means of visual inspection. Visual inspection alone is not capable of locating and identifying all signs of damage, hence a variety of structural health monitoring (SHM) techniques is used regularly nowadays to monitor performance and to assess condition of bridges for early damage detection. Acoustic emission (AE) is one technique that is finding an increasing use in SHM applications of bridges all around the world. The chapter starts with a brief introduction to structural health monitoring and techniques commonly used for monitoring purposes. Acoustic emission technique, wave nature of AE phenomenon, previous applications and limitations and challenges in the use as a SHM technique are also discussed. Scope of the project and work carried out will be explained, followed by some recommendations of work planned in future.

Development of an online condition monitoring system for slow speed machinery

One of the main challenges of slow speed machinery condition monitoring is that the energy generated from an incipient defect is too weak to be detected by traditional vibration measurements due to its low impact energy. Acoustic emission (AE) measurement is an alternative for this as it has the ability to detect crack initiations or rubbing between moving surfaces. However, AE measurement requires high sampling frequency and consequently huge amount of data are obtained to be processed. It also requires expensive hardware to capture those data, storage and involves signal processing techniques to retrieve valuable information on the state of the machine. AE signal has been utilised for early detection of defects in bearings and gears. This paper presents an online condition monitoring (CM) system for slow speed machinery, which attempts to overcome those challenges. The system incorporates relevant signal processing techniques for slow speed CM which include noise removal techniques to enhance the signal-to-noise and peak-holding down sampling to reduce the burden of massive data handling. The analysis software works under Labview environment, which enables online remote control of data acquisition, real-time analysis, offline analysis and diagnostic trending. The system has been fully implemented on a site machine and contributing significantly to improve the maintenance efficiency and provide a safer and reliable operation.

Participation index : a measure to identify rural transport disadvantage?

This paper develops a composite participation index (PI) to identify patterns of transport disadvantage in space and time. It is operationalised using 157 weekly activity-travel diaries data collected from three case study areas in rural Northern Ireland. A review of activity space and travel behaviour research found that six dimensional indicators of activity spaces were typically used including the number of unique locations visited, distance travelled, area of activity spaces, frequency of activity participation, types of activity participated in, and duration of participation in order to identify transport disadvantage. A combined measure using six individual indices were developed based on the six dimensional indicators of activity spaces, by taking into account the relativity of the measures for weekdays, weekends, and for a week. Factor analyses were conducted to derive weights of these indices to form the PI measure. Multivariate analysis using general linear models of the different indicators/indices identified new patterns of transport disadvantage. The research found that: indicator based measures and index based measures are complement each other; interactions between different factors generated new patterns of transport disadvantage; and that these patterns vary in space and time. The analysis also indicates that the transport needs of different disadvantaged groups are varied.

Participation index : improved measure of transport related social exclusion?

Although transport related social exclusion has been identified through zonal accessibility measures in the recent past, the debate has shifted from zonal to individual level measures. One way to identify disadvantaged individuals is to measure their size of participation in society (activity spaces). After reviewing existing literature, this paper has found two approaches to measure the activity spaces. One approach is based on the time-geographic potential path area (PPA) concept. The size of the PPA has largely been used as an indicator to the size of potential activity spaces and consequently individual accessibility. The limitations of the PPA concept have been identified in this paper and it is argued cannot be applied as a measure of social exclusion. The other approach is based on individuals’ actual travel activity participation called actual activity spaces. The size of actual activity spaces possesses a good potential measure of social exclusion. However, the indicators to measure the size of actual activity spaces are multidimensional representing the different aspects of social exclusion. The development of a unified approach has therefore been found to be important. This paper has developed a participation index (PI) using the different dimensions of actual activity spaces encountered. A framework has also been developed to operationalise the concept in GIS. The framework, on the one hand, will visualize individuals’ actual travel behaviour in real geographic space; on the other hand, it will calculate the size of their participation in society.

Diesel engine condition monitoring and simulated diesel knock

This paper discusses diesel engine condition monitoring (CM) using acoustic emissions (AE)as well as some of the commonly encountered diesel engine problems. Also discussed are some of the underlying combustion related faults and the methods used in past studies to simulate diesel engine faults. The initial test involved an experimental simulation of two common combustion related diesel engine faults, namely diesel knock and misfire. These simulated faults represent the first step towards a comprehensive investigation and analysis into the characteristics of acoustic emission signals arising from combustion related diesel engine faults. Data corresponding to different engine running conditions was captured using in-cylinder pressure, vibration and acoustic emission transducers along with both crank angle encoder and top-dead centre (TDC) signals. Using these signals, it was possible to characterise the effect of different combustion conditions and hence, various diesel engine in-cylinder pressure profiles.

Development of a diagnostic tool for condition monitoring of rotating machinery

This paper presents an overview of the CRC for Infrastructure and Engineering Asset Management (CIEAM)’s rotating machine health monitoring project and the status of the research progress. The project focuses on the development of a comprehensive diagnostic tool for condition monitoring and systematic analysis of rotating machinery. Particularly attention focuses on the machine health monitoring of diesel engines, compressors and pumps by using acoustic emission and vibration-based monitoring techniques. The paper also provides a brief summary of the work done by the three main research collaborating partners in the project, namely, Queensland University of Technology (QUT), Curtin University of Technology (CUT) and the University of Western Australia (UWA). Preliminary test and analysis results from this work are also reported in the paper

Buyer's waiver of a special condition

A recent decision of the Queensland Supreme Court (McMurdo J) raises matters of interest for practitioners undertaking conveyancing. Woodward v Nagel [2003] QSC 100 was delivered on 11 April 2003.

Drug diffusion from polymeric delivery devices : a problem with two moving boundaries

An existing model for solvent penetration and drug release from a spherically-shaped polymeric drug delivery device is revisited. The model has two moving boundaries, one that describes the interface between the glassy and rubbery states of polymer, and another that defines the interface between the polymer ball and the pool of solvent. The model is extended so that the nonlinear diffusion coefficient of drug explicitly depends on the concentration of solvent, and the resulting equations are solved numerically using a front-fixing transformation together with a finite difference spatial discretisation and the method of lines. We present evidence that our scheme is much more accurate than a previous scheme. Asymptotic results in the small-time limit are presented, which show how the use of a kinetic law as a boundary condition on the innermost moving boundary dictates qualitative behaviour, the scalings being very different to the similar moving boundary problem that arises from modelling the melting of an ice ball. The implication is that the model considered here exhibits what is referred to as ``non-Fickian'' or Case II diffusion which, together with the initially constant rate of drug release, has certain appeal from a pharmaceutical perspective.

Multi-step ahead direct prediction for the machine condition prognosis using regression trees and neuro-fuzzy systems

This paper presents an approach to predict the operating conditions of machine based on classification and regression trees (CART) and adaptive neuro-fuzzy inference system (ANFIS) in association with direct prediction strategy for multi-step ahead prediction of time series techniques. In this study, the number of available observations and the number of predicted steps are initially determined by using false nearest neighbor method and auto mutual information technique, respectively. These values are subsequently utilized as inputs for prediction models to forecast the future values of the machines’ operating conditions. The performance of the proposed approach is then evaluated by using real trending data of low methane compressor. A comparative study of the predicted results obtained from CART and ANFIS models is also carried out to appraise the prediction capability of these models. The results show that the ANFIS prediction model can track the change in machine conditions and has the potential for using as a tool to machine fault prognosis.

A test vehicle for compliance with resilience requirements in index-based e-health systems

Increasingly, national and international governments have a strong mandate to develop national e-health systems to enable delivery of much-needed healthcare services. Research is, therefore, needed into appropriate security and reliance structures for the development of health information systems which must be compliant with governmental and alike obligations. The protection of e-health information security is critical to the successful implementation of any e-health initiative. To address this, this paper proposes a security architecture for index-based e-health environments, according to the broad outline of Australia’s National E-health Strategy and National E-health Transition Authority (NEHTA)’s Connectivity Architecture. This proposal, however, could be equally applied to any distributed, index-based health information system involving referencing to disparate health information systems. The practicality of the proposed security architecture is supported through an experimental demonstration. This successful prototype completion demonstrates the comprehensibility of the proposed architecture, and the clarity and feasibility of system specifications, in enabling ready development of such a system. This test vehicle has also indicated a number of parameters that need to be considered in any national indexed-based e-health system design with reasonable levels of system security. This paper has identified the need for evaluation of the levels of education, training, and expertise required to create such a system.

Children with special health care needs : social and learning competence in the early years

The number of children with special health care needs surviving infancy and attending school has been increasing. Due to their health status, these children may be at risk of low social-emotional and learning competencies (e.g., Lightfoot, Mukherjee, & Sloper, 2000; Zehnder, Landolt, Prchal, & Vollrath, 2006). Early social problems have been linked to low levels of academic achievement (Ladd, 2005), inappropriate behaviours at school (Shiu, 2001) and strained teacher-child relationships (Blumberg, Carle, O‘Connor, Moore, & Lippmann, 2008). Early learning difficulties have been associated with mental health problems (Maughan, Rowe, Loeber, & Stouthamer-Loeber, 2003), increased behaviour issues (Arnold, 1997), delinquency (Loeber & Dishion, 1983) and later academic failure (Epstein, 2008). Considering the importance of these areas, the limited research on special health care needs in social-emotional and learning domains is a factor driving this research. The purpose of the current research is to investigate social-emotional and learning competence in the early years for Australian children who have special health care needs. The data which informed this thesis was from Growing up in Australia: The Longitudinal Study of Australian Children. This is a national, longitudinal study being conducted by the Commonwealth Department of Families, Housing, Community Services and Indigenous Affairs. The study has a national representative sample, with data collection occurring biennially, in 2004 (Wave 1), 2006 (Wave 2) and 2008 (Wave 3). Growing up in Australia uses a cross-sequential research design involving two cohorts, an Infant Cohort (0-1 at recruitment) and a Kindergarten Cohort (4-5 at recruitment). This study uses the Kindergarten Cohort, for which there were 4,983 children at recruitment. Three studies were conducted to address the objectives of this thesis. Study 1 used Wave 1 data to identify and describe Australian children with special health care needs. Children who identified as having special health care needs through the special health care needs screener were selected. From this, descriptive analyses were run. The results indicate that boys, children with low birth weight and children from families with low levels of maternal education are likely to be in the population of children with special health care needs. Further, these children are likely to be using prescription medications, have poor general health and are likely to have specific condition diagnoses. Study 2 used Wave 1 data to examine differences between children with special health care needs and their peers in social-emotional competence and learning competence prior to school. Children identified by the special health care needs screener were chosen for the case group (n = 650). A matched case control group of peers (n = 650), matched on sex, cultural and linguistic diversity, family socioeconomic position and age, were the comparison group. Social-emotional competence was measured through Social/Emotional Domain scores taken from the Growing up in Australia Outcome Index, with learning competence measured through Learning Domain scores. Results suggest statistically significant differences in scores between the two groups. Children with special health care needs have lower levels of social-emotional and learning competence prior to school compared to their peers. Study 3 used Wave 1 and Wave 2 data to examine the relationship between special health care needs at Wave 1 and social-emotional competence and learning competence at Wave 2, as children started school. The sample for this study consisted of children in the Kindergarten Cohort who had teacher data at Wave 2. Results from multiple regression models indicate that special health care needs prior to school (Wave 1) significantly predicts social-emotional competence and learning competence in the early years of school (Wave 2). These results indicate that having special health care needs prior to school is a risk factor for the social-emotional and learning domains in the early years of school. The results from these studies give valuable insight into Australian children with special health care needs and their social-emotional and learning competence in the early years. The Australia population of children with special health care needs were primarily male children, from families with low maternal education, were likely to be of poor health and taking prescription medications. It was found that children with special health care needs were likely to have lower social-emotional competence and learning competence prior to school compared to their peers. Results indicate that special health care needs prior to school were predictive of lower social-emotional and learning competencies in the early years of school. More research is required into this unique population and their competencies over time. However, the current research provides valuable insight into an under researched 'at risk' population.

A pilot study assessing the feasibility of a home-based progressive resistance exercise program and trend toward healing rates for patients with venous leg ulcers

Venous leg ulceration is a serious condition affecting 1 – 3% of the population. Decline in the function of the calf muscle pump is correlated with venous ulceration. Many previous studies have reported an improvement in the function of the calf muscle pump, endurance of the calf muscle and increased range of ankle motion after structured exercise programs. However, there is a paucity of published research that assesses if these improvements result in an improvement in the healing rates of venous ulcers. The primary purpose of this pilot study was to establish the feasibility of a homebased progressive resistance exercise program and examine if there was any clinical significance or trend toward healing. The secondary aims were to examine the benefit of a home-based progressive resistance exercise program on calf muscle pump function and physical parameters. The methodology used was a randomised controlled trial where eleven participants were randomised into an intervention (n = 6) or control group (n = 5). Participants who were randomised to receive a 12-week home-based progressive resistance exercise program were instructed through weekly face-to-face consultations during their wound clinic appointment by the author. Control group participants received standard wound care and compression therapy. Changes in ulcer parameters were measured fortnightly at the clinic (number healed at 12 weeks, percentage change in area and pressure ulcer score healing score). An air plethysmography test was performed at baseline and following the 12 weeks of training to determine changes in calf muscle pump function. Functional measures included maximum number of heel raises (endurance), maximal isometric plantar flexion (strength) and range of ankle motion (ROAM); these tests were conducted at baseline, week 6 and week 12. The sample for the study was drawn from the Princess Alexandra Hospital in Brisbane, Australia. Participants with venous leg ulceration who met the inclusion criteria were recruited. The participants were screened via duplex scanning and ankle brachial pressure index (ABPI) to ensure they did not have any arterial complications. Participants were excluded if there was evidence of cellulitis. Demographic data were obtained from each participant and details regarding medical history, quality of life and geriatric depression scores were collected at baseline. Both the intervention and control group were required to complete a weekly exercise diary to monitor activity levels between groups. To test for the effect of the intervention over time, a repeated measures analysis of variance was conducted on the major outcome variables. Group (intervention versus control) was the between subject factor and time (baseline, week 6, week 12) was the within subject or repeated measures factor. Due to the small sample size, further tests were conducted to check the assumptions of the statistical test to be used. The results showed that Mauchly.s Test, the Sphericity assumptions of repeated measures for ANOVA were met. Further tests of homogeneity of variance assumptions also confirmed that this assumption was met. Data analysis was conducted using the software package SPSS for Windows Release 17.0. The pilot study proved feasible with all of the intervention (n=6) participants continuing with the resistance program for the 12 week duration and no deleterious effects noted. Clinical significance was observed in the intervention group with a 32% greater change in ulcer size (p= 0.26) than the control group, and a 10% (p = 0.74) greater difference between the numbers healed compared to the control group. Statistical significance was observed for the ejection fraction (p = 0.05), residual volume fraction (p = 0.04) and ROAM (p = 0.01), which all improved significantly in the intervention group over time. These results are encouraging, nevertheless, further investigations seem warranted to examine the effect exercise has on the healing rates of venous leg ulcers, with a multistudy site, larger sample size and longer follow up period.