A regulatory on-board mass monitoring application for heavy vehicles in Australia

This paper reports on the development of specifications for an on-board mass monitoring (OBM) application for regulatory requirements in Australia. An earlier paper reported on feasibility study and pilot testing program prior to the specification development [1]. Learnings from the pilot were used to refine this testing process and a full scale testing program was conducted from July to October 2008. The results from the full scale test and evidentiary implications are presented in this report. The draft specification for an evidentiary on-board mass monitoring application is currently under development.

Application of acoustic emission technology in monitoring structure integrity of bridges

Bridges are an important part of a nation’s infrastructure and reliable monitoring methods are necessary to ensure their safety and efficiency. Most bridges in use today were built decades ago and are now subjected to changes in load patterns that can cause localized distress, which can result in bridge failure if not corrected. Early detection of damage helps in prolonging lives of bridges and preventing catastrophic failures. This paper briefly reviews the various technologies currently used in health monitoring of bridge structures and in particular discusses the application and challenges of acoustic emission (AE) technology. Some of the results from laboratory experiments on a bridge model are also presented. The main objectives of these experiments are source localisation and assessment. The findings of the study can be expected to enhance the knowledge of acoustic emission process and thereby aid in the development of an effective bridge structure diagnostics system.

Moving tele-monitoring and tele-treatment from promise to practice : a business model approach for a chronic lower back pain application

The availability of new information and communication technologies creates opportunities for new, mobile tele-health services. While many promising tele-health projects deliver working R&D prototypes, they often do not result in actual deployment. We aim to identify critical issues than can increase our understanding and enhance the viability of the mobile tele-health services beyond the R&D phase by developing a business model. The present study describes the systematic development and evaluation of a service-oriented business model for tele-monitoring and -treatment of chronic lower back pain patients based on a mobile technology prototype. We address challenges of multi-sector collaboration and disruptive innovation.

Aerial image analysis using spiking neural networks with application to power line corridor monitoring

Trees, shrubs and other vegetation are of continued importance to the environment and our daily life. They provide shade around our roads and houses, offer a habitat for birds and wildlife, and absorb air pollutants. However, vegetation touching power lines is a risk to public safety and the environment, and one of the main causes of power supply problems. Vegetation management, which includes tree trimming and vegetation control, is a significant cost component of the maintenance of electrical infrastructure. For example, Ergon Energy, the Australia’s largest geographic footprint energy distributor, currently spends over $80 million a year inspecting and managing vegetation that encroach on power line assets. Currently, most vegetation management programs for distribution systems are calendar-based ground patrol. However, calendar-based inspection by linesman is labour-intensive, time consuming and expensive. It also results in some zones being trimmed more frequently than needed and others not cut often enough. Moreover, it’s seldom practicable to measure all the plants around power line corridors by field methods. Remote sensing data captured from airborne sensors has great potential in assisting vegetation management in power line corridors. This thesis presented a comprehensive study on using spiking neural networks in a specific image analysis application: power line corridor monitoring. Theoretically, the thesis focuses on a biologically inspired spiking cortical model: pulse coupled neural network (PCNN). The original PCNN model was simplified in order to better analyze the pulse dynamics and control the performance. Some new and effective algorithms were developed based on the proposed spiking cortical model for object detection, image segmentation and invariant feature extraction. The developed algorithms were evaluated in a number of experiments using real image data collected from our flight trails. The experimental results demonstrated the effectiveness and advantages of spiking neural networks in image processing tasks. Operationally, the knowledge gained from this research project offers a good reference to our industry partner (i.e. Ergon Energy) and other energy utilities who wants to improve their vegetation management activities. The novel approaches described in this thesis showed the potential of using the cutting edge sensor technologies and intelligent computing techniques in improve power line corridor monitoring. The lessons learnt from this project are also expected to increase the confidence of energy companies to move from traditional vegetation management strategy to a more automated, accurate and cost-effective solution using aerial remote sensing techniques.

Acoustic emission condition monitoring : an application for wind turbine fault detection

Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE) technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.

The synthesis and application of novel profluorescent nitroxides as probes for polymer degradation

This PhD project has expanded the knowledge in the area of profluorescent nitroxides with regard to the synthesis and characterisations of novel profluorescent nitroxide probes as well as physical characterisation of the probe molecules in various polymer/physical environments. The synthesis of the first example of an azaphenalene-based fused aromatic nitroxide TMAO, [1,1,3,3-tetramethyl-2,3-dihydro-2-azaphenalen-2-yloxyl, was described. This novel nitroxide possesses some of the structural rigidity of the isoindoline class of nitroxides, as well as some properties akin to TEMPO nitroxides. Additionally, the integral aromatic ring imparts fluorescence that is switched on by radical scavenging reactions of the nitroxide, which makes it a sensitive probe for polymer degradation. In addition to the parent TMAO, 5 other azaphenalene derivatives were successfully synthesised. This new class of nitroxide was expected to have interesting redox properties when the structure was investigated by high-level ab initio molecular orbitals theory. This was expected to have implications with biological relevance as the calculated redox potentials for the azaphenalene ring class would make them potent antioxidant compounds. The redox potentials of 25 cyclic nitroxides from four different structural classes (pyrroline, piperidine, isoindoline and azaphenalene) were determined by cyclic voltammetry in acetonitrile. It was shown that potentials related to the one electron processes of the nitroxide were influenced by the type of ring system, ring substituents or groups surrounding the moiety. Favourable comparisons were found between theoretical and experimental potentials for pyrroline, piperidine and isoindoline ring classes. Substitution of these ring classes, were correctly calculated to have a small yet predictable effect on the potentials. The redox potentials of the azaphenalene ring class were underestimated by the calculations in all cases by at least a factor of two. This is believed to be due to another process influencing the redox potentials of the azaphenalene ring class which is not taken into account by the theoretical model. It was also possible to demonstrate the use of both azaphenalene and isoindoline nitroxides as additives for monitoring radical mediated damage that occurs in polypropylene as well as in more commercially relevant polyester resins. Polymer sample doped with nitroxide were exposed to both thermo-and photo-oxidative conditions with all nitroxides showing a protective effect. It was found that isoindoline nitroxides were able to indicate radical formation in polypropylene aged at elevated temperatures via fluorescence build-up. The azaphenalene nitroxide TMAO showed no such build-up of fluorescence. This was believed to be due to the more labile bond between the nitroxide and macromolecule and the protection may occur through a classical Denisov cycle, as is expected for commercially available HAS units. Finally, A new profluorescent dinitroxide, BTMIOA (9,10-bis(1,1,3,3- tetramethylisoindolin-2-yloxyl-5-yl)anthracene), was synthesised and shown to be a powerful probe for detecting changes during the initial stages of thermo-oxidative degradation of polypropylene. This probe, which contains a 9,10-diphenylanthracene core linked to two nitroxides, possesses strongly suppressed fluorescence due to quenching by the two nitroxide groups. This molecule also showed the greatest protective effect on thermo-oxidativly aged polypropylene. Most importantly, BTMIOA was found to be a valuable tool for imaging and mapping free-radical generation in polypropylene using fluorescence microscopy.

Review of vibration-based damage detection and condition assessment of bridge structures using structural health monitoring

As a part of vital infrastructure and transportation networks, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs always make the infrastructure owners difficult to undertake. Structural health monitoring (SHM) is set to assess condition and foresee probable failures of designated bridge(s), so as to monitor the structural health of the bridges. The SHM systems proposed recently are incorporated with Vibration-Based Damage Detection (VBDD) techniques, Statistical Methods and Signal processing techniques and have been regarded as efficient and economical ways to solve the problem. The recent development in damage detection and condition assessment techniques based on VBDD and statistical methods are reviewed. The VBDD methods based on changes in natural frequencies, curvature/strain modes, modal strain energy (MSE) dynamic flexibility, artificial neural networks (ANN) before and after damage and other signal processing methods like Wavelet techniques and empirical mode decomposition (EMD) / Hilbert spectrum methods are discussed here.

Sustainable subdivisions – ventilation monitoring

Australia’s current pattern of residential development is typified by relatively low-density subdivision of land and highlights the necessity for development to be more sustainable to avoid unnecessary demand on natural resources and to prevent environmental degradation and to safeguard the environment for future generations. What role can climatically appropriate sub-division design play in decreasing the use of energy required to cool premises by maximising access to natural ventilation? How can this design be achieved?

Listening to nature : techniques for large-scale monitoring of ecosystems using acoustics

Climate change and human activity are subjecting the environment to unprecedented rates of change. Monitoring these changes is an immense task that demands new levels of automated monitoring and analysis. We propose the use of acoustics as a proxy for the time consuming auditing of fauna, especially for determining the presence/absence of species. Acoustic monitoring is deceptively simple; seemingly all that is required is a sound recorder. However there are many major challenges if acoustics are to be used for large scale monitoring of ecosystems. Key issues are scalability and automation. This paper discusses our approach to this important research problem. Our work is being undertaken in collaboration with ecologists interested both in identifying particular species and in general ecosystem health.

Listening to nature : acoustic monitoring of the environment

The requirement to monitor the rapid pace of environmental change due to global warming and to human development is producing large volumes of data but placing much stress on the capacity of ecologists to store, analyse and visualise that data. To date, much of the data has been provided by low level sensors monitoring soil moisture, dissolved nutrients, light intensity, gas composition and the like. However, a significant part of an ecologist’s work is to obtain information about species diversity, distributions and relationships. This task typically requires the physical presence of an ecologist in the field, listening and watching for species of interest. It is an extremely difficult task to automate because of the higher order difficulties in bandwidth, data management and intelligent analysis if one wishes to emulate the highly trained eyes and ears of an ecologist. This paper is concerned with just one part of the bigger challenge of environmental monitoring – the acquisition and analysis of acoustic recordings of the environment. Our intention is to provide helpful tools to ecologists – tools that apply information technologies and computational technologies to all aspects of the acoustic environment. The on-line system which we are building in conjunction with ecologists offers an integrated approach to recording, data management and analysis. The ecologists we work with have different requirements and therefore we have adopted the toolbox approach, that is, we offer a number of different web services that can be concatenated according to need. In particular, one group of ecologists is concerned with identifying the presence or absence of species and their distributions in time and space. Another group, motivated by legislative requirements for measuring habitat condition, are interested in summary indices of environmental health. In both case, the key issues are scalability and automation.