Failure analysis of engineering systems with preventive maintenance and failure interactions

Optimal operation and maintenance of engineering systems heavily rely on the accurate prediction of their failures. Most engineering systems, especially mechanical systems, are susceptible to failure interactions. These failure interactions can be estimated for repairable engineering systems when determining optimal maintenance strategies for these systems. An extended Split System Approach is developed in this paper. The technique is based on the Split System Approach and a model for interactive failures. The approach was applied to simulated data. The results indicate that failure interactions will increase the hazard of newly repaired components. The intervals of preventive maintenance actions of a system with failure interactions, will become shorter compared with scenarios where failure interactions do not exist.

Delay distribution based robust H∞ control of networked control systems with uncertainties

Network induced delay in networked control systems (NCS) is inherently non-uniformly distributed and behaves with multifractal nature. However, such network characteristics have not been well considered in NCS analysis and synthesis. Making use of the information of the statistical distribution of NCS network induced delay, a delay distribution based stochastic model is adopted to link Quality-of-Control and network Quality-of-Service for NCS with uncertainties. From this model together with a tighter bounding technology for cross terms, H∞ NCS analysis is carried out with significantly improved stability results. Furthermore, a memoryless H∞ controller is designed to stabilize the NCS and to achieve the prescribed disturbance attenuation level. Numerical examples are given to demonstrate the effectiveness of the proposed method.

Robust real time multi-layer foreground segmentation

Many surveillance applications (object tracking, abandoned object detection) rely on detecting changes in a scene. Foreground segmentation is an effective way to extract the foreground from the scene, but these techniques cannot discriminate between objects that have temporarily stopped and those that are moving. We propose a series of modifications to an existing foreground segmentation system\cite{Butler2003} so that the foreground is further segmented into two or more layers. This yields an active layer of objects currently in motion and a passive layer of objects that have temporarily ceased motion which can itself be decomposed into multiple static layers. We also propose a variable threshold to cope with variable illumination, a feedback mechanism that allows an external process (i.e. surveillance system) to alter the motion detectors state, and a lighting compensation process and a shadow detector to reduce errors caused by lighting inconsistencies. The technique is demonstrated using outdoor surveillance footage, and is shown to be able to effectively deal with real world lighting conditions and overlapping objects.

Multi-spectral fusion for surveillance systems

Surveillance systems such as object tracking and abandoned object detection systems typically rely on a single modality of colour video for their input. These systems work well in controlled conditions but often fail when low lighting, shadowing, smoke, dust or unstable backgrounds are present, or when the objects of interest are a similar colour to the background. Thermal images are not affected by lighting changes or shadowing, and are not overtly affected by smoke, dust or unstable backgrounds. However, thermal images lack colour information which makes distinguishing between different people or objects of interest within the same scene difficult. ----- By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using either modality individually. We evaluate four approaches for fusing visual and thermal images for use in a person tracking system (two early fusion methods, one mid fusion and one late fusion method), in order to determine the most appropriate method for fusing multiple modalities. We also evaluate two of these approaches for use in abandoned object detection, and propose an abandoned object detection routine that utilises multiple modalities. To aid in the tracking and fusion of the modalities we propose a modified condensation filter that can dynamically change the particle count and features used according to the needs of the system. ----- We compare tracking and abandoned object detection performance for the proposed fusion schemes and the visual and thermal domains on their own. Testing is conducted using the OTCBVS database to evaluate object tracking, and data captured in-house to evaluate the abandoned object detection. Our results show that significant improvement can be achieved, and that a middle fusion scheme is most effective.

Scene invariant crowd counting for real-time surveillance

Automated crowd counting allows excessive crowding to be detected immediately, without the need for constant human surveillance. Current crowd counting systems are location specific, and for these systems to function properly they must be trained on a large amount of data specific to the target location. As such, configuring multiple systems to use is a tedious and time consuming exercise. We propose a scene invariant crowd counting system which can easily be deployed at a different location to where it was trained. This is achieved using a global scaling factor to relate crowd sizes from one scene to another. We demonstrate that a crowd counting system trained at one viewpoint can achieve a correct classification rate of 90% at a different viewpoint.

Extending life-cycle costing (LCC) analysis for sustainability considerations in road infrastructure projects

Sustainable development is about making societal investments. These investments should be in synchronization with the natural environment, trends of social development, as well as organisational and local economies over a long time span. Traditionally in the eyes of clients, project development will need to produce the required profit margins, with some degrees of consideration for other impacts. This is being changed as all citizens of our society are becoming more aware of concepts and challenges such as the climate change, greenhouse footprints, and social dimensions of sustainability, and will in turn demand answers to these issues in built facilities. A large number of R&D projects have focused on the technical advancement and environmental assessment of products and built facilities. It is equally important address the cost/benefit issue, as developers in the world would not want to loose money by investing in built assets. For infrastructure projects, due to its significant cost of development and lengthy delivery time, presenting the full money story of going green is of vital importance. Traditional views of life-cycle costing tend to focus on the pure economics of a construction project. Sustainability concepts are not broadly integrated with the current LCCA in the construction sector. To rectify this problem, this paper reports on the progress to date of developing and extending contemporary LCCA models in the evaluation of road infrastructure sustainability. The suggested new model development is based on sustainability indicators identified through previous research, and incorporating industry verified cost elements of sustainability measures. The on-going project aims to design and a working model for sustainability life-cycle costing analysis for this type of infrastructure projects.

Inertial motion capture and live performance (with a focus on dance)

3D Motion capture is a fast evolving field and recent inertial technology may expand the artistic possibilities for its use in live performance. Inertial motion capture has three attributes that make it suitable for use with live performance; it is portable, easy to use and can operate in real-time. Using four projects, this paper discusses the suitability of inertial motion capture to live performance with a particular emphasis on dance. Dance is an artistic application of human movement and motion capture is the means to record human movement as digital data. As such, dance is clearly a field in which the use of real-time motion capture is likely to become more common, particularly as projected visual effects including real-time video are already often used in dance performances. Understandably, animation generated in real-time using motion capture is not as extensive or as clean as the highly mediated animation used in movies and games, but the quality is still impressive and the ‘liveness’ of the animation has compensating features that offer new ways of communicating with an audience.

Labelled silhouettes for human pose estimation

This paper proposes a new method of using foreground silhouette images for human pose estimation. Labels are introduced to the silhouette images, providing an extra layer of information that can be used in the model fitting process. The pixels in the silhouettes are labelled according to the corresponding body part in the model of the current fit, with the labels propagated into the silhouette of the next frame to be used in the fitting for the next frame. Both single and multi-view implementations are detailed, with results showing performance improvements over only using standard unlabelled silhouettes.

An analysis of cyclists crashes to identify ITS-based intervention

Cycling provides a number of health and environmental benefits. However, cyclists are more likely to suffer serious injury or be killed in traffic accidents than car drivers and the estimated cost of crashes in Australia is $1.25AU billion per year. Current interventions to reduce bicycle crashes include compulsory helmet use, media campaigns, and the provision of cycling lanes, as well as road user education and training. It is difficult to assess the effectiveness of current interventions as there is no accurate measure of cyclist exposure in South East Queensland (SEQ). This paper analyses cyclist crash characteristics in Queensland with the view to identifying appropriate Intelligent Transport Systems (ITS) based intervention to reduce cyclist injury and death. The inappropriateness of some ITS interventions to improve cyclist safety is highlighted and a set of ITS interventions are identified, based on Queensland crash data 2002-2006.

Azo-linked corner porphyrin systems: synthesis, crystal structures and spectroscopic investigation

1,2-Bis[10,15-di(3,5-di-tert-butyl)phenylporphyrinatonickel(II)-5-yl]diazene was synthesised via copper catalysed coupling of aminated nickel(II) 5,10-diarylporphyrin (“corner porphyrin”) and its X-ray crystal structure was determined. Two different crystals yielded different structures, one with the free meso positions in a trans-like orientation, and the other with a cis-like disposition. The free meso positions of the obtained dimer have been further functionalised while the synthesis of a zinc analogue has so far been unsuccessful. The X-ray crystal structure of the dinitro derivative of the dinickel(II) azoporphyrin was determined, and the structure showed a cis-like disposition of the nitro groups.

Strategic information systems research : an archival analysis

The Journal of Strategic Information Systems (JSIS) has been an international outlet for Information Systems research that focuses on strategic issues since 1991. This paper reports on an analysis of the research published in JSIS to date. The paper presents a preliminary classification system for research topics related to Strategic Information Systems into which all 316 JSIS research papers as at end 2009 are classified. Discussion on changing emphases in topics over time is provided, in the context of the editorial philosophy of the journal. The paper seeks to stimulate discussion on future directions for research in Strategic Information Systems.

Mining patterns and factors contributing to crash severity on road curves

Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

Changes in accountancy costs for Tasmanian SMEs implementing computerised accounting systems

There have been powerful incentives for Tasmanian Small and Medium-sized Enterprises (SMEs) to adopt information technology to enable them to remain competitive and to comply with legislative regulations. This research study was undertaken to establish whether SMEs implementing computerised accounting systems have a subsequent change in their external accountancy fees. The research study employed a quantitative methodology using survey questionnaires. The study found that in less than 3% of cases SMEs reported a decrease in accountancy fees, in almost 45% of cases the organisation actually experienced a slight to substantial fee increase while 52% reported no change in accountancy fees.