The user query based learning system for lifetime prediction of metallic components

Real-World Data Mining Applications generally do not end up with the creation of the models. The use of the model is the final purpose especially in prediction tasks. The problem arises when the model is built based on much more information than that the user can provide in using the model. As a result, the performance of model reduces drastically due to many missing attributes values. This paper develops a new learning system framework, called as User Query Based Learning System (UQBLS), for building data mining models best suitable for users use. We demonstrate its deployment in a real-world application of the lifetime prediction of metallic components in buildings

Towards continuous surveillance of fruit flies using sensor networks and machine vision

In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of our sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. Our experiments showed that the designed trap and sensor platform is capable to capture quality fly images, the invasive flies can be successfully detected and the average precision of the Queensland fruit fly recognition is 80% from our experiment.

Assessing the energy efficiency of gear oils via the FZG test machine

Energy efficient lubricants are becoming increasingly popular. This is due to a global increase in environmental awareness combined with the potential of reducing operating costs. A new test method of evaluating the energy efficiency of gear oils has been described in this report. The method involves measuring the power required by an FZG test rig to run while using a particular test lubricant. For each oil that was being evaluated, the rig was run for 10 minutes at a load stage of 10. Six extreme pressure (EP) industrial gear oils of mineral base were tested. The difference in power requirements between the best and the worst performing oils was 2.77 and 3.24 kW, respectively. This equates to a 14.6% reduction in power, a significant amount if considered in relation to a high powered industrial machine. The oils of superior performance were noticed to run at reduced temperatures. They were also more expensive than the other products of lesser performance.

Integrated Diagnosis and Prognosis Model for High Pressure LNG Pump

In condition-based maintenance (CBM), effective diagnostics and prognostics are essential tools for maintenance engineers to identify imminent fault and to predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedules production if necessary. This paper presents a technique for accurate assessment of the remnant life of machines based on historical failure knowledge embedded in the closed loop diagnostic and prognostic system. The technique uses the Support Vector Machine (SVM) classifier for both fault diagnosis and evaluation of health stages of machine degradation. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for multi-class fault diagnosis. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Scheduling trains as a blocking parallel-machine job shop scheduling problem

In this paper, the train scheduling problem is modelled as a blocking parallel-machine job shop scheduling (BPMJSS) problem. In the model, trains, single-track sections and multiple-track sections, respectively, are synonymous with jobs, single machines and parallel machines, and an operation is regarded as the movement/traversal of a train across a section. Due to the lack of buffer space, the real-life case should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold the train until next section on the routing becomes available. Based on literature review and our analysis, it is very hard to find a feasible complete schedule directly for BPMJSS problems. Firstly, a parallel-machine job-shop-scheduling (PMJSS) problem is solved by an improved shifting bottleneck procedure (SBP) algorithm without considering blocking conditions. Inspired by the proposed SBP algorithm, feasibility satisfaction procedure (FSP) algorithm is developed to solve and analyse the BPMJSS problem, by an alternative graph model that is an extension of the classical disjunctive graph models. The proposed algorithms have been implemented and validated using real-world data from Queensland Rail. Sensitivity analysis has been applied by considering train length, upgrading track sections, increasing train speed and changing bottleneck sections. The outcomes show that the proposed methodology would be a very useful tool for the real-life train scheduling problems

Characterisation of soluble components and PAH in PM10 atmospheric particulate matter in Brisbane

Fours sets of PM10 samples were collected in three sites in SEQ from December 2002 to August 2004. Three of these sets of samples were collected by QLD EPA as a part of their regular air monitoring program at Woolloongabba, Rocklea and Eagle Farm. Half of the samples were used in this study for the analysis of water-soluble ions, which are Na+, K+, Mg2+, Ca2+, NH4 +, Cl-, NO3 -, SO4 2-, F-, Br-, NO2 -, PO4 -3 and the other half was retained by QLD EPA. The fourth set of samples was collected at Rocklea, specifically for this study. A quarter of the samples obtained from this set of samples were used to analyse water-soluble ions; a quarter of the sample was used to analyse Pb, Cu, Al, Fe, Mn and Zn; and the rests were used to analyse US EPA 16 priority PAHs. The water-soluble ions were extracted ultrasonically with water and the major watersoluble anions as well as NH4 + were analysed using IC. Na+, K+, Mg2+, Ca2+ Pb, Cu, Al, Fe, Mn and Zn were analysed using ICP-AES while PAHs were extracted by acetonitrile and analysed using HPLC. Of the analysed water-soluble ions, Cl-, NO3 -, SO4 2-, Na+, K+, Mg2+ and Ca2+ were high in concentration and determined in all the samples. F-, Br-, NO2 -, PO4 -3 and NH4 + ions were lower in concentration and determined only in some samples. Na+ and Cl- were high in all samples indicating the importance of a marine source. Principal Component Analysis (PCA) was used to examine the temporal variations of the water-soluble ions at the three sites. The results indicated that there was no major difference between the three sites. However, comparing the average concentrations of ions and Cl-/Na+ it was concluded that Woolloongabba had more marine influence than the other sites. Al, Fe and Zn were detected in all samples. Al and Fe were high in all samples indicating the significance of a source of crustal matter. Cu, Mn and Pb were in low concentrations and were determined only in some samples. The lower Pb concentrations observed in the study than in previous studies indicate that the phasing-out of leaded petrol had an appreciable impact on Pb levels in SEQ. This study reports for the first time, simultaneous data on the water-soluble, metal ion and PAH levels of PM10 aerosols in Brisbane, and provides information on the most likely sources of these chemical species. Such information can be used alongside those that already exist to formulate PM10 pollution reduction strategies for SEQ in order to protect the community from the adverse effects of PM pollution.

Evaluating the Java Virtual Machine as a Target for Languages Other Than Java

The portability and runtime safety of programs which are executed on the Java Virtual Machine (JVM) makes the JVM an attractive target for compilers of languages other than Java. Unfortunately, the JVM was designed with language Java in mind, and lacks many of the primitives required for a straighforward implementation of other languages. Here, we discuss how the JVM may be used to implement other object-oriented languages. As a practical example of the possibilities, we report on a comprehensive case study. The open source Gardens Point Component Pascal compiler compiles the entire Component Pascal language, a dialect of Oberon-2, to JVM bytecodes. This compiler achieves runtime efficiencies which are comparable to native-code implementations of procedural languages.

Implementing languages other than Java on the Java Virtual Machine

The portability and runtime safety of programs which are executed on the Java Virtual Machine (JVM) makes the JVM an attractive target for compilers of languages other than Java. Unfortunately, the JVM was designed with language Java in mind, and lacks many of the primitives required for a straight forward implementation of other languages. Here, we discuss how the JVM may be used to implement other object oriented languages. As a practical example of the possibilities, we report on a comprehensive case study. The open source Gardens Point Component Pascal compiler compiles the entire Component Pascal language, a dialect of Oberon 2, to JVM bytecodes. This compiler achieves runtime efficiencies which are comparable to native code implementations of procedural languages.

Condition-based prognosis of machine health

Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

A study into the permeability and compressibility of Australian bagasse pulp

This is an experimental study into the permeability and compressibility properties of bagasse pulp pads. Three experimental rigs were custom-built for this project. The experimental work is complemented by modelling work. Both the steady-state and dynamic behaviour of pulp pads are evaluated in the experimental and modelling components of this project. Bagasse, the fibrous residue that remains after sugar is extracted from sugarcane, is normally burnt in Australia to generate steam and electricity for the sugar factory. A study into bagasse pulp was motivated by the possibility of making highly value-added pulp products from bagasse for the financial benefit of sugarcane millers and growers. The bagasse pulp and paper industry is a multibillion dollar industry (1). Bagasse pulp could replace eucalypt pulp which is more widely used in the local production of paper products. An opportunity exists for replacing the large quantity of mainly generic paper products imported to Australia. This includes 949,000 tonnes of generic photocopier papers (2). The use of bagasse pulp for paper manufacture is the main application area of interest for this study. Bagasse contains a large quantity of short parenchyma cells called ‘pith’. Around 30% of the shortest fibres are removed from bagasse prior to pulping. Despite the ‘depithing’ operations in conventional bagasse pulp mills, a large amount of pith remains in the pulp. Amongst Australian paper producers there is a perception that the high quantity of short fibres in bagasse pulp leads to poor filtration behaviour at the wet-end of a paper machine. Bagasse pulp’s poor filtration behaviour reduces paper production rates and consequently revenue when compared to paper production using locally made eucalypt pulp. Pulp filtration can be characterised by two interacting factors; permeability and compressibility. Surprisingly, there has previously been very little rigorous investigation into neither bagasse pulp permeability nor compressibility. Only freeness testing of bagasse pulp has been published in the open literature. As a result, this study has focussed on a detailed investigation of the filtration properties of bagasse pulp pads. As part of this investigation, this study investigated three options for improving the permeability and compressibility properties of Australian bagasse pulp pads. Two options for further pre-treating depithed bagasse prior to pulping were considered. Firstly, bagasse was fractionated based on size. Two bagasse fractions were produced, ‘coarse’ and ‘medium’ bagasse fractions. Secondly, bagasse was collected after being processed on two types of juice extraction technology, i.e. from a sugar mill and from a sugar diffuser. Finally one method of post-treating the bagasse pulp was investigated. The effects of chemical additives, which are known to improve freeness, were also assessed for their effect on pulp pad permeability and compressibility. Pre-treated Australian bagasse pulp samples were compared with several benchmark pulp samples. A sample of commonly used kraft Eucalyptus globulus pulp was obtained. A sample of depithed Argentinean bagasse, which is used for commercial paper production, was also obtained. A sample of Australian bagasse which was depithed as per typical factory operations was also produced for benchmarking purposes. The steady-state pulp pad permeability and compressibility parameters were determined experimentally using two purpose-built experimental rigs. In reality, steady-state conditions do not exist on a paper machine. The permeability changes as the sheet compresses over time. Hence, a dynamic model was developed which uses the experimentally determined steady-state permeability and compressibility parameters as inputs. The filtration model was developed with a view to designing pulp processing equipment that is suitable specifically for bagasse pulp. The predicted results of the dynamic model were compared to experimental data. The effectiveness of a polymeric and microparticle chemical additives for improving the retention of short fibres and increasing the drainage rate of a bagasse pulp slurry was determined in a third purpose-built rig; a modified Dynamic Drainage Jar (DDJ). These chemical additives were then used in the making of a pulp pad, and their effect on the steady-state and dynamic permeability and compressibility of bagasse pulp pads was determined. The most important finding from this investigation was that Australian bagasse pulp was produced with higher permeability than eucalypt pulp, despite a higher overall content of short fibres. It is thought this research outcome could enable Australian paper producers to switch from eucalypt pulp to bagasse pulp without sacrificing paper machine productivity. It is thought that two factors contributed to the high permeability of the bagasse pulp pad. Firstly, thicker cell walls of the bagasse pulp fibres resulted in high fibre stiffness. Secondly, the bagasse pulp had a large proportion of fibres longer than 1.3 mm. These attributes helped to reinforce the pulp pad matrix. The steady-state permeability and compressibility parameters for the eucalypt pulp were consistent with those found by previous workers. It was also found that Australian pulp derived from the ‘coarse’ bagasse fraction had higher steady-state permeability than the ‘medium’ fraction. However, there was no difference between bagasse pulp originating from a diffuser or a mill. The bagasse pre-treatment options investigated in this study were not found to affect the steady-state compressibility parameters of a pulp pad. The dynamic filtration model was found to give predictions that were in good agreement with experimental data for pads made from samples of pretreated bagasse pulp, provided at least some pith was removed prior to pulping. Applying vacuum to a pulp slurry in the modified DDJ dramatically reduced the drainage time. At any level of vacuum, bagasse pulp benefitted from chemical additives as quantified by reduced drainage time and increased retention of short fibres. Using the modified DDJ, it was observed that under specific conditions, a benchmark depithed bagasse pulp drained more rapidly than the ‘coarse’ bagasse pulp. In steady-state permeability and compressibility experiments, the addition of chemical additives improved the pad permeability and compressibility of a benchmark bagasse pulp with a high quantity of short fibres. Importantly, this effect was not observed for the ‘coarse’ bagasse pulp. However, dynamic filtration experiments showed that there was also a small observable improvement in filtration for the ‘medium’ bagasse pulp. The mechanism of bagasse pulp pad consolidation appears to be by fibre realignment. Chemical additives assist to lubricate the consolidation process. This study was complemented by pulp physical and chemical property testing and a microscopy study. In addition to its high pulp pad permeability, ‘coarse’ bagasse pulp often (but not always) had superior physical properties than a benchmark depithed bagasse pulp.

Best basis-based intelligent machine fault diagnosis

The wavelet packet transform decomposes a signal into a set of bases for time–frequency analysis. This decomposition creates an opportunity for implementing distributed data mining where features are extracted from different wavelet packet bases and served as feature vectors for applications. This paper presents a novel approach for integrated machine fault diagnosis based on localised wavelet packet bases of vibration signals. The best basis is firstly determined according to its classification capability. Data mining is then applied to extract features and local decisions are drawn using Bayesian inference. A final conclusion is reached using a weighted average method in data fusion. A case study on rolling element bearing diagnosis shows that this approach can greatly improve the accuracy ofdiagno sis.