Practical determination of cane wagon derailment forces for the Australian sugar industry

Derailments are a significant cost to the Australian sugar industry with damage to rail infrastructure and rolling stock in excess of $2 M per annum. Many factors can contribute to cane rail derailments. The more prevalent factors are discussed. Derailment statistics on likely causes for cane rail derailments are presented with the case of empty wagons on the main line being the highest contributor to business cost. Historically, the lateral to vertical wheel load ratio, termed the derailment ratio, has been used to indicate the derailment probability of rolling stock. When the derailment ratio reaches the Nadal limit of 0.81 for cane rail operations, there is a high probability that a derailment will occur. Contributing factors for derailments include the operating forces, the geometric variables of the rolling stock and the geometric deviations of the railway track. These combined, have the capacity to affect the risk of derailment for a cane rail transport operating system. The derailment type that is responsible for creating the most damage to assets and creating mill stops is the flange climb derailment, as these derailments usually occur at speed with a full rake of empty wagons. The typical forces that contribute to the flange climb derailment case for cane rail operations are analysed and a practical derailment model is developed to enable operators to better appreciate the most significant contributing factors to this type of derailment. The paper aims to: (a) improve awareness of the significance of physical operating parameters so that these principles can be included in locomotive driver training and (b) improve awareness of track and wagon variables related to the risk of derailment so that maintainers of the rail system can allocate funds for maintenance more effectively.

A data mining approach for fault diagnosis: An application of anomaly detection algorithm

Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.

Structural, physiological and molecular characterisation of the Australian native resurrection grass Tripogon loliiformis (F.Meull) C.E.Hubb during dehydration and rehydration

There is an urgent need to develop crops that can withstand future climates. Results from this thesis demonstrated that a native Australian resurrection grass exhibits structural, physiological and metabolic strategies to tolerate drying. These strategies may be utilized for the generation of stress tolerant crops.

Characterisation of head-hardened rail steel in terms of cyclic plasticity response and microstructure for improved material modelling

Stress- and strain-controlled tests of heat treated high-strength rail steel (Australian Standard AS1085.1) have been performed in order to improve the characterisation of the said material׳s ratcheting and fatigue wear behaviour. The hardness of the rail head material has also been studied and it has been found that hardness reduces considerably below four-millimetres from the rail top surface. Historically, researchers have used test coupons with circular cross-sections to conduct cyclic load tests. Such test coupons, typically five-millimetres in gauge diameter and ten‐millimetres in grip diameter, are usually taken from the rail head sample. When there is considerable variation of material properties over the cross-section it becomes likely that localised properties of the rail material will be missed. In another case from the literature, disks 47 mm in diameter for a twin-disk rolling contact test machine were obtained directly from the rail sample and used to validate ratcheting and rolling contact fatigue wear models. The question arises: How accurate are such tests, especially when large material property gradients exist? In this research paper, the effects of rail sampling location on the ratcheting behaviour of AS1085.1 rail steel were investigated using rectangular-shaped specimens obtained at four different depths to observe their respective cyclic plasticity behaviour. The microstructural features of the test coupons were also analysed, especially the pearlite inter-lamellar spacing which showed strong correlation with both hardness and cyclic plasticity behaviour of the material. This work ultimately provides new data and testing methodology to aid the selection of valid parameters for material constitutive models to better understand rail surface ratcheting and wear.