Maintenance strategy optimization using a continuous-state partially observable semi-Markov decision process

Due to the limitation of current condition monitoring technologies, the estimates of asset health states may contain some uncertainties. A maintenance strategy ignoring this uncertainty of asset health state can cause additional costs or downtime. The partially observable Markov decision process (POMDP) is a commonly used approach to derive optimal maintenance strategies when asset health inspections are imperfect. However, existing applications of the POMDP to maintenance decision-making largely adopt the discrete time and state assumptions. The discrete-time assumption requires the health state transitions and maintenance activities only happen at discrete epochs, which cannot model the failure time accurately and is not cost-effective. The discrete health state assumption, on the other hand, may not be elaborate enough to improve the effectiveness of maintenance. To address these limitations, this paper proposes a continuous state partially observable semi-Markov decision process (POSMDP). An algorithm that combines the Monte Carlo-based density projection method and the policy iteration is developed to solve the POSMDP. Different types of maintenance activities (i.e., inspections, replacement, and imperfect maintenance) are considered in this paper. The next maintenance action and the corresponding waiting durations are optimized jointly to minimize the long-run expected cost per unit time and availability. The result of simulation studies shows that the proposed maintenance optimization approach is more cost-effective than maintenance strategies derived by another two approximate methods, when regular inspection intervals are adopted. The simulation study also shows that the maintenance cost can be further reduced by developing maintenance strategies with state-dependent maintenance intervals using the POSMDP. In addition, during the simulation studies the proposed POSMDP shows the ability to adopt a cost-effective strategy structure when multiple types of maintenance activities are involved.

Bond–slip models for double strap joints strengthened by CFRP

This paper presents the results of a series of tension tests on CFRP bonded steel plate double strap joints. The main aim of this research is to provide detailed understanding of bond characteristics using experimental and numerical analysis of strengthened double strap joints under tension. A parametric study has been performed by numerical modelling with the variables of CFRP bond lengths, adhesive maximum strain and adhesive layer thicknesses. Finally, bond-slip models are proposed for three different types of adhesives within the range of the parametric study.

Learning the Kernel Matrix with Semi-Definite Programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space -- classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semi-definite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -- using the labelled part of the data one can learn an embedding also for the unlabelled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method to learn the 2-norm soft margin parameter in support vector machines, solving another important open problem. Finally, the novel approach presented in the paper is supported by positive empirical results.

Performance of square and inclined insulated rail joints based on field strain measurements

Insulated rail joints (IRJs) possess lower bending stiffness across the gap containing insulating endpost and hence are subjected to wheel impact. IRJs are either square cut or inclined cut to the longitudinal axis of the rails in a vertical plane. It is generally claimed that the inclined cut IRJs outperformed the square cut IRJs; however, there is a paucity of literature with regard to the relative structural merits of these two designs. This article presents comparative studies of the structural response of these two IRJs to the passage of wheels based on continuously acquired field data from joints strain-gauged closer to the source of impact. Strain signatures are presented in time, frequency, and avelet domains and the peak vertical and shear strains are systematically employed to examine the relative structural merits of the two IRJs subjected to similar real-life loading. It is shown that the inclined IRJs resist the wheel load with higher peak shear strains and lower peak vertical strains than that of the square IRJs.

Relationship between physical activity and stiff or painful joints in mid-aged women and older women: a 3-year prospective study

This prospective study examined the association between physical activity and the incidence of self-reported stiff or painful joints (SPJ) among mid-age women and older women over a 3-year period. Data were collected from cohorts of mid-age (48–55 years at Time 1; n = 4,780) and older women (72–79 years at Time 1; n = 3,970) who completed mailed surveys 3 years apart for the Australian Longitudinal Study on Women's Health. Physical activity was measured with the Active Australia questions and categorized based on metabolic equivalent value minutes per week: none (<40 MET.min/week); very low (40 to <300 MET.min/week); low (300 to <600 MET.min/week); moderate (600 to <1,200 MET.min/week); and high (1,200+ MET.min/week). Cohort-specific logistic regression models were used to examine the association between physical activity at Time 1 and SPJ 'sometimes or often' and separately 'often' at Time 2. Respondents reporting SPJ 'sometimes or often' at Time 1 were excluded from analysis. In univariate models, the odds of reporting SPJ 'sometimes or often' were lower for mid-age respondents reporting low (odds ratio (OR) = 0.77, 95% confidence interval (CI) = 0.63–0.94), moderate (OR = 0.82, 95% CI = 0.68–0.99), and high (OR = 0.75, 95% CI = 0.62–0.90) physical activity levels and for older respondents who were moderately (OR = 0.80, 95% CI = 0.65–0.98) or highly active (OR = 0.83, 95% CI = 0.69–0.99) than for those who were sedentary. After adjustment for confounders, these associations were no longer statistically significant. The odds of reporting SPJ 'often' were lower for mid-age respondents who were moderately active (OR = 0.71, 95% CI = 0.52–0.97) than for sedentary respondents in univariate but not adjusted models. Older women in the low (OR = 0.72, 95% CI = 0.55–0.96), moderate (OR = 0.54, 95% CI = 0.39–0.76), and high (OR = 0.61, 95% CI = 0.46–0.82) physical activity categories had lower odds of reporting SPJ 'often' at Time 2 than their sedentary counterparts, even after adjustment for confounders. These results are the first to show a dose–response relationship between physical activity and arthritis symptoms in older women. They suggest that advice for older women not currently experiencing SPJ should routinely include counseling on the importance of physical activity for preventing the onset of these symptoms.

Bond characteristics between CFRP and steel plates in double strap joints

This paper describes a series of double strap shear tests loaded in tension to investigate the bond between CFRP sheets and steel plates. Both normal modulus (240 GPa) and high modulus (640 GPa) CFRPs were used in the test program. Strain gauges were mounted to capture the strain distribution along the CFRP length. Different failure modes were observed for joints with normal modulus CFRP and those with high modulus CFRP. The strain distribution along the CFRP length was found to be similar for the two cases. A shorter effective bond length was obtained for joints with high modulus CFRP whereas larger ultimate load carrying capacity can be achieved for joints with normal modulus CFRP when the bond length is long enough. The Hart-Smith Model was modified to predict the effective bond length and ultimate load carrying capacity of joints between the normal modulus CFRP and steel plates. The Multilayer Distribution Model developed by the authors was modified to predict the load carrying capacity of joints between the high modulus CFRP and steel plates. The predicted values agreed well with experimental ones.

SwarmPS: Rapid, semi-automated single particle selection software

Single particle analysis (SPA) coupled with high-resolution electron cryo-microscopy is emerging as a powerful technique for the structure determination of membrane protein complexes and soluble macromolecular assemblies. Current estimates suggest that ∼104–105 particle projections are required to attain a 3 Å resolution 3D reconstruction (symmetry dependent). Selecting this number of molecular projections differing in size, shape and symmetry is a rate-limiting step for the automation of 3D image reconstruction. Here, we present SwarmPS, a feature rich GUI based software package to manage large scale, semi-automated particle picking projects. The software provides cross-correlation and edge-detection algorithms. Algorithm-specific parameters are transparently and automatically determined through user interaction with the image, rather than by trial and error. Other features include multiple image handling (∼102), local and global particle selection options, interactive image freezing, automatic particle centering, and full manual override to correct false positives and negatives. SwarmPS is user friendly, flexible, extensible, fast, and capable of exporting boxed out projection images, or particle coordinates, compatible with downstream image processing suites.

Hypothetical model of hydrophilic lubrication in synovial joints

This paper presents a new insight into the mechanism of biolubrication of articulating mammalian joints that includes the function of surface-active phospholipids (SAPLs). SAPLs can be adsorbed on surface of cartilage membranes as a hydrophobic monolayer (H-phobic-M Madel or Hills' Model) or as a newly proposed hydrophilic bilayer (H-philic-B Model). With respect to the synovial joint's frictionless work, three processes are identified namely: monolayer/bilayer phospholipids binding to cartilage with lubricin interaction; influence of induced-pressure on interaction of hyaluronan with phospholipids; and biolubrication arising from two gliding articular hydrophilic surfaces acting as reverse micelle. Lubricin is considered to play critical role as a supplier of phospholipids, which overlay the articular surface of articular cartilage. Hyaluronic acid is considered to play a critical mediating role in the interaction between the hydrophilic part of phospholipids, the articular surface and water (hydration) in facilitating the lubrication process. Tivo models of frictionless lubrication processes, namely hydrophobic (H-phobic-M Model) and our conceptual hydrophilic (H-philic-B Model), are compared. © Institution of Engineers Australia, 2008.

Leveraging Web 2.0 data for scalable semi-supervised learning of domain-specific sentiment lexicons

Since manually constructing domain-specific sentiment lexicons is extremely time consuming and it may not even be feasible for domains where linguistic expertise is not available. Research on the automatic construction of domain-specific sentiment lexicons has become a hot topic in recent years. The main contribution of this paper is the illustration of a novel semi-supervised learning method which exploits both term-to-term and document-to-term relations hidden in a corpus for the construction of domain specific sentiment lexicons. More specifically, the proposed two-pass pseudo labeling method combines shallow linguistic parsing and corpusbase statistical learning to make domain-specific sentiment extraction scalable with respect to the sheer volume of opinionated documents archived on the Internet these days. Another novelty of the proposed method is that it can utilize the readily available user-contributed labels of opinionated documents (e.g., the user ratings of product reviews) to bootstrap the performance of sentiment lexicon construction. Our experiments show that the proposed method can generate high quality domain-specific sentiment lexicons as directly assessed by human experts. Moreover, the system generated domain-specific sentiment lexicons can improve polarity prediction tasks at the document level by 2:18% when compared to other well-known baseline methods. Our research opens the door to the development of practical and scalable methods for domain-specific sentiment analysis.

A semi-local method for iterative depth-map refinement

We present an iterative hierarchical algorithm for multi-view stereo. The algorithm attempts to utilise as much contextual information as is available to compute highly accurate and robust depth maps. There are three novel aspects to the approach: 1) firstly we incrementally improve the depth fidelity as the algorithm progresses through the image pyramid; 2) secondly we show how to incorporate visual hull information (when available) to constrain depth searches; and 3) we show how to simultaneously enforce the consistency of the depth-map by continual comparison with neighbouring depth-maps. We show that this approach produces highly accurate depth-maps and, since it is essentially a local method, is both extremely fast and simple to implement.

Molecular structure of the phosphate mineral brazilianite NaAl3(PO4)2(OH)4 : a semi precious jewel

The phosphate mineral brazilianite NaAl3(PO4)2(OH)4 is a semi precious jewel. There are almost no minerals apart from brazilianite which are used in jewellery. Vibrational spectroscopy was used to characterize the mol. structure of brazilianite. Brazilianite is composed of chains of edge-sharing Al-O octahedra linked by P-O tetrahedra, with Na located in cavities of the framework. An intense sharp Raman band at 1019 cm-1 is attributed to the PO43- sym. stretching mode. Raman bands at 973 and 988 cm-1 are assigned to the stretching vibrations of the HOPO33- units. The IR spectra compliment the Raman spectra but show greater complexity. Multiple Raman bands are obsd. in the PO43- and HOPO33- bending region. This observation implies that both phosphate and hydrogen phosphate units are involved in the structure. Raman OH stretching vibrations are found at 3249, 3417 and 3472 cm-1. These peaks show that the OH units are not equiv. in the brazilianite structure. Vibrational spectroscopy is useful for increasing the knowledge of the mol. structure of brazilianite.