Machine prognostics based on health state probability estimation

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

Global Lessons from Fitzgerald : From State and National to Global Integrity Systems

Tony Fitzgerald’s visionary leap was to see beyond localised, individual wrongdoing. He suggested remedies that were systemic, institutionalised, and directed at underlying structural problems that led to corruption. His report said ‘the problems with which this Inquiry is concerned are not merely associated with individuals, but are institutionalized and related to attitudes which have become entrenched’ (Fitzgerald Report 1989, 13). His response was to suggest an enmeshed system of measures to not only respond reactively to future corruption, but also to prevent its recurrence through improved integrity systems. In the two decades since that report the primary focus of corruption studies and anti-corruption activism has remained on corruption at the local level or within sovereign states. International activism was largely directed at co-ordinating national campaigns and to use international instruments to make these campaigns more effective domestically. This reflects the broader fact that, since the rise of the nation state, states have comprised the majority of the largest institutional actors and have been the most significant institution in the lives of most individuals. This made states the ‘main game in town’ for the ‘governance disciplines’ of ethics, law, political science and economics.

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.

'State' of play : Queensland report

A number of recent legislative amendments impact on property law practice in Queensland. Property Law (Mortgagor Protection) Amendment Act 2008 (Qld) Body Corporate and Community Management Amendment Act 2009 (Qld) Residential Tenancies and Rooming Accommodation Act 2008 (Qld) Sustainable Planning Act 2009 (Qld) Vegetation Management and Other Legislation Amendment Bill 2009 (Qld) Property Agents and Motor Dealers Act 2000 (Qld)

School system as axiological medium : the state's primary macro-proposing context and its expanding moral role in Australia

This paper analyses the Australian Values Education Program (VEP) within the framework of late-classical political economy. using analytical methods from systemic functional linguistics and critical discourse analysis, we demonstrate that the VEP is an unwitting restatement of the principles of ideology as developed by the likes of Destutt de Tracy and the Young Hegelians. We conclude that the sudden shock of globalisation and the post-national cultures this has entailed is in many ways similar to the shock of formal nationalism that emerged in the late-Seventeenth and early- Eighteenth centuries. The overall result of the VEP for the Australian school system is a massive procedural burden that is unlikely to produce the results at which the program is aimed.

Infinite-horizon policy-gradient estimation

Gradient-based approaches to direct policy search in reinforcement learning have received much recent attention as a means to solve problems of partial observability and to avoid some of the problems associated with policy degradation in value-function methods. In this paper we introduce GPOMDP, a simulation-based algorithm for generating a biased estimate of the gradient of the average reward in Partially Observable Markov Decision Processes (POMDPs) controlled by parameterized stochastic policies. A similar algorithm was proposed by Kimura, Yamamura, and Kobayashi (1995). The algorithm's chief advantages are that it requires storage of only twice the number of policy parameters, uses one free parameter β ∈ [0,1) (which has a natural interpretation in terms of bias-variance trade-off), and requires no knowledge of the underlying state. We prove convergence of GPOMDP, and show how the correct choice of the parameter β is related to the mixing time of the controlled POMDP. We briefly describe extensions of GPOMDP to controlled Markov chains, continuous state, observation and control spaces, multiple-agents, higher-order derivatives, and a version for training stochastic policies with internal states. In a companion paper (Baxter, Bartlett, & Weaver, 2001) we show how the gradient estimates generated by GPOMDP can be used in both a traditional stochastic gradient algorithm and a conjugate-gradient procedure to find local optima of the average reward. ©2001 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.

A Raman spectroscopic study of the different vanadate-groups in solid-state compounds, model case : mineral phases vésigniéite, BaCu3(VO4)2(OH)2, and volborthite, Cu3V2O7(OH)2•2H2O

Raman spectroscopy has been used to study vanadates in the solid state. The molecular structure of the vanadate minerals vésigniéite [BaCu3(VO4)2(OH)2] and volborthite [Cu3V2O7(OH)2·2H2O] have been studied by Raman spectroscopy and infrared spectroscopy. The spectra are related to the structure of the two minerals. The Raman spectrum of vésigniéite is characterized by two intense bands at 821 and 856 cm−1 assigned to ν1 (VO4)3− symmetric stretching modes. A series of infrared bands at 755, 787 and 899 cm−1 are assigned to the ν3 (VO4)3− antisymmetric stretching vibrational mode. Raman bands at 307 and 332 cm−1 and at 466 and 511 cm−1 are assigned to the ν2 and ν4 (VO4)3− bending modes. The Raman spectrum of volborthite is characterized by the strong band at 888 cm−1, assigned to the ν1 (VO3) symmetric stretching vibrations. Raman bands at 858 and 749 cm−1 are assigned to the ν3 (VO3) antisymmetric stretching vibrations; those at 814 cm−1 to the ν3 (VOV) antisymmetric vibrations; that at 508 cm−1 to the ν1 (VOV) symmetric stretching vibration and those at 442 and 476 cm−1 and 347 and 308 cm−1 to the ν4 (VO3) and ν2 (VO3) bending vibrations, respectively. The spectra of vésigniéite and volborthite are similar, especially in the region of skeletal vibrations, even though their crystal structures differ.

Unbiased estimation of the half-life to price index convergence among U.S. cities

Estimates of the half-life to convergence of prices across a panel of cities are subject to bias from three potential sources: inappropriate cross-sectional aggregation of heterogeneous coefficients, presence of lagged dependent variables in a model with individual fixed effects, and time aggregation of commodity prices. This paper finds no evidence of heterogeneity bias in annual CPI data for 17 U.S. cities from 1918 to 2006, but correcting for the “Nickell bias” and time aggregation bias produces a half-life of 7.5 years, shorter than estimates from previous studies.

Surveying the state of higher education in energy efficiency, in Australian engineering curriculum

This paper presents the method and results of a survey of 27 of the 33 Australian universities teaching engineering education in late 2007, undertaken by The Natural Edge Project (hosted by Griffith University and the Australian National University) and supported by the National Framework for Energy Efficiency. This survey aimed to ascertain the extent of energy efficiency (EE) education, and to identify preferred methods to assist in increasing the extent to which EE education is embedded in engineering curriculum. In this paper the context for the survey is supported by a summary of the key results from a variety of surveys undertaken over the last decade internationally. The paper concludes that EE education across universities and engineering disciplines in Australia is currently highly variable and ad hoc. Based on the results of the survey, this paper highlights a number of preferred options to support educators to embed sustainability within engineering programs, and future opportunities for monitoring EE, within the context of engineering education for sustainable development (EESD).