Reliability evaluations of railway power supplies by fault-tree analysis

High reliability of railway power systems is one of the essential criteria to ensure quality and cost-effectiveness of railway services. Evaluation of reliability at system level is essential for not only scheduling maintenance activities, but also identifying reliability-critical components. Various methods to compute reliability on individual components or regularly structured systems have been developed and proven to be effective. However, they are not adequate for evaluating complicated systems with numerous interconnected components, such as railway power systems, and locating the reliability critical components. Fault tree analysis (FTA) integrates the reliability of individual components into the overall system reliability through quantitative evaluation and identifies the critical components by minimum cut sets and sensitivity analysis. The paper presents the reliability evaluation of railway power systems by FTA and investigates the impact of maintenance activities on overall reliability. The applicability of the proposed methods is illustrated by case studies in AC railways.

Applications on fault tree analysis in railway power supply systems

Fault tree analysis (FTA) is presented to model the reliability of a railway traction power system in this paper. First, the construction of fault tree is introduced to integrate components in traction power systems into a fault tree; then the binary decision diagram (BDD) method is used to evaluate fault trees qualitatively and quantitatively. The components contributing to the reliability of overall system are identified with their relative importance through sensitivity analysis. Finally, an AC traction power system is evaluated by the proposed methods.

Notification of data breaches under the continuous disclosure regime

Consumer personal information is now a valuable commodity for most corporations. Concomitant with increased value is the expansion of new legal obligations to protect personal information. Mandatory data breach notification laws are an important new development in this regard. Such laws require a corporation that has suffered a data breach, which involves personal information, such as a computer hacking incident, to notify those persons who may have been affected by the breach. Regulators may also need to be notified. Australia currently does not have a mandatory data breach notification law but this may be about to change. The Australian Law Reform Commission has suggested that a data breach notification scheme be implemented through the Privacy Act 1988 (Cth). However, the notification of data breaches may already be required under the continuous disclosure regime stipulated by the Corporations Act 2001 (Cth) and the Australian Stock Exchange (ASX) Listing Rules. Accordingly, this article examines whether the notification of data breaches is a statutory requirement of the existing continuous disclosure regime and whether the ASX should therefore be notified of such incidents.

Directional earth fault relay operation in mutually coupled multiple circuit distribution lines

Many of the power utilities around the world experienced spurious tripping of directional earth fault relays in their mesh distribution networks due to induced circulating currents. This circulating current is zero sequence and induced in the healthy circuit due to the zero sequence current flow resulting from a ground fault of a parallel circuit. This paper quantitatively discusses the effects of mutual coupling on earth fault protection of distribution systems. An actual spurious tripping event is analyzed to support the theory and to present options for improved resilience to spurious tripping.

Sustainability and mandatory disclosure in Queensland : an assessment of the impact on home buyer patterns

Sustainability Declarations were introduced by the Queensland State Government on 1 January 2010 as a compulsory measure for all dwelling sales. The purpose of this policy decision was to improve the relevance of sustainability in the home ownership decision making process. This paper assesses the initial impact of this initiative over its first year in operation. In partnership with the Real Estate Institute of Queensland, real estate agents and salespeople in Queensland were surveyed to determine what impact the Sustainability Declaration has had on home buyer decision making. The level of compliance by the real estate industry was also reviewed. These preliminary findings indicate a high level of compliance from the real estate industry, however results confirm that sustainability is yet to become a criterion of relevance to the majority of home buyers in Queensland. The Sustainability Declarations are a first step in raising awareness in home owners of the importance of sustainability in housing. Further monitoring of this impact will be carried out over time.

Beware statutory disclosure obligations

Great care is needed to ensure strict compliance with statutory disclosure obligations in conveyancing. The types of issues that may arise are well illustrated by the facts before the court in APM Property 3 Pty Ltd v Blondeau [2009] QSC 326, decision of Mullins J.

Property Agents and Motor Dealers Act (Qld) : disclosure, cooling-off and marketeers

The Property Agents and Motor Dealers Act 2000 commenced on 1 July 2001. Significant changes have now been made to the Act by the Property Agents and Motor Dealers Amendment Act 2001 (“the amending Act”). The amending Act contains two distinct parts. First, ss 11-19 of the amending Act provide for increased disclosure obligations on real estate agents, property developers and lawyers together with an extension of the 5 business day cooling-off period imposed by the original Act to all residential property (other than contracts formed on a sale by auction). These provisions are expected to commence on 29 October 2001. The remaining provisions of the amending Act provide for increased jurisdiction and powers to the Property Agents and Motor Dealers Tribunal (“the Tribunal”) enabling the Tribunal to deal with claims against marketeers. These provisions commenced on the date of assent (21 September 2001).

Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference

This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART–ANFIS model has potential for fault diagnosis of induction motors.

The level and quality of Value-at-Risk disclosure by commercial banks

In this paper we study both the level of Value-at-Risk (VaR) disclosure and the accuracy of the disclosed VaR figures for a sample of US and international commercial banks. To measure the level of VaR disclosures, we develop a VaR Disclosure Index that captures many different facets of market risk disclosure. Using panel data over the period 1996–2005, we find an overall upward trend in the quantity of information released to the public. We also find that Historical Simulation is by far the most popular VaR method. We assess the accuracy of VaR figures by studying the number of VaR exceedances and whether actual daily VaRs contain information about the volatility of subsequent trading revenues. Unlike the level of VaR disclosure, the quality of VaR disclosure shows no sign of improvement over time. We find that VaR computed using Historical Simulation contains very little information about future volatility.

Disclosure, conservatism and the cost of equity capital : a review of the foundation literature

In this review piece, we survey the literature on the cost of equity capital implications of corporate disclosure and conservative accounting policy choice decisions with the principle objective of providing insights into the design and methodological issues, which underlie the empirical investigations. We begin with a review of the analytical studies most typically cited in the empirical research as providing a theoretical foundation. We then turn to consider literature that offers insights into the selection of proxies for each of our points of interest, cost of equity capital, disclosure quality and accounting conservatism. As a final step, we review selected empirical studies to illustrate the relevant evidence found within the literature. Based on our review, we interpret the literature as providing the researcher with only limited direct guidance on the appropriate choice of measure for each of the constructs of interest. Further, we view the literature as raising questions about both the interpretation of empirical findings in the face of measurement concerns and the suitability of certain theoretical arguments to the research setting. Overall, perhaps the message which is most clear is that one of the most controversial and fundamental issues underlying the literature is the issue of the diversifiability or nondiversifiability of information effects.

Fault diagnostics and supervised testing : How fault diagnostic tools can be proactive?

The topic of fault detection and diagnostics (FDD) is studied from the perspective of proactive testing. Unlike most research focus in the diagnosis area in which system outputs are analyzed for diagnosis purposes, in this paper the focus is on the other side of the problem: manipulating system inputs for better diagnosis reasoning. In other words, the question of how diagnostic mechanisms can direct system inputs for better diagnosis analysis is addressed here. It is shown how the problem can be formulated as decision making problem coupled with a Bayesian Network based diagnostic mechanism. The developed mechanism is applied to the problem of supervised testing in HVAC systems.

Application of machine learning in fault diagnostics of mechanical systems

A diagnostic method based on Bayesian Networks (probabilistic graphical models) is presented. Unlike conventional diagnostic approaches, in this method instead of focusing on system residuals at one or a few operating points, diagnosis is done by analyzing system behavior patterns over a window of operation. It is shown how this approach can loosen the dependency of diagnostic methods on precise system modeling while maintaining the desired characteristics of fault detection and diagnosis (FDD) tools (fault isolation, robustness, adaptability, and scalability) at a satisfactory level. As an example, the method is applied to fault diagnosis in HVAC systems, an area with considerable modeling and sensor network constraints.