Application of anomaly technique in wind turbine bearing fault detection

Bearing faults are the most common cause of wind turbine failures. Unavailability and maintenance cost of wind turbines are becoming critically important, with their fast growing in electric networks. Early fault detection can reduce outage time and costs. This paper proposes Anomaly Detection (AD) machine learning algorithms for fault diagnosis of wind turbine bearings. The application of this method on a real data set was conducted and is presented in this paper. For validation and comparison purposes, a set of baseline results are produced using the popular one-class SVM methods to examine the ability of the proposed technique in detecting incipient faults.

Double star chopper cell converter for battery electric vehicles with inter-module SoC balancing and fault tolerant control

A modularized battery system with Double Star Chopper Cell (DSCC) based modular multilevel converter is proposed for a battery operated electric vehicle (EV). A design concept for the modularized battery micro-packs for DSCC is described. Multidimensional pulse width modulation (MD-PWM) with integrated inter-module SoC balancing and fault tolerant control is proposed and explained. The DSCC can be operated either as an inverter to drive the EV motor or as a synchronous rectifier connected to external three phase power supply equipment for charging the battery micro-packs. The methods of operation as inverter and synchronous rectifier with integrated inter-module SoC balancing and fault tolerant control are discussed. The proposed system operation as inverter and synchronous rectifier are verified through simulations and the results are presented.

Fault detection of wind turbine drivetrain utilizing power-speed characteristics

Wind energy, being the fastest growing renewable energy source in the present world, requires a large number of wind turbines to transform wind energy into electricity. One factor driving the cost of this energy is the reliable operation of these turbines. Therefore, it is a growing requirement within the wind farm community, to monitor the operation of the wind turbines on a continuous basis so that a possible fault can be detected ahead of time. As the wind turbine operates in an environment of constantly changing wind speed, it is a challenging task to design a fault detection technique which can accommodate the stochastic operational behavior of the turbines. Addressing this issue, this paper proposes a novel fault detection criterion which is robust against operational uncertainty, as well as having the ability to quantify severity level specifically of the drivetrain abnormality within an operating wind turbine. A benchmark model of wind turbine has been utilized to simulate drivetrain fault condition and effectiveness of the proposed technique has been tested accordingly. From the simulation result it can be concluded that the proposed criterion exhibits consistent performance for drivetrain faults for varying wind speed and has linear relationship with the fault severity level.

Reliable fault diagnosis for incipient low-speed bearings using fault feature analysis based on a binary bat algorithm

In this paper, we propose a highly reliable fault diagnosis scheme for incipient low-speed rolling element bearing failures. The scheme consists of fault feature calculation, discriminative fault feature analysis, and fault classification. The proposed approach first computes wavelet-based fault features, including the respective relative wavelet packet node energy and entropy, by applying a wavelet packet transform to an incoming acoustic emission signal. The most discriminative fault features are then filtered from the originally produced feature vector by using discriminative fault feature analysis based on a binary bat algorithm (BBA). Finally, the proposed approach employs one-against-all multiclass support vector machines to identify multiple low-speed rolling element bearing defects. This study compares the proposed BBA-based dimensionality reduction scheme with four other dimensionality reduction methodologies in terms of classification performance. Experimental results show that the proposed methodology is superior to other dimensionality reduction approaches, yielding an average classification accuracy of 94.9%, 95.8%, and 98.4% under bearing rotational speeds at 20 revolutions-per-minute (RPM), 80 RPM, and 140 RPM, respectively.

Online self-disclosure across cultures: A study of Facebook use in Saudi Arabia and Australia

This research aimed to gain a sophisticated understanding of self-disclosure on Facebook across two distinctive cultures, Saudi Arabia and Australia. This study utilised an explanatory sequential mixed methods design, consisting of a quantitative phase followed by a qualitative phase. Findings from both quantitative and qualitative data provide a broad understanding of the types of information that people self-disclose on Facebook, identifies factors that have a significant influence (either positive or negative) on such disclosure, and explains how it is affected by one's national culture.

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.

Insurance contract disclosure – an uncertain balance

This article canvasses recent case law adjudicating the uneasy disclosure balance between the interests of the insurer and the insured in the process of transacting an insurance contract. It examines also the consequences of non-disclosure and misrepresentation and whether the avowed legislative intent — that the liability of the insurer in respect of a claim is to be reduced to the amount that would place the insurer in the position it would have been had the non-disclosure or misrepresentation not occurred — is being achieved in practice. As there is no doubt as to who bears the onus of proof as to non-disclosure or misrepresentation it is surprising that insurers continue to flounder in this regard in relation to underwriting guidelines and adherence to them. The article reviews recent case law in this context and stresses that an insurer wishing to preserve its capacity to avoid liability on the basis that it would not have entered into a contract at all had the true situation been known to it must maintain detailed underwriting guidelines supported by consistent adherence to those guidelines. Recent case law also emphasises that the insurer must provide clear and cogent admissible evidence from appropriate personnel and officers of the company to discharge its onus.

Public disclosure of biological sequences in global patent practice

Biological sequences are an important part of global patenting, with unique challenges for their effective and equitable use in practice and in policy. Because their function can only be determined with computer-aided technology, the form in which sequences are disclosed matters greatly. Similarly, the scope of patent rights sought and granted requires computer readable data and tools for comparison. Critically, the primary data provided to the national patent offices and thence to the public, must be comprehensive, standardized, timely and meaningful. It is not yet. The proposed global Patent Sequence (PatSeq) Data platform can enable national and regional jurisdictions meet the desired standards.

Fault tolerant vessel stabiliser control system

A vessel stabilizer control system includes a sensor fault detection means which senses the availability of sensing signals from a gyrostabilizer precession motion sensor and a vessel roll motion sensor. The control system controls the action of a gyro-actuator which is mechanically coupled to a gyrostabilizer. The benefit of employing fault sensing of the sensors providing the process control variables is that the sensed number of available process control variables (or sensors) can be used to activate a tiered system of control modes. Each tiered control mode is designed to utilize the available process control variables to ensure safe and effective operation of the gyrostabilizer that is tolerant of sensor faults and loss of power supply. A control mode selector is provided for selecting the appropriate control mode based on the number of available process control variables.

Deriatives disclosure in corporate annual reports: bank analysts; perceptions of usefulness

Responding to mixed evidence on the decision-usefulness of annual report disclosures for derivative financial instruments to capital market participants, and concerns identified by practice, this paper examines usefulness in a direct study of user perceptions. Interviews with analysts from Australia’s four major banks reveal essential usefulness, limited by the disclosures’ failure to reflect companies’ actual use of derivatives throughout the period, and inability of users to understand companies’ off-balance sheet risk and risk management practices from information considered generic and boilerplate. The research complements and extends existing archival and survey research and provides new evidence suggesting low-cost ways for increasing usefulness. It supports the International Accounting Standards Board’s disclosure recommendations in its recent Discussion Paper: A Review of the Conceptual Framework for Financial Reporting, but, at the same time, highlights that for these proposed measures to be successful in relation to IFRS 7, they may need to address other issues. The research increases knowledge of the informational requirements of lenders, an important class of financial information user, and supports calls from practice for companies to improve their disclosure of material economic risks.

Corporate disclosure in relation to combating corporate bribery: A case study of two Chinese telecommunications companies

This paper investigates the association between global community concerns about bribery activities and anti-bribery disclosure practices by two Chinese telecommunication companies operating internationally, namely China Mobile and ZTE. Based on content analysis of annual reports and global news media articles over a period of 16 years from 1995-2010, the findings suggest that the changes in the level of disclosures by the two major Chinese telecommunications companies were closely associated with the level of international concerns over bribery practices within the Chinese telecommunications industry. This finding indicates that the companies adopt anti-bribery disclosure practices in order to minimise the gap of trust (Social capital) between companies themselves and global stakeholders. In this paper we argue that, for domestic companies in China, culturally constructed social capital, such as guanxi, creates a level of trust between managers and their stakeholders, which obviates the need for managers to disclose anti-bribery performance information. However, for companies operating internationally, as social capital is inadequate to bridge the gap of trust between managers and global stakeholders, managers use disclosures of anti-bribery performance information as a way to minimise such a gap.

Identifying statutory encumbrances for seller disclosure

The standard land contracts in Queensland require a seller of land to disclose to a buyer not only registered encumbrances, but also statutory encumbrances affecting the land. Whether a statute creates a statutory encumbrance over the title to the property is therefore a key question for a seller when completing a contract. This article examines relevant case law and provides some guidelines for when a statute creates a statutory encumbrance that should be disclosed to a buyer as a defect in title.

Demand for, and impediments to, the disclosure of information about climate change-related corporate governance practices

Based on a survey of climate change experts in different stakeholder groups and interviews with corporate climate change managers, this study provides insights into the gap between what information stakeholders expect, and what Australian corporations disclose. This paper focuses on annual reports and sustainability reports with specific reference to the disclosure of climate change-related corporate governance practices. The findings culminate in the governance practises. Interview results indicate that the low levels of disclosures made by Australian companies may be due to a number of factors. A lack of proactive stakeholder engagement and an apparent preoccupation with financial performance and advancing shareholders interest, coupled with a failure by managers to accept accountability, seems to go a long way to explaining low levels of disclosure.