Application of machine learning technique in wind turbine fault diagnosis

In this study, a machine learning technique called anomaly detection is employed for wind turbine bearing fault detection. Basically, the anomaly detection algorithm is used to recognize the presence of unusual and potentially faulty data in a dataset, which contains two phases: a training phase and a testing phase. Two bearing datasets were used to validate the proposed technique, fault-seeded bearing from a test rig located at Case Western Reserve University to validate the accuracy of the anomaly detection method, and a test to failure data of bearings from the NSF I/UCR Center for Intelligent Maintenance Systems (IMS). The latter data set was used to compare anomaly detection with SVM, a previously well-known applied method, in rapidly finding the incipient faults.

Fault diagnosis of low speed bearing based on acoustic emission signal and multi-class relevance vector machine

This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

Sweet sorghum : opportunities for a new, renewable fuel and food industry in Australia

Sweet sorghum is receiving significant global interest as an agro-industrial crop because of its capacity to co-produce energy, food, and feed products in integrated biorefineries. This report assesses the opportunities to develop a sweet sorghum industry in Australia, reports on research demonstrating the production of energy, food, and feed products, and assesses the potential economic and sustainability benefits of sweet sorghum biorefineries in the Australian context.

Structured contract strategies for capital and operations expenditure projects in the oil and gas industry

This project was a step forward in developing a 'descriptive theory' of contracting in the oil and gas industry that reflects the operating environment in which the project manager operates. This study investigates the existing processes and methods used in establishing contracts which are very often prescriptive, and not always appropriate or optimal for a given situation. This study contributes to contracting effectiveness or optimal contracting in the oil and gas industry.

ACE research vignette 031: Startups lead the way in creating a nanobiotechnology industry

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. In this vignette, Dr Martin Bliemel and his research team explore the emergence and evolution of a new knowledge intensive industry, i.e. the nanobiotechnology industry.

ACE research briefing paper 007 : Ken Talbot - an entrepreneur's contribution to the growth of the Australian Mining Industry

Ken Talbot was one of Australian mining’s most successful entrepreneurs and rose to the top of his industry to become one of Australia’s wealthiest men. Although the nation’s resources industry is synonymous with global names such as Xstrata, BHP Billiton and Rio Tinto, Ken was an individual who made a big impact on the development and growth of the sector. This case study examines Ken’s achievements, his transition from employee to entrepreneur, and the qualities that enabled him to succeed at such a high level. In particular, it focuses on his Jellinbah and Coppabella mining developments that directly led to the creation of Macarthur Coal and the Talbot Group. By the time of his premature death in an African plane crash in 2010, Ken had amassed a fortune estimated at almost $1 billion and was aged just 59. The last publically available Talbot Group annual report for calendar year 2009 showed that the investment portfolio of the group returned 113 per cent that year. Even throughout the global financial crisis the portfolio made a positive return on investment of no less than 10 per cent. Ken’s sense of mateship and his tremendous people skills were keys to his success in the mining industry and the wider community. In addition to excelling in business, he is also remembered for his philanthropy and leaving 30 per cent of his estate to charity through the Talbot Family Foundation.

Self-labelling versus behavioural experience of workplace bullying : differences in sector- and industry-level prevalence and sources

This study reports on differences in self-labelling versus the behavioural experience of workplace bullying across sectors and industries for a sample of 6,406 Australian employees, as well as differences in source of workplace bullying. It was found that overall prevalence rates of workplace bullying were 2.9% (self-labelling method) and 4.0% (behavioural experience method). Exposure to workplace bullying was found to decrease with age. There was no significant difference between the public and private sectors, or among industries, in the prevalence of workplace bullying; however, two industries (Construction; Health and Community Services) showed a significantly higher rate of workplace bullying with the behavioural experience method compared to the self-labelling method. For the overall sample, the most prevalent source of workplace bullying was reported to be coworkers (49.1%), followed by clients (35.7%), and then supervisors (27.4%). Subordinates were rated as the source in 7.9% of cases. Closer examination of source as a function of sector and industry revealed a number of significant differences specific to sectors and industries, highlighting the need for tailored approaches for managing workplace bullying.

Professional development and social networks in digital content industry micro businesses

This study explores the professional development strategies of digital content professionals in Australian micro businesses. This thesis presents the argument that as these professionals are working in cutting edge creative fields where digital technology drives ongoing change, formal education experiences may be less important than for other professionals, and that specific types of online and face-to-face socially mediated informal learning strategies may be critical to currency. This thesis documents the findings of a broad survey of industry professionals' learning needs and development strategies, in conjunction with rich data from in-depth interviews and social network analyses.

Hidden innovation : Policy, industry and the creative sector

The term ‘two cultures’ was coined more than 50 years ago by scientist and novelist C.P. Snow to describe the divergence in the world views and methods of scientists and the creative sector. This divergence has meant that innovation systems and policies have focused for decades on science, engineering, technology and medicine and the industries that depend on them. The humanities, arts and social sciences have been bit players at best; their contributions hidden from research agendas, policy and program initiatives, and the public mind. But structural changes to advanced economies and societies have brought services industries and the creative sector to greater prominence as key contributors to innovation. Hidden Innovation peels back the veil, tracing the way innovation occurs through new forms of screen production enabled by social media platforms as well as in public broadcasting. It shows that creative workers are contributing fresh ideas across the economy and how creative cities debates need reframing. It traces how policies globally are beginning to catch up with the changing social and economic realities. In his new book, Cunningham argues that the innovation framework offers the best opportunity in decades to reassess and refresh the case for the public role of the humanities, particularly the media, cultural and communication studies disciplines.

Gender, sexuality, and rurality in the mining industry

Sexuality is a subject that has been, at best, marginal in the significant body of literature that has examined gender and mining in contemporary Western nations. This is despite the fact that academics have circled, if not almost bumped into the topic in closely related discussions of hegemonic masculinity and mining work, and of patriarchal familial relations and mining communities. This scholarship has documented what has been and remains women’s primary relationship to mining—that is, as a “mining wife.” How patriarchal relations are manifest in and emerge from this state of affairs has been critiqued with research on the gendered implications of housing arrangements in mining towns, the division of household labor, changing shift-work mining rosters, and the gendered consequences of strikes and mine closures (Williams 1981; Gibson 1992; Gibson-Graham 1996; Rhodes 2005; McDonald, Mayes, and Pini 2012). Despite the centrality of the heterosexual relationship—and indeed heteronormativity—to these discussions, scholars of gender and mining have had little to say on the subject of sexuality. In response to this lacuna, this chapter takes an exploratory lens to the subject of sexuality and the mining industry. We approach the task from the perspective that the mining industry is gendered as masculine. That is, definitions of mining mobilize around masculinized notions of physicality, technical competence with machinery, and strength, as well as emphasize the harshness and dirtiness of the work (Mayes and Pini 2010).

Transcript and metabolite profiling for the evaluation of tobacco tree and poplar as feedstock for the bio-based industry

The global demand for food, feed, energy and water poses extraordinary challenges for future generations. It is evident that robust platforms for the exploration of renewable resources are necessary to overcome these challenges. Within the multinational framework MultiBioPro we are developing biorefinery pipelines to maximize the use of plant biomass. More specifically, we use poplar and tobacco tree (Nicotiana glauca) as target crop species for improving saccharification, isoprenoid, long chain hydrocarbon contents, fiber quality, and suberin and lignin contents. The methods used to obtain these outputs include GC-MS, LC-MS and RNA sequencing platforms. The metabolite pipelines are well established tools to generate these types of data, but also have the limitations in that only well characterized metabolites can be used. The deep sequencing will allow us to include all transcripts present during the developmental stages of the tobacco tree leaf, but has to be mapped back to the sequence of Nicotiana tabacum. With these set-ups, we aim at a basic understanding for underlying processes and at establishing an industrial framework to exploit the outcomes. In a more long term perspective, we believe that data generated here will provide means for a sustainable biorefinery process using poplar and tobacco tree as raw material. To date the basal level of metabolites in the samples have been analyzed and the protocols utilized are provided in this article.

Towards the development of 1-to-n human machine interfaces for unmanned aerial vehicles

Multi-touch interfaces across a wide range of hardware platforms are becoming pervasive. This is due to the adoption of smart phones and tablets in both the consumer and corporate market place. This paper proposes a human-machine interface to interact with unmanned aerial systems based on the philosophy of multi-touch hardware-independent high-level interaction with multiple systems simultaneously. Our approach incorporates emerging development methods for multi-touch interfaces on mobile platforms. A framework is defined for supporting multiple protocols. An open source solution is presented that demonstrates: architecture supporting different communications hardware; an extensible approach for supporting multiple protocols; and the ability to monitor and interact with multiple UAVs from multiple clients simultaneously. Validation tests were conducted to assess the performance, scalability and impact on packet latency under different client configurations.

Modeling and sensorless direct torque and flux control of a dual-airgap axial flux permanent-magnet machine with field-weakening operation

This paper presents the modeling and motion-sensorless direct torque and flux control of a novel dual-airgap axial-flux permanent-magnet machine optimized for use in flywheel energy storage system (FESS) applications. Independent closed-loop torque and stator flux regulation are performed in the stator flux ( x-y) reference frame via two PI controllers. This facilitates fast torque dynamics, which is critical as far as energy charging/discharging in the FESS is concerned. As FESS applications demand high-speed operation, a new field-weakening algorithm is proposed in this paper. Flux weakening is achieved autonomously once the y-axis voltage exceeds the available inverter voltage. An inherently speed sensorless stator flux observer immune to stator resistance variations and dc-offset effects is also proposed for accurate flux and speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a machine prototype.

Modeling and position-sensorless control of a dual-airgap axial flux permanent magnet machine for flywheel energy storage systems

This paper presents the modeling and position-sensorless vector control of a dual-airgap axial flux permanent magnet (AFPM) machine optimized for use in flywheel energy storage system (FESS) applications. The proposed AFPM machine has two sets of three-phase stator windings but requires only a single power converter to control both the electromagnetic torque and the axial levitation force. The proper controllability of the latter is crucial as it can be utilized to minimize the vertical bearing stress to improve the efficiency of the FESS. The method for controlling both the speed and axial displacement of the machine is discussed. An inherent speed sensorless observer is also proposed for speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a prototype machine.

Translations of industry-based student learning and academic performances

We hypothesized that Industry based learning and teaching, especially through industry assigned student projects or training programs, is an integral part of science, technology, engineering and mathematics (STEM) education. In this paper we show that industry-based student training and experience increases students’ academic performances independent to the organizational parameters and contexts. The literature on industry-based student training focuses on employability and the industry dimension, and neglects in many ways the academic dimension. We observed that the association factors between academic attributes and contributions of industry-based student training are central and vital to the technological learning experiences. We explore international initiatives and statistics collected of student projects in two categories: Industry based learning performances and on campus performances. The data collected were correlated to five (5) universities in different industrialized countries, e.g., Australia N=545, Norway N=279, Germany N=74, France N=107 and Spain N=802 respectively. We analyzed industry-based student training along with company assigned student projects compared with in comparisons to campus performance. The data that suggests a strong correlation between industry-based student training per se and improved performance profiles or increasing motivation shows that industry-based student training increases student academic performance independent of organizational parameters and contexts. The programs we augmented were orthogonal to each other however, the trend of the students’ academic performances are identical. An isolated cohort for the reported countries that opposed our hypothesis warrants further investigation.