Fault symptoms of rolling element bearings under variable operating conditions - a multi domain analysis

Diagnostics of rolling element bearings have been traditionally developed for constant operating conditions, and sophisticated techniques, like Spectral Kurtosis or Envelope Analysis, have proven their effectiveness by means of experimental tests, mainly conducted in small-scale laboratory test-rigs. Algorithms have been developed for the digital signal processing of data collected at constant speed and bearing load, with a few exceptions, allowing only small fluctuations of these quantities. Owing to the spreading of condition based maintenance in many industrial fields, in the last years a need for more flexible algorithms emerged, asking for compatibility with highly variable operating conditions, such as acceleration/deceleration transients. This paper analyzes the problems related with significant speed and load variability, discussing in detail the effect that they have on bearing damage symptoms, and propose solutions to adapt existing algorithms to cope with this new challenge. In particular, the paper will i) discuss the implication of variable speed on the applicability of diagnostic techniques, ii) address quantitatively the effects of load on the characteristic frequencies of damaged bearings and iii) finally present a new approach for bearing diagnostics in variable conditions, based on envelope analysis. The research is based on experimental data obtained by using artificially damaged bearings installed on a full scale test-rig, equipped with actual train traction system and reproducing the operation on a real track, including all the environmental noise, owing to track irregularity and electrical disturbances of such a harsh application.

Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

Climate change and financial regulation : challenges for the financial sector post the Global Financial Crisis

Regulation has played a significant role in shaping the financial services sector in Australia over the past few decades. Regulatory changes have included the establishment of the Australian Prudential Regulation Authority (APRA), floating the Australian dollar, allowing foreign financial institutions to operate domestically, the introduction of the superannuation guarantee charge, and the removal of interest rate controls. As the economy emerges from the worst financial crisis since the great depression, a new force of change that is recognised as one of the most significant sources of risk and opportunity facing the business community in the foreseeable future is that of climate change. Climate change is expected to be a significant change agent in the financial services sector as extreme weather patterns, sea level rises, and atmospheric changes impact on asset values (both investment and lending), project finance, and risk products. The financial services industry will be particularly affected by these developments, both as a provider of financial products (capital, credit, investment, advice, and insurance), and also through its powerful influence on the economy in terms of capital allocation. In addition, industry constituents will be heavily impacted by government regulation in this area (reporting, emissions trading and environmental policies), with respect to their own business practices and also those of their clients. This study reports the results of interviews conducted with senior members of the finance sector working in the sustainability area to gauge their perceptions of the challenges facing the sector with respect to climate change. Our results confirm that that regulatory intervention will be critical to climate change response gaining traction and momentum. In particular, regulatory certainty will promote engagement, particularly in relation to the Carbon Pollution Reduction Scheme (CPRS), with other developments needed in terms of information disclosure, performance and remuneration, and incentive programs. Accordingly, the significant potential risks and opportunities that climate change presents to the sector, and the broader economy, will in part be managed/realised only if a swift and significant regulatory response is achieved.

Numerical estimation of 3D mechanical forces exerted by cells on non-linear materials

The exchange of physical forces in both cell-cell and cell-matrix interactions play a significant role in a variety of physiological and pathological processes, such as cell migration, cancer metastasis, inflammation and wound healing. Therefore, great interest exists in accurately quantifying the forces that cells exert on their substrate during migration. Traction Force Microscopy (TFM) is the most widely used method for measuring cell traction forces. Several mathematical techniques have been developed to estimate forces from TFM experiments. However, certain simplifications are commonly assumed, such as linear elasticity of the materials and/or free geometries, which in some cases may lead to inaccurate results. Here, cellular forces are numerically estimated by solving a minimization problem that combines multiple non-linear FEM solutions. Our simulations, free from constraints on the geometrical and the mechanical conditions, show that forces are predicted with higher accuracy than when using the standard approaches.

Business process management in small business : a case study

Small Businesses account for a significant portion of the Australian business sector. With Business Process Management (BPM) gaining prominence in recent decades as a means of improving business performance, it would seem to only be a matter of time before it gains momentum within the Small Business sector. One may even question why it has not already achieved more traction within the sector. This case study involves a BPM initiative to develop process infrastructure in an establishing Small Business. It explores whether mainstream BPM tools, techniques and technologies can be applied in a Small Business setting. The chapter provides a background to the case organisation, outlines the activities undertaken in the BPM initiative and distils key observations drawn from participation in the initiative and consultation with stakeholders. Based on the case study experiences, a number of implications are identified for further consideration by the BPM discipline as it continues to address the question of how it can become more widely adopted amongst Small Businesses.

On extension and torsion of a compressible elastic circular cylinder

In this paper we examine the combined extension and torsion of a compressible isotropic elastic cylinder of finite extent. The equilibrium equations are formulated in terms of the principal stretches and then applied to the special case of pure torsion superimposed on a uniform extension (an isochoric deformation). Explicit necessary and sufficient conditions on the strain-energy function for the material to support this deformation with vanishing traction on the lateral surfaces of the cylinder are obtained. Some strain-energy functions satisfying these conditions are considered, existing results are recovered as special cases and new results are obtained. We also point out how the strain-energy functions generated from the considered isochoric deformation considered (of a compressible material) can be used to generate energy functions and corresponding solutions for the incompressible theory.

Carbon nanotube membranes with ultrahigh specific adsorption capacity for water desalination and purification

Development of technologies for water desalination and purification is critical to meet the global challenges of insufficient water supply and inadequate sanitation, especially for point-of-use applications. Conventional desalination methods are energy and operationally intensive, whereas adsorption-based techniques are simple and easy to use for point-of-use water purification, yet their capacity to remove salts is limited. Here we report that plasma-modified ultralong carbon nanotubes exhibit ultrahigh specific adsorption capacity for salt (exceeding 400% by weight) that is two orders of magnitude higher than that found in the current state-of-the-art activated carbon-based water treatment systems. We exploit this adsorption capacity in ultralong carbon nanotube-based membranes that can remove salt, as well as organic and metal contaminants. These ultralong carbon nanotube-based membranes may lead to next-generation rechargeable, point-of-use potable water purification appliances with superior desalination, disinfection and filtration properties. © 2013 Macmillan Publishers Limited.

Enhancing paramedics procedural skills using a cadaveric model

Background Paramedic education has evolved in recent times from vocational post-employment to tertiary pre-employment supplemented by clinical placement. Simulation is advocated as a means of transferring learned skills to clinical practice. Sole reliance of simulation learning using mannequin-based models may not be sufficient to prepare students for variance in human anatomy. In 2012, we trialled the use of fresh frozen human cadavers to supplement undergraduate paramedic procedural skill training. The purpose of this study is to evaluate whether cadaveric training is an effective adjunct to mannequin simulation and clinical placement. Methods A multi-method approach was adopted. The first step involved a Delphi methodology to formulate and validate the evaluation instrument. The instrument comprised of knowledge-based MCQs, Likert for self-evaluation of procedural skills and behaviours, and open answer. The second step involved a pre-post evaluation of the 2013 cadaveric training. Results One hundred and fourteen students attended the workshop and 96 evaluations were included in the analysis, representing a return rate of 84%. There was statistically significant improved anatomical knowledge after the workshop. Students' self-rated confidence in performing procedural skills on real patients improved significantly after the workshop: inserting laryngeal mask (MD 0.667), oropharyngeal (MD 0.198) and nasopharyngeal (MD 0.600) airways, performing Bag-Valve-Mask (MD 0.379), double (MD 0.344) and triple (MD 0.326,) airway manoeuvre, doing 12-lead electrocardiography (MD 0.729), using McGrath(R) laryngoscope (MD 0.726), using McGrath(R) forceps to remove foreign body (MD 0.632), attempting thoracocentesis (MD 1.240), and putting on a traction splint (MD 0.865). The students commented that the workshop provided context to their theoretical knowledge and that they gained an appreciation of the differences in normal tissue variation. Following engagement in/ completion of the workshop, students were more aware of their own clinical and non-clinical competencies. Conclusions The paramedic profession has evolved beyond patient transport with minimal intervention to providing comprehensive both emergency and non-emergency medical care. With limited availability of clinical placements for undergraduate paramedic training, there is an increasing demand on universities to provide suitable alternatives. Our findings suggested that cadaveric training using fresh frozen cadavers provides an effective adjunct to simulated learning and clinical placements.

Why the energy technology revolution hasn't happened

The main thrusts of this TEDx talk are rooted in findings from original research by Rob Perrons concerning the role of industry clockspeed on technology-focused startups. The study involved extensive exposure to five member companies from the Shell Technology Ventures portfolio of companies over a three-year period, and shed new light on the specific mechanics that were contributing to these companies’ inability to get traction for their respective innovations within the marketplace. This evidence is also being coalesced into scholarly and scholarly publications—but this TEDx talk was a first release of a few of these high-level findings.

Conceptualising business models : definitions, frameworks and classifications

The business model concept is gaining traction in different disciplines but is still criticized for being fuzzy and vague and lacking consensus on its definition and compositional elements. In this paper we set out to advance our understanding of the business model concept by addressing three areas of foundational research: business model definitions, business model elements, and business model archetypes. We define a business model as a representation of the value logic of an organization in terms of how it creates and captures customer value. This abstract and generic definition is made more specific and operational by the compositional elements that need to address the customer, value proposition, organizational architecture (firm and network level) and economics dimensions. Business model archetypes complement the definition and elements by providing a more concrete and empirical understanding of the business model concept. The main contributions of this paper are (1) explicitly including the customer value concept in the business model definition and focussing on value creation, (2) presenting four core dimensions that business model elements need to cover, (3) arguing for flexibility by adapting and extending business model elements to cater for different purposes and contexts (e.g. technology, innovation, strategy),(4) stressing a more systematic approach to business model archetypes by using business model elements for their description, and (5) suggesting to use business model archetype research for the empirical exploration and testing of business model elements and their relationships.

Real-time price based home energy management scheduler

With the recent development of advanced metering infrastructure, real-time pricing (RTP) scheme is anticipated to be introduced in future retail electricity market. This paper proposes an algorithm for a home energy management scheduler (HEMS) to reduce the cost of energy consumption using RTP. The proposed algorithm works in three subsequent phases namely real-time monitoring (RTM), stochastic scheduling (STS) and real-time control (RTC). In RTM phase, characteristics of available controllable appliances are monitored in real-time and stored in HEMS. In STS phase, HEMS computes an optimal policy using stochastic dynamic programming (SDP) to select a set of appliances to be controlled with an objective of the total cost of energy consumption in a house. Finally, in RTC phase, HEMS initiates the control of the selected appliances. The proposed HEMS is unique as it intrinsically considers uncertainties in RTP and power consumption pattern of various appliances. In RTM phase, appliances are categorized according to their characteristics to ease the control process, thereby minimizing the number of control commands issued by HEMS. Simulation results validate the proposed method for HEMS.

The psychological and economic factors that influence energy consumption habits of low-income earners

Social marketers and governments have often targeted hard to reach or vulnerable groups (Gordon et al., 2006) such as young adults and low income earners. Past research has shown that low-income earners are often at risk of poor health outcomes and diminished lifestyle (Hampson et al., 2009; Scott et al., 2012). Young adults (aged 18 to 35) are in a transition phase of their life where lifestyle preferences are still being formed and are thus a useful target for long-term sustainable change. An area of focus for all levels of government is the use of energy with an aim to reduce consumption. There is little research to date that combines both of these groups and in particular in the context of household energy usage. Research into financially disadvantaged consumers is challenging the notion that that low income consumer purchasing and usage of products and services is based upon economic status (Sharma et al., 2012). Prior research shows higher income earners view items such as televisions and computers as necessities rather than non-essential (Karlsson et al., 2004). Consistent with this is growing evidence that low income earners purchase non-essential, energy intensive electronic appliances such as multiple big screen TV sets and additional refrigerators. With this in mind, there is a need for knowledge about how psychological and economic factors influence the energy consumption habits (e.g. appliances on standby power, leaving appliances turned on, running multiple devices at one time) of low income earners. Thus, our study sought to address the research question of: What are the factors that influence young adult low-income earners energy habits?

A lightweight, modular robotic vehicle for the sustainable intensification of agriculture

This paper describes a lightweight, modular and energy efficient robotic vehicle platform designed for broadacre agriculture - the Small Robotic Farm Vehicle (SRFV). The current trend in farming is towards increasingly large machines that optimise the individual farmer’s productivity. Instead, the SRFV is designed to promote the sustainable intensification of agriculture by allowing farmers to concentrate on more important farm management tasks. The robot has been designed with a user-centred approach which focuses the outcomes of the project on the needs of the key project stakeholders. In this way user and environmental considerations for broadacre farming have informed the vehicle platform configuration, locomotion, power requirements and chassis construction. The resultant design is a lightweight, modular four-wheeled differential steer vehicle incorporating custom twin in-hub electric drives with emergency brakes. The vehicle is designed for a balance between low soil impact, stability, energy efficiency and traction. The paper includes modelling of the robot’s dynamics during an emergency brake in order to determine the potential for tipping. The vehicle is powered by a selection of energy sources including rechargeable lithium batteries and petrol-electric generators.

Energy efficient home with price sensitive stochastically programmable TCAs

Introduction of dynamic pricing in present retail market, considerably affects customers with an increased cost of energy consumption. Therefore, customers are enforced to control their loads according to price variation. This paper proposes a new technique of Home Energy Management, which helps customers to minimize their cost of energy consumption by appropriately controlling their loads. Thermostatically Controllable Appliances (TCAs) such as air conditioner and water heater are focused in this study, as they consume more than 50% of the total household energy consumption. The control process includes stochastic dynamic programming, which incorporated uncertainties in price and demand variation. It leads to an accurate selection of appliance settings. It is followed by a real time control of selected appliances with its optimal settings. Temperature set points of TCAs are adjusted based on price droop which is a reflection of actual cost of energy consumption. Customer satisfaction is maintained within limits using constraint optimization. It is showed that considerable energy savings is achieved.