965 resultados para Industrial networks


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Ethernet is a key component of the standards used for digital process buses in transmission substations, namely IEC 61850 and IEEE Std 1588-2008 (PTPv2). These standards use multicast Ethernet frames that can be processed by more than one device. This presents some significant engineering challenges when implementing a sampled value process bus due to the large amount of network traffic. A system of network traffic segregation using a combination of Virtual LAN (VLAN) and multicast address filtering using managed Ethernet switches is presented. This includes VLAN prioritisation of traffic classes such as the IEC 61850 protocols GOOSE, MMS and sampled values (SV), and other protocols like PTPv2. Multicast address filtering is used to limit SV/GOOSE traffic to defined subsets of subscribers. A method to map substation plant reference designations to multicast address ranges is proposed that enables engineers to determine the type of traffic and location of the source by inspecting the destination address. This method and the proposed filtering strategy simplifies future changes to the prioritisation of network traffic, and is applicable to both process bus and station bus applications.

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Process bus networks are the next stage in the evolution of substation design, bringing digital technology to the high voltage switchyard. Benefits of process buses include facilitating the use of Non-Conventional Instrument Transformers, improved disturbance recording and phasor measurement and the removal of costly, and potentially hazardous, copper cabling from substation switchyards and control rooms. This paper examines the role a process bus plays in an IEC 61850 based Substation Automation System. Measurements taken from a process bus substation are used to develop an understanding of the network characteristics of "whole of substation" process buses. The concept of "coherent transmission" is presented and the impact of this on Ethernet switches is examined. Experiments based on substation observations are used to investigate in detail the behavior of Ethernet switches with sampled value traffic. Test methods that can be used to assess the adequacy of a network are proposed, and examples of the application and interpretation of these tests are provided. Once sampled value frames are queued by an Ethernet switch the additional delay incurred by subsequent switches is minimal, and this allows their use in switchyards to further reduce communications cabling, without significantly impacting operation. The performance and reliability of a process bus network operating with close to the theoretical maximum number of digital sampling units (merging units or electronic instrument transformers) was investigated with networking equipment from several vendors, and has been demonstrated to be acceptable.

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For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.

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There is increasing evidence of a weakened platform of consumer trust in mass produced food products. The resistance shown by consumers to the agro-industrial paradigm is evident in an emergent phase of reflexive consumerism, public reactions to an overly-concentrated retail sector and the rise of alternative food networks such as farmers' markets and organic box schemes. Supermarkets are responding strategically by aiming to manufacture new trust relations with consumers. This paper identifies three key strategies of trust manufacturing: (i) reputational enhancement though the institution of “behind the scenes,” business-to-business private standards; (ii) direct quality claims via private standard certification badges on food products, and ; (iii) discursive claimsmaking through symbolic representations of “authenticity” and “tradition.” Drawing upon the food governance literature and a “visual sociology” of supermarkets and supermarket produce, we highlight how trust is both commoditized and increasingly embedded into the marketing of mass-produced foods.

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Despite over three decades of legislation and initiatives designed to tackle the traditional gender divide in the science, technology and design fields, only a quarter of the registered architects in Australia are women. There are no statistics available for other design disciplines, with little known about why women choose design as a career path and who or what influences this decision. This qualitative research addresses this knowledge gap, through semi-structured in-depth interviews conducted with 19 Australian women who completed an industrial (product) design degree. Thematic analysis revealed three key themes: childhood aptitude and exposure; significant experiences and people; and design as a serendipitous choice. The findings emphasise the importance of early exposure to design as a potential career choice, highlighting the critical role played by parents, teachers, professionals and social networks.

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Major advances in power electronics during recent years have prompted considerable interest within the traction community. The capability of new technologies to reduce the AC railway networks' effect on power quality and improve their supply efficiency is expected to significantly decrease the cost of electric rail supply systems. Of particular interest are Static Frequency Converter (SFC), Rail Power Conditioner (RPC), High Voltage Direct Current (HVDC) and Energy Storage Systems (ESS) solutions. Substantial impacts on future feasibility of railway electrification are anticipated. Aurizon, Australia's largest heavy haul railway operator, has recently commissioned the world's first 50Hz/50Hz SFC installation and is currently investigating SFC, RPC, HVDC and ESS solutions. This paper presents a summary of current and emerging technologies with a particular focus on the potential techno-economic benefits.

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The present trend in the industry is towards the use of power transistors in the development of efficient Pulsewidth Modulated (PWM) inverters, because of their operation at high frequency, simplicity of turn-off, and low commutation losses compared to the technology using thyristors. But the protection of power transistors, minimization of switching power loss, and design of base drive circuit are very important for a reliable operation of the system. The requirements, analysis, and a simplified procedure for calculation of the switching-aid network components are presented. The transistor is protected against short circuit using a modified autoregulated and autoprotection drive circuit. The experimental results show that the switching power loss and voltage stress in the device can be reduced by suitable choice of the switching-aid network component values.

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Research on the internationalisation of small and medium-sized enterprises (SMEs) has received increasing attention in recent years due to the important role they play in today’s economic environment. Internationalisation prompting, or awareness, is an already recognised phase of the innovation-related stages model (I-model). This phase of awareness is closely related to the international exposure that a firm may experience during the occasion when it realises its competitors are already internationalising. Although the literature has discussed the various forms in which international exposure may happen, there has been limited attention given to the extent of its effect on the internationalisation of clustered SMEs that behave according to the I-Model. This study will assess the applicability of the I-Model in a dynamic, competitive and co-operative setting of an industrial cluster. It also evaluates the impact (if any) of international exposure derived from networks and the mimetic pressure that these firms may experience due to their embeddedness in an industrial cluster. Results from this study will indicate the effectiveness of the improved adapted model that will provide a richer insight for both academic researchers and policy makers.

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Wireless technologies are continuously evolving. Second generation cellular networks have gained worldwide acceptance. Wireless LANs are commonly deployed in corporations or university campuses, and their diffusion in public hotspots is growing. Third generation cellular systems are yet to affirm everywhere; still, there is an impressive amount of research ongoing for deploying beyond 3G systems. These new wireless technologies combine the characteristics of WLAN based and cellular networks to provide increased bandwidth. The common direction where all the efforts in wireless technologies are headed is towards an IP-based communication. Telephony services have been the killer application for cellular systems; their evolution to packet-switched networks is a natural path. Effective IP telephony signaling protocols, such as the Session Initiation Protocol (SIP) and the H 323 protocol are needed to establish IP-based telephony sessions. However, IP telephony is just one service example of IP-based communication. IP-based multimedia sessions are expected to become popular and offer a wider range of communication capabilities than pure telephony. In order to conjoin the advances of the future wireless technologies with the potential of IP-based multimedia communication, the next step would be to obtain ubiquitous communication capabilities. According to this vision, people must be able to communicate also when no support from an infrastructured network is available, needed or desired. In order to achieve ubiquitous communication, end devices must integrate all the capabilities necessary for IP-based distributed and decentralized communication. Such capabilities are currently missing. For example, it is not possible to utilize native IP telephony signaling protocols in a totally decentralized way. This dissertation presents a solution for deploying the SIP protocol in a decentralized fashion without support of infrastructure servers. The proposed solution is mainly designed to fit the needs of decentralized mobile environments, and can be applied to small scale ad-hoc networks or also bigger networks with hundreds of nodes. A framework allowing discovery of SIP users in ad-hoc networks and the establishment of SIP sessions among them, in a fully distributed and secure way, is described and evaluated. Security support allows ad-hoc users to authenticate the sender of a message, and to verify the integrity of a received message. The distributed session management framework has been extended in order to achieve interoperability with the Internet, and the native Internet applications. With limited extensions to the SIP protocol, we have designed and experimentally validated a SIP gateway allowing SIP signaling between ad-hoc networks with private addressing space and native SIP applications in the Internet. The design is completed by an application level relay that permits instant messaging sessions to be established in heterogeneous environments. The resulting framework constitutes a flexible and effective approach for the pervasive deployment of real time applications.

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Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

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Research on corporate responsibility has traditionally focused on the responsibilities of companies within their corporate boundaries only. Yet this view is challenged today as more and more companies face the situation in which the environmental and social performance of their suppliers, distributors, industry or other associated partners impacts on their sales performance and brand equity. Simultaneously, policy-makers have taken up the discussion on corporate responsibility from the perspective of globalisation, in particular of global supply chains. The category of selecting and evaluating suppliers has also entered the field of environmental reporting. Companies thus need to tackle their responsibility in collaboration with different partners. The aim of the thesis is to further the understanding of collaboration and corporate environmental responsibility beyond corporate boundaries. Drawing on the fields of supply chain management and industrial ecology, the thesis sets out to investigate inter-firm collaboration on three different levels, between the company and its stakeholders, in the supply chain, and in the demand network of a company. The thesis is comprised of four papers: Paper A discusses the use of different research approaches in logistics and supply chain management. Paper B introduces the study on collaboration and corporate environmental responsibility from a focal company perspective, looking at the collaboration of companies with their stakeholders, and the salience of these stakeholders. Paper C widens this perspective to an analysis on the supply chain level. The focus here is not only beyond corporate boundaries, but also beyond direct supplier and customer interfaces in the supply chain. Paper D then extends the analysis to the demand network level, taking into account the input-output, competitive and regulatory environments, in which a company operates. The results of the study broaden the view of corporate responsibility. By applying this broader view, different types of inter-firm collaboration can be highlighted. Results also show how environmental demand is extended in the supply chain regardless of the industry background of the company.

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The neural network finds its application in many image denoising applications because of its inherent characteristics such as nonlinear mapping and self-adaptiveness. The design of filters largely depends on the a-priori knowledge about the type of noise. Due to this, standard filters are application and image specific. Widely used filtering algorithms reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design a finite impulse response filter based on principal component neural network (PCNN) is proposed in this study for image filtering, optimized in the sense of visual inspection and error metric. This algorithm exploits the inter-pixel correlation by iteratively updating the filter coefficients using PCNN. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions. Further, the number of unknown parameters is very few and most of these parameters are adaptively obtained from the processed image.