15,495 research outputs found

    Human response to vibration in residential environments (NANR209), technical report 3 : calculation of vibration exposure

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    The Technical Report 3 describes the research undertaken to develop a methodology by which human exposure to vibration in residential environments can be calculated. That work has carried out by the University of Salford supported by the Department of environment food and rural affairs (Defra). The overall aim of the project is to derive exposure-response relationships for human vibration in residential environments. This document in particular focuses on the methods used to calculate vibration exposure from measured vibration signals due to different sources. The main objective of this report is to describe the different approaches used for calculating the different source-specific exposure. Reported here are findings obtained and a description of the feasibility of the methods used for evaluating exposure for different sources. In addition, an evaluation of the uncertainty related to the exposure calculation is considered

    An extension of the Dewey decimal system of classification applied to the engineering industries

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    A review of key planning and scheduling in the rail industry in Europe and UK

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    Planning and scheduling activities within the rail industry have benefited from developments in computer-based simulation and modelling techniques over the last 25 years. Increasingly, the use of computational intelligence in such tasks is featuring more heavily in research publications. This paper examines a number of common rail-based planning and scheduling activities and how they benefit from five broad technology approaches. Summary tables of papers are provided relating to rail planning and scheduling activities and to the use of expert and decision systems in the rail industry.EPSR

    Slip and Adhesion in a Railway Wheelset Simulink Model Proposed for Detection Driving Conditions Via Neural Networks

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    Constantly enlarging operation of locomotives with a very high tractive power in modern railway transport has caused problems with optimal supplying torque from motor to wheel-sets. Losses emerging with inadequate torque values lead to wheel slipping connected with excessive wear and limited acceleration. In models simulating dynamics of torque transmission from the drive units to wheels, the most important are the submodel of the drive and the submodel of balance between traction forces and drive resistances. Some issues of this field studied within a PhD program and SGS (CTU Students Grant Competition) has been focused on increasing quality of these submodels. This contribution is aimed at an innovated part in the existing Simulink model utilizing new data sources and modeling techniques. This improvement supports application of operating point detection methods based on machine learning techniques. New control facilities provided with pulse-width modulated frequency control of the asynchronous motor will be used for automatic submission of optimal operating points. The idea of utilization of via simulation obtained data is an on-line training of polynomial neural unit as an approximation of current driving conditions.Neustále narůstající provoz lokomotiv s velmi vysokým trakčním výkonem v moderní železniční dopravě způsobuje problémy s přenosem optimálního hnacího momentu z motoru na dvojkolí. Ztráty vyplývající z nevhodných hodnot točivého momentu vedou k prokluzu kol spojeným s nadměrným opotřebením a omezeným zrychlením. V modelech simulujících dynamiku přenosu točivého momentu z pohonné jednotky na dvojkolí jsou nejdůležitější submodely pohonu a rovnováhy mezi trakčními silami a jízdními odpory. Výzkum prováděný v rámci doktorských studijních programů a SGS (Studentská grantová soutěž ČVUT) se zaměřuje na zvyšování kvality těchto submodelů. Tento příspěvek je zaměřen na inovovanou část v existujícím Simulink modelu využívajícím nové zdroje dat a technik modelování. Nové možnosti regulace zajištěné pulzně-šířkovou frekvenční regulací asynchronního motoru budou použity pro automatické poskytnutí optimálních provozních bodů. Představa využití simulací získaných dat je on-line učení polynomické neuronové jednotky jako aproximace současných jízdních podmínek

    Wireless Sensor Networks for Condition Monitoring in the Railway Industry : a Survey

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    In recent years, the range of sensing technologies has expanded rapidly, whereas sensor devices have become cheaper. This has led to a rapid expansion in condition monitoring of systems, structures, vehicles, and machinery using sensors. Key factors are the recent advances in networking technologies such as wireless communication and mobile adhoc networking coupled with the technology to integrate devices. Wireless sensor networks (WSNs) can be used for monitoring the railway infrastructure such as bridges, rail tracks, track beds, and track equipment along with vehicle health monitoring such as chassis, bogies, wheels, and wagons. Condition monitoring reduces human inspection requirements through automated monitoring, reduces maintenance through detecting faults before they escalate, and improves safety and reliability. This is vital for the development, upgrading, and expansion of railway networks. This paper surveys these wireless sensors network technology for monitoring in the railway industry for analyzing systems, structures, vehicles, and machinery. This paper focuses on practical engineering solutions, principally,which sensor devices are used and what they are used for; and the identification of sensor configurations and network topologies. It identifies their respective motivations and distinguishes their advantages and disadvantages in a comparative review

    A comparative reliability analysis of ETCS train radio communications

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    StoCharts have been proposed as a UML statechart extension for performance and dependability evaluation, and were applied in the context of train radio reliability assessment to show the principal tractability of realistic cases with this approach. In this paper, we extend on this bare feasibility result in two important directions. First, we sketch the cornerstones of a mechanizable translation of StoCharts to MoDeST. The latter is a process algebra-based formalism supported by the Motor/Möbius tool tandem. Second, we exploit this translation for a detailed analysis of the train radio case study
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