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Introducing an innovative and efficient seat user interface for professional drivers

IET INTELLIGENT TRANSPORT SYSTEMS 2007年第1期1卷 37-46页

作者： Amditis, A. Karaseitanidis, I. Bekiaris, E. Sartor, S. Ronnefahrt, J. Dangelmaier, M. Inst Commun & Comp Syst Athens 15773 Greece Aristotle Univ Thessaloniki Transport Syst Res Grp Thessaloniki 54124 Greece Isringhausen GmbH & Co KG D-32657 Lemgo Germany Fraunhofer Inst Ind Engn D-70569 Stuttgart Germany

Prolonged driving is now recognised as one of the main contributing factors to a number of health issues related to professional drivers. Back pain and musculoskeletal disorders are the most frequent symptoms and would seem to be directly related to the driving conditions and, in particular, the seating system. SAFEGUARD, a European co-funded research project, has developed two prototype seating systems, one customised for a truck and the other for a tractor, with the intention of addressing these problems by the implementation of sensors and actuators that are suited for increasing safety and comfort while driving. The diversity of the options provided by the prototype systems, their complexity and requirement to be used properly has necessitated the development of an advanced user interface (UI). The UI prerequisites are for the efficient handling of the varied seat features, a non-obstructive character for the interface and a natural integration of the operational input/output elements in the cabin interior.

关键词： seat user interface truck seat systems Automobile industry automotive engineering ergonomics drive comfort tractor seat systems civil and mechanical engineering computing User interfaces drive safety Vehicle mechanics road safety professional driver health user interfaces

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Linking run-time resource management of embedded multi-core platforms with automated design-time exploration

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IET COMPUTERS AND DIGITAL TECHNIQUES 2011年第2期5卷 123-135页

作者： Ykman-Couvreur, C. Avasare, P. Mariani, G. Palermo, G. Silvano, C. Zaccaria, V. IMEC VZW IBBT B-3001 Louvain Belgium Univ Lugano ALaRI Lugano Switzerland Politecn Milan Dipartimento Elect & Informaz Milan Italy

Nowadays, owing to unpredictable changes of the environment and workload variation, optimally running multiple applications in terms of quality, performance and power consumption on embedded multi-core platforms is a huge challenge. A lightweight run-time manager, linked with an automated design-time exploration and incorporated in the host processor of the platform, is required to dynamically and efficiently configure the applications according to the available platform resources (e. g. processing elements, memories, communication bandwidth), for minimising the cost (e. g. power consumption), while satisfying the constraints (e. g. deadlines). This study presents a flow linking a design-time design space explorer, coupled with platform simulators at two abstraction levels, with a fast and lightweight priority-based heuristic integrated in the run-time manager to select near-optimal application configurations. To illustrate its feasibility and the very low complexity of the run-time selection, the proposed flow is used to manage the processors and clock frequencies of a multiple-stream MPEG4 encoder chip dedicated to automotive cognitive safety applications.

关键词： priority-based heuristic video coding Video signal processing Microprocessor chips Multiprocessing systems Image and video coding civil and mechanical engineering computing design-time design space explorer Digital signal processing chips Microprocessors and microcomputers run-time manager automotive engineering run-time resource management host processor platform simulators digital signal processing chips run-time selection automotive cognitive safety automated design-time exploration MPEG4 encoder chip embedded multicore platform road safety resource allocation multiprocessing systems

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Development of fast-response servos for military and naval systems - Part 2 - Simulation techniques

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computing & CONTROL engineering JOURNAL 2002年第4期13卷 206-213页

作者： Garner, F Kenilworth House Newport Shropshire TF10 9HJ 4 Church Road United Kingdom

In Part I of this article (June CCEJ, pp.127-136), a brief history of the development of servo drives for military applications was given. Then the design and performance of the laboratory hardware,constructed was described. Part 2 comments on results from system analysis mathematics and computer modelling work using Matlab/Simulink software. The article refers to computer modelling work currently being carried out and to future work.

关键词： fast-response servos systems analysis military systems computer modelling control system analysis computing naval engineering computing Military administration computing in other engineering fields Control technology and theory civil and mechanical engineering computing Actuating and final control devices simulation techniques military computing Control system design and analysis Matlab/Simulink software servomechanisms software packages system analysis mathematics Marine system control Military control systems naval systems digital simulation

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NEW TECHNIQUES FOR APPROXIMATE REALIZATION

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PROCEEDINGS OF THE INSTITUTION OF ELECTRICAL ENGINEERS-LONDON 1979年第6期126卷 596-604页

作者： GLOVER, K Department of Engineering Control & Management Systems Division Cambridge University Cambridge UK

The problem of approximate realisation is described and various methods are discussed. A new method is then given which directly identifies the system poles from pulse response data by finding the local minima of a real function of a complex variable. These estimates of the poles are then refined using a new iterative nonlinear least-squares algorithm. Finally, these methods are applied to a ‘seismic wavelet’, and are shown to give good qualitative and quantitative information on the system being modelled.

关键词： seismology data reduction and analysis geophysical techniques seismic wavelet Numerical approximation and analysis poles and zeros system poles identification geophysics computing pulse response data Geophysics computing iterative nonlinear least squares algorithm approximate realisation Simulation, modelling and identification civil and mechanical engineering computing Seismic waves Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research signal processing Function theory, analysis

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Algorithm to decompose three-dimensional complex structures at the necks: tested on snow structures

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IET IMAGE PROCESSING 2011年第2期5卷 132-140页

作者： Theile, T. Schneebeli, M. WSL Inst Snow & Avalanche Res SLF CH-7260 Davos Switzerland

The separation of overlapping particles in three-dimensional images is an image processing task with many fields of application. However, commonly used image processing algorithms have difficulties to identify the single particles and their connections in certain structures. Here the authors present an alternative algorithm for part decomposition, which performs better on some structures than common algorithms. This algorithm is a special case of part decomposition, as it decomposes a structure at the necks into single particles. The necks are detected based on their characteristic negative Gaussian curvature. The algorithm itself consists of three steps: cutting at negative Gaussian curvature, region growing and intersecting plane minimisation. The authors tested the performance of the algorithm by comparison with two state-of-the-art algorithms for part decomposition, the watershed and a skeleton-based algorithm on strongly differing geometries, taken from natural snow samples. The two test algorithms are known for having difficulties to decompose certain structures. As the new algorithm uses a different characteristic to decompose the structure, the new algorithm is a good alternative to the existing algorithms. The new algorithm decomposes 72% of the reference structure correctly. This is a better performance than by the two other algorithms.

关键词： snow structures structural engineering computing mechanical engineering applications of IT three-dimensional images image processing snow negative Gaussian curvature Computer vision and image processing techniques decompose three-dimensional complex structures mechanical structures skeleton-based algorithm Optical, image and video signal processing civil and mechanical engineering computing overlapping particles

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STLRF-Stack: A fault prediction model for pure electric vehicles based on a high dimensional imbalanced dataset

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IET INTELLIGENT TRANSPORT SYSTEMS 2023年第2期17卷 400-417页

作者： Tian, Sheng Li, Jia Zhang, Jinming Li, Chengwei South China Univ Technol Sch Civil Engn & Transportat Guangzhou 510000 Peoples R China

Fault prediction is an important part of the safe operation and maintenance of pure electric vehicles, and it is crucial to predict faults efficiently and accurately. To address the problems that the pure electric vehicle fault prediction model has less than ideal prediction effect and classification bias to most classes due to unbalanced data set categories and high dimensionality of features, this paper firstly obtains a low dimensional balanced dataset based on hybrid sampling and joint feature selection. Then the classification ability of the model is improved through ensemble learning. Finally, a new hybrid model STLRF-Stack is proposed to realize efficient fault prediction of pure electric vehicles. This paper is validated on a real operating dataset of pure electric vehicles. The experimental results show that the prediction effect of the hybrid model proposed in this paper is better than that of the single model and related literature. In addition, this model can successfully predict the fault 5 min before the actual fault of electric vehicles occurs, which provides the drivers with the opportunity of accident prevention and early treatment. Therefore, the model has specific feasibility and practical application value.

关键词： actual fault fault diagnosis civil and mechanical engineering computing pure electric vehicle fault prediction model learning (artificial intelligence) hybrid model STLRF-Stack feature selection pattern classification Transportation efficient fault prediction Statistics mechanical components Data handling techniques pure electric vehicles mechanical engineering computing Inspection and quality control low dimensional balanced dataset mechanical engineering applications of IT high dimensional imbalanced dataset fault 5 min accident prevention ideal prediction effect Other topics in statistics Maintenance and reliability

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FLO/STRESS: an integrated software module to predict stress in electronic products

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computing & CONTROL engineering JOURNAL 2002年第3期13卷 143-148页

作者： Bailey, C Warner, M Agha, A Pericleous, K Parry, J Marooney, C Reeves, H Clark, I Univ Greenwich Ctr Numer Modelling & Proc Anal London SE10 9LS England Flomer Ltd Surrey KT8 9HH England

Software technology that predicts stress in electronic systems and packages, developed as part of TCS Programme, is described. The software is closely integrated within a thermal design tool providing the ability to simulate the coupled effects of airflow, temperature and stress on product performance. This integrated approach to analysis will help decrease the number of design cycles.

关键词： design cycles Electronics industry product performance circuit CAD Design product development CAD Production engineering computing Digital circuit design, modelling and testing computer-aided analysis thermal design tool integrated software module mechanical engineering computing electronic product stress prediction airflow civil and mechanical engineering computing Computer-aided circuit analysis and design FLO STRESS software circuit analysis computing TCS Programme Electronic engineering computing electronics industry Industrial applications of IT temperature

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Automatic detection of safety helmet wearing based on head region location

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IET IMAGE PROCESSING 2021年第11期15卷 2441-2453页

作者： Gu, Yuwan Wang, Yusheng Shi, Lin Li, Ning Zhuang, Lihua Xu, Shoukun Changzhou Univ Sch Comp Sci & Artificial Intelligence Changzhou 213164 Jiangsu Peoples R China

In order to solve the problem of difficult and low precision in the detection of safety helmet wearing in the complex pose of construction worker, a detection method of safety helmet wearing based on pose estimation is proposed. In the pose estimation model of OpenPose, the residual network optimized feature extraction is introduced to obtain the skeletal point information of the construction worker, and then the pose of the construction worker is estimated based on the skeletal point information, three-point localization method is proposed for the front and back pose, and skin colour detection method is proposed for the side pose, and then to determine the head region. The YOLO v4 is used to detect the safety helmet region, and then the construction worker's safety helmet wearing is judged according to whether the head region intersects the safety helmet region or not. Experimental results show that the detection accuracy of the method is higher than other methods, and the adaptability to the environment is stronger.

关键词： difficult precision Construction industry occupational safety Production equipment image colour analysis construction equipment three point localization method Image recognition Computer vision and image processing techniques production engineering computing construction worker safety helmet wearing automatic detection skeletal point information feature extraction Industrial applications of IT safety systems skin colour detection method network optimized feature extraction construction industry head region location pose estimation Production engineering computing civil and mechanical engineering computing Health and safety aspects

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Statistical multivariate monitoring of rolling bearings working under varying operational conditions

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IET SCIENCE MEASUREMENT & TECHNOLOGY 2021年第9期15卷 749-762页

作者： Wang, Baoxiang Pan, Hongxia Huaiyin Inst Technol Fac Mech & Mat Engn Huaian Peoples R China North Univ China Fac Mech Engn Taiyuan Peoples R China

In recent years, statistical data-driven approaches have been developed for health monitoring of rolling bearings working under variable operational conditions. Due to the reliance on reference models, most of them encounter with the model mismatch problem. A novel statistical multivariate health monitoring framework is proposed in this article to determine the initial degradation of rolling bearings. On the one hand, multivariate statistical parameters are extracted from original vibration signals to indicate bearing's degradation trajectories from different perspectives, a dynamic autoencoder neural network is extended with a matrix augmentation trick for discovering both dynamic and nonlinear latent representation in the high-dimensional features. On the other hand, an eccentricity index is introduced for measuring information variations in the latent representation, such that bearing health development can be revealed timely. Then, an adaptive threshold is exploited for online monitoring of bearing damage. The effectiveness of the proposed work is substantiated using real vibration signals acquired from two different bearing degradation test rigs. The monitoring performance of the proposed work is evaluated in terms of false alarm rate (FAR). Experimental results confirm that the proposed work can identify early bearing damage under variable working conditions, by circumventing the model mismatch problem. It is found to be more superior than existing techniques.

关键词： Other topics in statistics Signal processing and detection Other topics in statistics Digital signal processing civil and mechanical engineering computing Statistics mechanical engineering applications of IT Maintenance and reliability Inspection and quality control Vibrations and shock waves (mechanical engineering) mechanical components Neural nets

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Empirical mode decomposition of acoustic signals for diagnosis of faults in gears and rolling element bearings

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IET SCIENCE MEASUREMENT & TECHNOLOGY 2012年第4期6卷 279-287页

作者： Amarnath, M. Krishna, I. R. Praveen Indian Inst Informat Technol Design & Mfg Jabalpu Jabalpur 482001 India Indian Inst Technol Machine Design Sect Dept Mech Engn Madras 600036 Tamil Nadu India

Rolling element bearings and gears are the most important components of rotating machines. One of the major causes of machine down time is because of the failure of these elements. Down time of rotating machines can be reduced by monitoring vibration and acoustic behaviour of machine elements. This study describes the application of the empirical mode decomposition (EMD) method to diagnose the faults in rolling element bearings and helical gears. By using EMD, a complicated signal can be decomposed into a number of intrinsic mode functions (IMFs) based on the local characteristic timescale of the signal. The IMFs reveal the intrinsic oscillation modes embedded in the signal. Acoustic signals acquired from the bearings and gears have been decomposed and kurtosis values are extracted from these IMFs to quantify various faults. Results demonstrate the advantages of EMD method to detect the faults in the early stage.

关键词： fault diagnosis acoustic signal detection fault detection rolling bearings mechanical components electric machine analysis computing helical gear Digital signal processing d.c. machines Vibrations and shock waves (mechanical engineering) vibration monitoring electric machines empirical mode decomposition method Power engineering computing Signal detection rotating machine element kurtosis value extraction acoustic signal behavior acquisition signal timescale intrinsic oscillation mode mechanical engineering computing mechanical engineering applications of IT rolling element bearing gears EMD method a.c. machines civil and mechanical engineering computing faults diagnosis intrinsic mode function IMF vibrations mechanical machinery

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