34 resultados para rail wheel flat, vibration monitoring, wavelet approaches, daubechies wavelets, signal processing


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The aim of this study is to highlight the relationship between muscle motion, generated by whole body vibration, and the correspondent electromyographic (EMG) activity and to suggest a new method to customize the stimulation frequency. Simultaneous recordings of EMG and tri-axial accelerations of quadriceps rectus femoris from fifteen subjects undergoing vibration treatments were collected. Vibrations were delivered via a sinusoidal oscillating platform at different frequencies (10-45 Hz). Muscle motion was estimated by processing the accelerometer data. Large EMG motion artifacts were removed using sharp notch filters centred at the vibration frequency and its superior harmonics. EMG-RMS values were computed and analyzed before and after artifact suppression to assess muscular activity. Muscles acceleration amplitude increased with frequency. Muscle displacements revealed a mechanical resonant-like behaviour of the muscle. Resonance frequencies and dumping factors depended on subject. Moreover, RMS of artifact-free EMG was found well correlated (R 2 = 0.82) to the actual muscle displacement, while the maximum of the EMG response was found related to the mechanical resonance frequency of muscle. Results showed that maximum muscular activity was found in correspondence to the mechanical resonance of the muscle itself. Assuming the hypothesis that muscle activation is proportional to muscle displacement, treatment optimization (i.e. to choose the best stimulation frequency) could be obtained by simply monitoring local acceleration (resonance), leading to a more effective muscle stimulation. Motion artifact produced an overestimation of muscle activity, therefore its removal was essential. © 2009 IPEM.

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The aim of this work is to contribute to the analysis and characterization of training with whole body vibration (WBV) and the resultant neuromuscular response. WBV aims to mechanically activate muscle by eliciting stretch reflexes. Generally, surface electromyography is utilized to assess muscular response elicited by vibrations. However, EMG analysis could potentially bring to erroneous conclusions if not accurately filtered. Tiny and lightweight MEMS accelerometers were found helpful in monitoring muscle motion. Displacements were estimated integrating twice the acceleration data after gravity and small postural subject adjustments contribution removal. Results showed the relevant presence of motion artifacts on EMG recordings, the high correlation between muscle motion and EMG activity and how resonance frequencies and dumping factors depended on subject and his positioning onto the vibrating platform. Stimulations at the resonant frequency maximize muscles lengthening and in turn, muscle spindle solicitation , which may produce more muscle activation. Local mechanical stimulus characterization (Le, muscle motion analysis) could be meaningful in discovering proper muscle stimulation and may contribute to suggest appropriate and effective WBV exercise protocols. ©2009 IEEE.

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As more of the economy moves from traditional manufacturing to the service sector, the nature of work is becoming less tangible and thus, the representation of human behaviour in models is becoming more important. Representing human behaviour and decision making in models is challenging, both in terms of capturing the essence of the processes, and also the way that those behaviours and decisions are or can be represented in the models themselves. In order to advance understanding in this area, a useful first step is to evaluate and start to classify the various types of behaviour and decision making that are required to be modelled. This talk will attempt to set out and provide an initial classification of the different types of behaviour and decision making that a modeller might want to represent in a model. Then, it will be useful to start to assess the main methods of simulation in terms of their capability in representing these various aspects. The three main simulation methods, System Dynamics, Agent Based Modelling and Discrete Event Simulation all achieve this to varying degrees. There is some evidence that all three methods can, within limits, represent the key aspects of the system being modelled. The three simulation approaches are then assessed for their suitability in modelling these various aspects. Illustration of behavioural modelling will be provided from cases in supply chain management, evacuation modelling and rail disruption.

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Optical fibre based sensors are transforming industry by permitting monitoring in hitherto inaccessible environments or measurement approaches that cannot be reproduced using conventional electronic sensors. A multitude of techniques have been developed to render the fibres sensitive to a wide range of parameters including: temperature, strain, pressure (static and dynamic), acceleration, rotation, gas type, and specific biochemical species. Constructed entirely of glass or polymer material, optical fibre devices like fibre gratings offer the properties: low loss, dielectric construction, small size, multiplexing, and so on [1-3]. In this paper, the authors will show the latest developing industrial applications, using polymer optical fibre (POF) devices, and comparing their performance with silica optical fibre devices. The authors address two pressing commercial requirements. The first concerns the monitoring of fuel level in civil aircraft. There is a strong motivation in the aerospace industry to move away from electrical sensors, especially in the fuel system. This is driven by the need to eliminate potential ignition hazards, the desire to reduce cabling weight and the need to mitigate the effects of lightning strikes in aircraft where the conventional metallic skin is increasingly being replaced by composite materials. In this case, the authors have developed pressure sensors based on a diaphragm in which a polymer fibre Bragg grating (POFBG) has been embedded [3]. These devices provide high pressure sensitivity enabling level measurement in the mm range. Also, it has developed an approach incorporating several such sensors which can compensate for temperature drifts and is insensitive to fluid density. Compared with silica fibre-based sensors, their performance is highly enhanced. Initial results have attracted the interest of Airbus from UK, who is keen to explore the potential of optical technology in commercial aircraft. The second concerns the monitoring of acoustic signals and vibration in the subsea environment, for applications in geophysical surveying and security (detection of unwanted craft or personnel). There is strong motivation to move away from electrical sensors due to the bulk of the sensor and associated cabling and the impossibility of monitoring over large distances without electrical amplification. Optical approaches like optical hydrophones [5] offer a means of overcoming these difficulties. In collaboration with Kongsberg from Norway, the authors will exploit the sensitivity improvements possible by using POF instead of silica fibre. These improvements will arise as a result of the much more compliant nature of POF compared to silica fibre (3 GPa vs 72 GPa, respectively). Essentially, and despite the strain sensitivity of silica and POFBGs being very similar, this renders the POF much more sensitive to the applied stress resulting from acoustic signals or vibration. An alternative way of viewing this is that the POF is better impedance-matched to the surrounding environment (water for the intended applications), because although its impedance is higher than that of water, it is nearly an order of magnitude smaller than that of silica. Finally, other future industrial applications will be presented and discussed, showing the vast range of the optical fiber devices in sensing applications.