906 resultados para Vehicle Acceleration.


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The aim of this paper is to analyse the influence of the load centre of gravity on heavy vehicle acceleration. This analysis is done through a method in which a vehicle centre of gravity map is used. A model for the driving force is presented for bus, truck and tractor-semi trailer combinations. The proposed model takes into consideration the resistance forces (drag, rolling resistance, translation and rotation acceleration, climbing resistance) and the 4 X 2 traction system. The positions of the vehicle centre of gravity as a function of the position of the load centre of gravity are determined. The vehicle acceleration is calculated based on the position of the load centre of gravity. This study analyses the acceleration of one of the Mercedes-Benz do Brasil tractor-semitrailer vehicle. A comparison of the acceleration for different maximum adhesion coefficients and ramps are presented, showing new results. An example showing the variations of the load centre of gravity position with the acceleration time and distance is provided. The load centre of gravity position is important for vehicle safety and the efficiency and economy in the transportation of the load.

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National Highway Traffic Safety Administration, Office of Passenger Vehicle Research, Washington, D.C.

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National Highway Traffic Safety Administration, Office of Passenger Vehicle Research, Washington, D.C.

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National Highway Traffic Safety Administration, Office of Passenger Vehicle Research, Washington, D.C.

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Previous research on damage detection based on the response of a structure to a moving load has reported decay in accuracy with increasing load speed. Using a 3D vehicle – bridge interaction model, this paper shows that the area under the filtered acceleration response of the bridge increases with increasing damage, even at highway load speeds. Once a datum reading is established, the area under subsequent readings can be monitored and compared with the baseline reading, if an increase is observed it may indicate the presence of damage. The sensitivity of the proposed approach to road roughness and noise is tested in several damage scenarios. The possibility of identifying damage in the bridge by analysing the acceleration response of the vehicle traversing it is also investigated. While vehicle acceleration is shown to be more sensitive to road roughness and noise and therefore less reliable than direct bridge measurements, damage is successfully identified in favourable scenarios.

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This paper investigates the feasibility of using an instrumented vehicle to detect bridge dynamic parameters, such as natural frequency and structural damping, in a scaled laboratory experiment. In the experiment, a scaled vehicle model crosses a steel girder which has been adopted as the bridge model. The bridge model also includes a scaled road surface profile. The effects of varying vehicle model mass and speed are investigated. The damping of the girder is also varied. The bridge frequency and changes in damping are detected in the vehicle acceleration response in the presence of a rough road surface profile.

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National Highway Traffic Safety Administration, Washington, D.C.

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本文分析了轮式移动机器人在运行过程中由于动力学不确定性引起的力矩扰动 ,并提出了一种基于传感器的移动机器人控制方法 .在利用线加速度传感器实时测量机器人车体加速度信号的基础上 ,实现了车体加速度反馈控制 ,实验证明了该方法的有效性 .

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In recent years, there has been a move towards the development of indirect structural health monitoring (SHM)techniques for bridges; the low-cost vibration-based method presented in this paper is such an approach. It consists of the use of a moving vehicle fitted with accelerometers on its axles and incorporates wavelet analysis and statistical pattern recognition. The aim of the approach is to both detect and locate damage in bridges while reducing the need for direct instrumentation of the bridge. In theoretical simulations, a simplified vehicle-bridge interaction model is used to investigate the effectiveness of the approach in detecting damage in a bridge from vehicle accelerations. For this purpose, the accelerations are processed using a continuous wavelet transform as when the axle passes over a damaged section, any discontinuity in the signal would affect the wavelet coefficients. Based on these coefficients, a damage indicator is formulated which can distinguish between different damage levels. However, it is found to be difficult to quantify damage of varying levels when the vehicle’s transverse position is varied between bridge crossings. In a real bridge field experiment, damage was applied artificially to a steel truss bridge to test the effectiveness of the indirect approach in practice; for this purpose a two-axle van was driven across the bridge at constant speed. Both bridge and vehicle acceleration measurements were recorded. The dynamic properties of the test vehicle were identified initially via free vibration tests. It was found that the resulting damage indicators for the bridge and vehicle showed similar patterns, however, it was difficult to distinguish between different artificial damage scenarios.

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This paper describes a ‘drive-by’ method of bridge inspection using an instrumented vehicle. Accelerometers on the vehicle are proposed as a means of detecting damage on the bridge in the time it takes for the vehicle to cross the bridge at full highway speed. For a perfectly smooth road profile, the method is shown to be feasible. Changes in bridge damping, which is an indicator of damage, are clearly visible in the acceleration signal of a quarter-car vehicle on a smooth road surface modelled using MatLab. When road profile is considered, the influence of changes in bridge damping on the vehicle acceleration signal is much less clear. However, when a half-car model is used on a road with a rough profile, it is again possible to detect changes in bridge damping, provided the vehicle has two identical axles.

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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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Federal Highway Administration, Washington, D.C.