900 resultados para Vehicle Parts.


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This paper presents a robust fixed order H2controller design using strengthened discrete optimal projection equations, which approximate the first order necessary optimality condition. The novelty of this work is the application of the robust H2controller to a micro aerial vehicle named Sarika2 developed in house. The controller is designed in discrete domain for the lateral dynamics of Sarika2 in the presence of low frequency atmospheric turbulence (gust) and high frequency sensor noise. The design specification includes simultaneous stabilization, disturbance rejection and noise attenuation over the entire flight envelope of the vehicle. The resulting controller performance is comprehensively analyzed by means of simulation

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The report talks about the implementation of Vehicle Detection tool using opensource software - WxPython. The main functionality of this tool includes collection of data, plotting of magnetometer data and the count of the vehicles detected. The report list about how installation process and various functionality of the tool.

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Precision inspection of manufactured components having multiple complex surfaces and variable tolerance definition is an involved, complex and time-consuming function. In routine practice, a jig is used to present the part in a known reference frame to carry out the inspection process. Jigs involve both time and cost in their development, manufacture and use. This paper describes 'as is where is inspection' (AIWIN), a new automated inspection technique that accelerates the inspection process by carrying out a fast registration procedure and establishing a quick correspondence between the part to inspect and its CAD geometry. The main challenge in doing away with a jig is that the inspection reference frame could be far removed from the CAD frame. Traditional techniques based on iterative closest point (ICP) or Newton methods require either a large number of iterations for convergence or fail in such a situation. A two-step coarse registration process is proposed to provide a good initial guess for a modified ICP algorithm developed earlier (Ravishankar et al., Int J Adv Manuf Technol 46(1-4):227-236, 2010). The first step uses a calibrated sphere for local hard registration and fixing the translation error. This transformation locates the centre for the sphere in the CAD frame. In the second step, the inverse transformation (involving pure rotation about multiple axes) required to align the inspection points measured on the manufactured part with the CAD point dataset of the model is determined and enforced. This completes the coarse registration enabling fast convergence of the modified ICP algorithm. The new technique has been implemented on complex freeform machined components and the inspection results clearly show that the process is precise and reliable with rapid convergence. © 2011 Springer-Verlag London Limited.

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Wheel bearings play a crucial role in the mobility of a vehicle by minimizing motive power loss and providing stability in cornering maneuvers. Detailed engineering analysis of a wheel bearing subsystem under dynamic conditions poses enormous challenges due to the nonlinearity of the problem caused by multiple factional contacts between rotating and stationary parts and difficulties in prediction of dynamic loads that wheels are subject to. Commonly used design methodologies are based on equivalent static analysis of ball or roller bearings in which the latter elements may even be represented with springs. In the present study, an advanced hybrid approach is suggested for realistic dynamic analysis of wheel bearings by combining lumped parameter and finite element modeling techniques. A validated lumped parameter representation serves as an efficient tool for the prediction of radial wheel load due to ground reaction which is then used in detailed finite element analysis that automatically accounts for contact forces in an explicit formulation.

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The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements. The problem with performing a combined cross-functional optimization is the time associated with running such CAE algorithms that can provide a single optimal solution for heterogeneous areas such as NVH and crash safety. In the present paper, a practical MDO methodology is suggested that can be applied to weight optimization of automotive body structures by specifying constraints on frequency and crash performance. Because of the reduced number of cases to be analyzed for crash safety in comparison with other MDO approaches, the present methodology can generate a single size-optimized solution without having to take recourse to empirical techniques such as response surface-based prediction of crash performance and associated successive response surface updating for convergence. An example of weight optimization of spaceframe-based BIW of an aluminum-intensive vehicle is given to illustrate the steps involved in the current optimization process.

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We present the selective sensing of multiple transition metal ions in water using a synthetic single probe. The probe is made up of pyrene and pyridine as signaling and interacting moiety, respectively. The sensor showed different responses toward metal ions just by varying the medium of detection. In organic solvent (acetonitrile), the probe showed selective detection of Hg2+ ion. In water, the fluorescence quenching was observed with three metal ions, Cu2+, Hg2+, and Ni2+. Further, just by varying the surface charge on the micellar aggregates, the probe could detect and discriminate the above-mentioned three different toxic metal ions appropriately. In neutral micelles (Brij 58), the probe showed a selective interaction with Hg2+ ion as observed in acetonitrile medium. However, in anionic micellar medium (sodium dodecyl sulfate, SDS), the probe showed changes with both Cu2+ and Ni2+. under UV-vis absorption spectroscopy. The discrimination between these two ions was achieved by recording their emission spectra, where it showed selective quenching with Cu2+.

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Moving shadow detection and removal from the extracted foreground regions of video frames, aim to limit the risk of misconsideration of moving shadows as a part of moving objects. This operation thus enhances the rate of accuracy in detection and classification of moving objects. With a similar reasoning, the present paper proposes an efficient method for the discrimination of moving object and moving shadow regions in a video sequence, with no human intervention. Also, it requires less computational burden and works effectively under dynamic traffic road conditions on highways (with and without marking lines), street ways (with and without marking lines). Further, we have used scale-invariant feature transform-based features for the classification of moving vehicles (with and without shadow regions), which enhances the effectiveness of the proposed method. The potentiality of the method is tested with various data sets collected from different road traffic scenarios, and its superiority is compared with the existing methods. (C) 2013 Elsevier GmbH. All rights reserved.

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This paper presents classification, representation and extraction of deformation features in sheet-metal parts. The thickness is constant for these shape features and hence these are also referred to as constant thickness features. The deformation feature is represented as a set of faces with a characteristic arrangement among the faces. Deformation of the base-sheet or forming of material creates Bends and Walls with respect to a base-sheet or a reference plane. These are referred to as Basic Deformation Features (BDFs). Compound deformation features having two or more BDFs are defined as characteristic combinations of Bends and Walls and represented as a graph called Basic Deformation Features Graph (BDFG). The graph, therefore, represents a compound deformation feature uniquely. The characteristic arrangement of the faces and type of bends belonging to the feature decide the type and nature of the deformation feature. Algorithms have been developed to extract and identify deformation features from a CAD model of sheet-metal parts. The proposed algorithm does not require folding and unfolding of the part as intermediate steps to recognize deformation features. Representations of typical features are illustrated and results of extracting these deformation features from typical sheet metal parts are presented and discussed. (C) 2013 Elsevier Ltd. All rights reserved.

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This paper presents the design and development of a novel optical vehicle classifier system, which is based on interruption of laser beams, that is suitable for use in places with poor transportation infrastructure. The system can estimate the speed, axle count, wheelbase, tire diameter, and the lane of motion of a vehicle. The design of the system eliminates the need for careful optical alignment, whereas the proposed estimation strategies render the estimates insensitive to angular mounting errors and to unevenness of the road. Strategies to estimate vehicular parameters are described along with the optimization of the geometry of the system to minimize estimation errors due to quantization. The system is subsequently fabricated, and the proposed features of the system are experimentally demonstrated. The relative errors in the estimation of velocity and tire diameter are shown to be within 0.5% and to change by less than 17% for angular mounting errors up to 30 degrees. In the field, the classifier demonstrates accuracy better than 97.5% and 94%, respectively, in the estimation of the wheelbase and lane of motion and can classify vehicles with an average accuracy of over 89.5%.

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A wobble instability is one of the major problems of a three-wheeled vehicle commonly used in India, and these instabilities are of great interest to industry and academia. In this paper, we studied this instability using a multi-body dynamic model and with experiments conducted on a prototype three-wheeled vehicle on a test track. The multi-body dynamic model of a three-wheeled vehicle is developed using the commercial software ADAMS/Car. In an initial model, all components including main structures such as the frame, the steering column and the rear forks are assumed to be rigid bodies. A linear eigenvalue analysis, which is carried out at different speeds, reveals a mode that has predominantly a steering oscillation, also called a wobble mode, with a frequency of around 5-6Hz. The analysis results shows that the damping of this mode is low but positive up to the maximum speed of the three-wheeled vehicle. However, the experimental study shows that the mode is unstable at speeds below 8.33m/s. To predict and study this instability in detail, a more refined model of the three-wheeled vehicle, with flexibilities of three important bodies, was constructed in ADAMS/Car. With flexible bodies, three modes of a steering oscillation were observed. Two of these are well damped and the other is lightly damped with negative damping at lower speeds. Simulation results with flexibility incorporated show a good match with the instability observed in the experimental studies. Further, we investigated the effect of each flexible body and found that the flexibility of the steering column is the major contributor for wobble instability and is similar to the wheel shimmy problem in aircraft.

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n this paper, three-axis autopilot of a tactical flight vehicle has been designed for surface to air application. Both nonlinear and linear design synthesis and analysis have been carried out pertaining to present flight vehicle. Lateral autopilot performance has been compared by tracking lateral acceleration components along yaw and pitch plane at higher angles of attack in presence of side force and aerodynamic nonlinearity. The nonlinear lateral autopilot design is based on dynamic inversion and time scale separation principle. The linear lateral autopilot design is based on three-loop topology. Roll autopilot robustness performance has been enhanced against unmodeled roll disturbances by backstepping technique. Complete performance comparison results of both nonlinear and linear controller based on six degrees of freedom simulation along with stability and robustness studies with respect to plant parameter variation have been discussed in the paper.