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Related Concept Videos

Relative Motion Analysis using Rotating Axes-Problem Solving01:29

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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
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The first two kinematic equations have time as a variable, but the third kinematic equation is independent of time. This equation expresses final velocity as a function of the acceleration and distance over which it acts. The fourth kinematic equation does not have an acceleration term and provides the final position of the object at time t in terms of the initial and final velocities. This equation is useful when the value of the constant acceleration is unknown.
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The second kinematic equation expresses the final position of an object in terms of its initial position, the distance traveled with the initial constant velocity, and the distance traveled due to a change in velocity. Similar to the first kinematic equation, this equation is also only valid when the acceleration is constant throughout the motion of an object.
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When an object moves with constant acceleration, the velocity of the object changes at a constant rate throughout the motion. The kinematic equations of motions are derived for such cases where the acceleration of the object is constant. The first kinematic equation gives an insight into the relationship between velocity, acceleration, and time. We can see, for example:
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A Track Geometry Measuring System Based on Multibody Kinematics, Inertial Sensors and Computer Vision.

José L Escalona1, Pedro Urda1, Sergio Muñoz2

  • 1Department of Mechanical and Manufacturing Engineering, University of Seville, Seville 41092, Spain.

Sensors (Basel, Switzerland)
|January 27, 2021
PubMed
Summary

A new Track Geometry Measuring System (TGMS) accurately calculates railway track irregularities using advanced kinematics and sensor data. This system, tested on a scaled model, shows good agreement with traditional measurement methods.

Keywords:
computer visioninertial sensorsmultibody dynamicsrail vehiclestrack irregularities

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Area of Science:

  • Railway Engineering
  • Geomatics
  • Mechanical Engineering

Background:

  • Accurate measurement of track geometric irregularities is crucial for railway safety and maintenance.
  • Existing methods may have limitations in real-time data acquisition and comprehensive analysis.
  • Advancements in sensor technology and computational methods offer opportunities for improved track monitoring.

Purpose of the Study:

  • To describe the kinematics for calculating track geometric irregularities using a novel Track Geometry Measuring System (TGMS).
  • To detail the components and methodology of the TGMS, integrating multibody dynamics and computer vision.
  • To validate the TGMS's performance by comparing its measurements with an established accurate method.

Main Methods:

  • Utilized multibody dynamics principles for kinematic description of vehicle-track interaction.
  • Integrated data from an inertial measuring unit (IMU), video cameras, and an encoder for sensor fusion.
  • Developed formulas to derive track irregularities (gauge, cross-level, alignment, vertical profile) from sensor inputs.

Main Results:

  • The TGMS successfully calculated track geometric irregularities based on sensor data and kinematic models.
  • Experimental validation on a 1:10 scaled vehicle and track demonstrated the system's functionality.
  • Results from the TGMS showed good agreement when compared to measurements obtained via an alternative, accurate method.

Conclusions:

  • The described kinematics and the TGMS provide a viable method for calculating railway track geometric irregularities.
  • The system's performance indicates its potential for practical application in railway maintenance and monitoring.
  • The integration of multibody dynamics and sensor data processing offers a robust approach to track geometry assessment.