scholarly journals Dynamic identification of a 1:5 scaled railway bogie on roller rig

2006 ◽  
Author(s):  
N. Bosso ◽  
A. Gugliotta ◽  
A. Somà
Keyword(s):  
Dynamic Identification ◽  
Roller Rig ◽  
Railway Bogie

scholarly journals Analysis on running safety considering the difference of coefficients of friction in a railway bogie (Comparison between experiment and numerical simulation of the roller-rig test)

2017 ◽  
Vol 83 (856) ◽  
pp. 17-00283-17-00283
Author(s):  
Yohei MICHITSUJI ◽  
Kakeru ISHII ◽  
Kensuke NAGASAWA ◽  
Akira MATSUMOTO ◽  
Hiroyuki OHNO ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Running Safety ◽  
Roller Rig ◽  
Railway Bogie ◽  
The Difference

Stabilization of a Two-Axle Railway Bogie: Roller Rig Tests

2017 ◽  
Vol 6 (3) ◽  
pp. 51-68
Author(s):  
J. Kalivoda ◽  
P. Bauer
Keyword(s):  
Roller Rig ◽  
Railway Bogie

Methodology and Application of Dynamic Identification System for Ecosystem Services

2010 ◽  
Vol 11 (4) ◽  
pp. 498-504
Author(s):  
Feng WU ◽  
Jinyan ZHAN ◽  
Xiangzheng DENG ◽  
Nana SHI
Keyword(s):  
Ecosystem Services ◽  
Identification System ◽  
Dynamic Identification

Tribology of rail bogie

2018 ◽  
Vol 77 (4) ◽  
pp. 230-240
Author(s):  
D. P. Markov
Keyword(s):  
Contact Fatigue ◽  
Basic Element ◽  
Difficult Problem ◽  
Railway Track ◽  
Rolling Stock ◽  
Kinematic Parameters ◽  
Approximate Estimation ◽  
Railway Bogie ◽  
Classical Calculation

Railway bogie is the basic element that determines the force, kinematic, power and other parameters of the rolling stock, and its movement in the railway track has not been studied enough. Classical calculation of the kinematic and dynamic parameters of the bogie's motion with the determination of the position of its center of rotation, the instantaneous axes of rotation of wheelsets, the magnitudes and directions of all forces present a difficult problem even in quasi-static theory. The paper shows a simplified method that allows one to explain, within the limits of one article, the main kinematic and force parameters of the bogie movement (installation angles, clearance between the wheel flanges and side surfaces of the rails), wear and contact damage to the wheels and rails. Tribology of the railway bogie is an important part of transport tribology, the foundation of the theory of wheel-rail tribosystem, without which it is impossible to understand the mechanisms of catastrophic wear, derailments, contact fatigue, cohesion of wheels and rails. In the article basic questions are considered, without which it is impossible to analyze the movement of the bogie: physical foundations of wheel movement along the rail, types of relative motion of contacting bodies, tribological characteristics linking the force and kinematic parameters of the bogie. Kinematics and dynamics of a two-wheeled bogie-rail bicycle are analyzed instead of a single wheel and a wheelset, which makes it clearer and easier to explain how and what forces act on the bogie and how they affect on its position in the rail track. To calculate the motion parameters of a four-wheeled bogie, it is represented as two two-wheeled, moving each on its own rail. Connections between them are replaced by moments with respect to the point of contact between the flange of the guide wheel and the rail. This approach made it possible to give an approximate estimation of the main kinematic and force parameters of the motion of an ideal bogie (without axes skewing) in curves, to understand how the corners of the bogie installation and the gaps between the flanges of the wheels and rails vary when moving with different speeds, how wear and contact injuries arise and to give recommendations for their assessment and elimination.

scholarly journals Autonomous Identification and Positioning of Trucks during Collaborative Forage Harvesting

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1166
Author(s):  
Wei Zhang ◽  
Liang Gong ◽  
Suyue Chen ◽  
Wenjie Wang ◽  
Zhonghua Miao ◽  
...  
Keyword(s):  
Field Experiments ◽  
Absolute Error ◽  
Identification Accuracy ◽  
Depth Image ◽  
Dynamic Identification ◽  
Random Sample Consensus ◽  
Harvesting Efficiency ◽  
Value Decomposition ◽  
Forage Harvester ◽  
Ransac Algorithm

In the process of collaborative operation, the unloading automation of the forage harvester is of great significance to improve harvesting efficiency and reduce labor intensity. However, non-standard transport trucks and unstructured field environments make it extremely difficult to identify and properly position loading containers. In this paper, a global model with three coordinate systems is established to describe a collaborative harvesting system. Then, a method based on depth perception is proposed to dynamically identify and position the truck container, including data preprocessing, point cloud pose transformation based on the singular value decomposition (SVD) algorithm, segmentation and projection of the upper edge, edge lines extraction and corner points positioning based on the Random Sample Consensus (RANSAC) algorithm, and fusion and visualization of results on the depth image. Finally, the effectiveness of the proposed method has been verified by field experiments with different trucks. The results demonstrated that the identification accuracy of the container region is about 90%, and the absolute error of center point positioning is less than 100 mm. The proposed method is robust to containers with different appearances and provided a methodological reference for dynamic identification and positioning of containers in forage harvesting.

scholarly journals Aspects of Vibration-Based Methods for the Prestressing Estimate in Concrete Beams with Internal Bonded or Unbonded Tendons

2021 ◽  
Vol 6 (6) ◽  
pp. 83
Author(s):  
Angelo Aloisio
Keyword(s):  
Elastic Modulus ◽  
Structural Reliability ◽  
Natural Frequencies ◽  
Concrete Beams ◽  
Experimental Testing ◽  
Hybrid Approach ◽  
Reliable Estimate ◽  
Axial Deformation ◽  
Dynamic Identification ◽  
Concrete Girders

The estimate of internal prestressing in concrete beams is essential for the assessment of their structural reliability. Many scholars have tackled multiple and diverse methods to estimate the measurable effects of prestressing. Among them, many experimented with dynamics-based techniques; however, these clash with the theoretical independence of the natural frequencies of the forces of internally prestressed beams. This paper examines the feasibility of a hybrid approach based on dynamic identification and the knowledge of the elastic modulus. Specifically, the author considered the effect of the axial deformation on the beam length and the weight per unit of volume. It is questioned whether the uncertainties related to the estimate of the elastic modulus and the first natural frequency yield reasonable estimates of the internal prestressing. The experimental testing of a set of full-scale concrete girders with known design prestressing supports a discussion about its practicability. The author found that the uncertainty in estimating the natural frequencies and elastic modulus significantly undermines a reliable estimate of the prestressing state.

scholarly journals Intelligent Dynamic Identification Technique of Industrial Products in a Robotic Workplace

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1797
Author(s):  
Ján Vachálek ◽  
Dana Šišmišová ◽  
Pavol Vašek ◽  
Jan Rybář ◽  
Juraj Slovák ◽  
...  
Keyword(s):  
Machine Learning ◽  
Control Charts ◽  
Nearest Neighbor ◽  
Learning Algorithm ◽  
Conveyor Belt ◽  
Standard Uncertainty ◽  
K Nearest Neighbor ◽  
Industrial Products ◽  
Dynamic Identification ◽  
Identification Technique

The article deals with aspects of identifying industrial products in motion based on their color. An automated robotic workplace with a conveyor belt, robot and an industrial color sensor is created for this purpose. Measured data are processed in a database and then statistically evaluated in form of type A standard uncertainty and type B standard uncertainty, in order to obtain combined standard uncertainties results. Based on the acquired data, control charts of RGB color components for identified products are created. Influence of product speed on the measuring process identification and process stability is monitored. In case of identification uncertainty i.e., measured values are outside the limits of control charts, the K-nearest neighbor machine learning algorithm is used. This algorithm, based on the Euclidean distances to the classified value, estimates its most accurate iteration. This results into the comprehensive system for identification of product moving on conveyor belt, where based on the data collection and statistical analysis using machine learning, industry usage reliability is demonstrated.

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