Wheel–rail dynamic interaction caused by wheel out-of-roundness and its transmission between wheelsets

2021 ◽  
pp. 095440972110165
Author(s):  
Gongquan Tao ◽  
Mengqi Liu ◽  
Qinglin Xie ◽  
Zefeng Wen
Keyword(s):  
Dynamic Interaction ◽  
High Order ◽  
Vibration Measurement ◽  
Bending Vibration ◽  
Vertical Stiffness ◽  
Finite Element Software ◽  
Measurement Results ◽  
Stiffness And Damping Coefficient ◽  
Stiffness And Damping ◽  
Low Order

High-order and low-order wheel out-of-roundness (OOR) often occur on metro train wheels, which can intensify the wheel–rail dynamic interaction. A vehicle–track rigid-flexible coupled dynamics model is built through combining the dynamics software SIMPACK with the finite element software ANSYS, which is validated by field vibration measurement results of vehicle and track. Two adjacent vehicles with two two-axle bogies for each one are considered in the model. The wheel–rail interactions caused by high-order and low-order wheel OOR are investigated. The influence of the wheel–rail interaction caused by wheel OOR on one wheelset on wheel–rail interactions at other 7 wheelsets is explored. The results show that the wheel OOR can excite the first bending vibration of the wheelset and the P2 resonance at a normal operating speed, which can result in a considerable increase of the wheel–rail dynamic interaction and wheelset vibration. The wheel–rail dynamic interaction can be transmitted from the polygonised wheelset to another wheelset of the same bogie through the rail. However, the transmission is negligible from the path of the bogie. The amplitude of wheel OOR has no effect on the transmission ratio of wheel–rail dynamic interaction, but the vertical stiffness and damping coefficient of fasteners greatly influence the transmission. The two wheelsets on the same bogie should be re-profiled simultaneously if the radial run-out for one wheelset exceeds the limit and for the other does not. The effects of vibration transmission between wheelsets and track flexibility need to be taken into account in a model for predicting the development of wheel OOR.

Design and experimental research of a magnetorheological elastomer isolator working in squeeze/elongation–shear mode

2017 ◽  
Vol 29 (7) ◽  
pp. 1418-1429 ◽  
Author(s):  
Yu Tao ◽  
Xiaoting Rui ◽  
Fufeng Yang ◽  
Gangli Chen ◽  
Leixiang Bian ◽  
...  
Keyword(s):  
Relative Increase ◽  
Shear Mode ◽  
Magnetorheological Elastomer ◽  
Magnetorheological Elastomers ◽  
Vertical Stiffness ◽  
Shear Modes ◽  
Strain Relationship ◽  
Stiffness And Damping Coefficient ◽  
Stiffness And Damping ◽  
Relationship Of

Due to the properties of controllable stiffness and damping, a novel isolator based on magnetorheological elastomers is introduced in this article. According to the experimental results, the initial vertical stiffness and damping coefficient of the magnetorheological elastomer isolator are 1.14 × 106 N/m and 495.8 N s/m, respectively. The relative increase in stiffness and damping is 66.57% and 45.55%, respectively. The isolation transmissibility and root mean square of acceleration response are reduced by 41.2% and 65.3%, respectively. To describe the magnetic-induced stress–strain relationship of the anisotropic magnetorheological elastomers, a theoretical model is presented as magnetorheological elastomers working in squeeze/elongation and shear modes simultaneously. Then, the stiffness formula relating to the magnetic field, strain, and the other demanding parameters is deduced. The analytical results of the stiffness formula are fairly in agreement with the experimental data.

STUDY ON THE VERTICAL STIFFNESS AND DAMPING COEFFICIENT OF TRACTOR TIRE USING SEMI-EMPIRICAL MODEL

2013 ◽  
Vol 83 (5) ◽  
Author(s):  
Đỗ Minh Cường ◽  
Zhu shi Hong ◽  
Đinh Vương Hùng ◽  
Nguyễn Thị Ngọc
Keyword(s):  
Damping Coefficient ◽  
Inflation Pressure ◽  
Vertical Stiffness ◽  
Damping Characteristics ◽  
Increasing Trend ◽  
Tire Stiffness ◽  
Stiffness And Damping Coefficient ◽  
Stiffness And Damping ◽  
Semi Empirical ◽  
Rear Tire

An experiment was conducted to determine the vertical stiffness and damping characteristics of tractor tires for the aim of simulation and design of the tractor suspension system. Three kinds of tractor tires were selected to measure vertical stiffness and damping coefficient by using Free-Vibration Logarithm Decay Method at five levels of tire inflation pressures and two tire loads. The results show that, for all kinds of tire, the stiffness was linearly increased by increasing tire inflation pressure whereas the damping coefficient decreased when tire inflation pressure increased. The stiffness and damping coefficient of tractor tires also depend on the tire size, the structure of tires as front tire or rear tire. Additionally, the damping coefficient shows the increasing trend while the increase in tire stiffness is not clear by increasing tire load. The results also reveal that the appropriate distribution of tire load, tire inflation pressure and tire size can change significantly the tire stiffness and damping coefficient to control tractor vibration. Keywords: Tire stiffness; Damping coefficient; Tractor tire; Tire inflation pressure.

Polynomial Moving Fitting Method for Edge Identification

2011 ◽  
Vol 308-310 ◽  
pp. 2560-2564 ◽  
Author(s):  
Xiang Rong Yuan
Keyword(s):  
Edge Detection ◽  
Curve Fitting ◽  
Polynomial Function ◽  
High Order ◽  
Polynomial Fitting ◽  
Fitting Method ◽  
Order Polynomial ◽  
Better Than ◽  
Low Order

A moving fitting method for edge detection is proposed in this work. Polynomial function is used for the curve fitting of the column of pixels near the edge. Proposed method is compared with polynomial fitting method without sub-segment. The comparison shows that even with low order polynomial, the effects of moving fitting are significantly better than that with high order polynomial fitting without sub-segment.

Characteristics in Response Integration and Bifurcation of a Forced Duffing Oscillator

2007 ◽  
Author(s):  
Jang-Der Jeng ◽  
Yuan Kang ◽  
Yeon-Pun Chang ◽  
Shyh-Shyong Shyr
Keyword(s):  
Applied Sciences ◽  
Phase Plane ◽  
Duffing Oscillator ◽  
High Order ◽  
Chaotic Motions ◽  
Integration Algorithm ◽  
High Order Harmonic ◽  
Stiffness And Damping

The Duffing oscillator is well-known models of nonlinear system, with applications in many fields of applied sciences and engineering. In this paper, a response integration algorithm is proposed to analyze high-order harmonic and chaotic motions in this oscillator for modeling rotor excitations. This method numerically integrates the distance between state trajectory and the origin in the phase plane during a specific period and predicted intervals with excitation periods. It provides a quantitative characterization of system responses and can replace the role of the traditional stroboscopic technique (Poincare´ section method) to observe bifurcations and chaos of the nonlinear oscillators. Due to the signal response contamination of system, thus it is difficult to identify the high-order responses of the subharmonic motion because of the sampling points on Poincare´ map too near each other. Even the system responses will be made misjudgments. Combining the capability of precisely identifying period and constructing bifurcation diagrams, the advantages of the proposed response integration method are shown by case studies. Applying this method, the effects of the change in the stiffness and the damping coefficients on the vibration features of a Duffing oscillator are investigated in this paper. From simulation results, it is concluded that the stiffness and damping of the system can effectively suppress chaotic vibration and reduce vibration amplitude.

Numerical analysis of the dynamic performance of aerostatic thrust bearings with different restrictors

2018 ◽  
Vol 233 (3) ◽  
pp. 406-423 ◽  
Author(s):  
Hailong Cui ◽  
Yang Wang ◽  
Xiaobin Yue ◽  
Yifei Li ◽  
Zhengyi Jiang
Keyword(s):  
Load Capacity ◽  
Dynamic Stiffness ◽  
Dynamic Performance ◽  
Dynamic Mesh ◽  
Eccentricity Ratio ◽  
Thrust Bearings ◽  
Stiffness And Damping Coefficient ◽  
Stiffness And Damping ◽  
The Impact ◽  
The Relationship

This study utilizes a dynamic mesh technology to investigate the dynamic performance of aerostatic thrust bearings with orifice restrictor, multiple restrictors, and porous restrictor. An experiment, which investigates the bearing static load capacity, was carried out to verify the calculation accuracy of dynamic mesh technology. Further, the impact of incentive amplitude, incentive frequency, axial eccentricity ratio, and non-flatness on the bearing dynamic performance was also studied. The results show incentive amplitude effect can be ignored at the condition of amplitude less than 5% film thickness, while the relationship between dynamic characteristics and incentive frequency presented a strong nonlinear relationship in the whole frequency range. The change law of dynamic stiffness and damping coefficient for porous restrictor was quite different from orifice restrictor and multiple restrictors. The bearing dynamic performance increased significantly with the growth of axial eccentricity ratio, and the surface non-flatness enhanced dynamic performance of aerostatic thrust bearings.

scholarly journals Development of a new test rig for the analysis of hydrodynamic bearings for rotors of microGT

2019 ◽  
Vol 113 ◽  
pp. 03002
Author(s):  
Carlo Alberto Niccolini Marmont Du Haut Champ ◽  
Fabrizio Stefani ◽  
Paolo Silvestri
Keyword(s):  
Experimental Data ◽  
Finite Element ◽  
Gas Turbines ◽  
Dynamic Interaction ◽  
Journal Bearings ◽  
Radial Clearance ◽  
Test Rig ◽  
Small Clearance ◽  
Stiffness And Damping ◽  
Good Agreement

The aim of the present work is to design a test rig suited to investigate the dynamic interaction between rotor and hydrodynamic journal bearings in micro gas turbines (microGT), i.e. with reference to small bearings (diameter in the order of ten millimeters). Particularly, the device is capable of measuring the journal location. Therefore, the journal motion due to rotor vibrations can be displayed, in order to assess performance as well as stiffness and damping of the bearings. The new test rig is based on Bently Nevada Rotor Kit (RK), but substantial modifications are carried out. Indeed, the relative radial clearance of the original RK bearings is about 2/100, while it is in the order of 1/1000 in industrial bearings. Therefore, the same RK bearings are employed in the new test rig, but a new shaft has been designed in order to reduce the original clearance. The new shaft enables us to study the bearing behaviour for different clearances, as it is equipped with interchangeable journals. The experimental data yielded by the new test rig are compared with numerical results. These are obtained by means of a suitable finite element (FEM) code developed by our research group. It allows the Thermo Elasto-HydroDynamic (TEHD) analysis of the bearing in static and dynamic conditions. In the present paper, bearing static performances are analysed in order to assess the reliability of the journal location predictions by comparing numerical and experimental results. Such comparisons are presented for both large and small clearance bearings of original and modified RK, respectively. Good agreement is found only for the modified RK equipped with small clearance bearings (relative radial clearance equal to 8/1000). Nevertheless, rotor alignment is quite difficult with small clearance bearings and a completely new test rig is designed for future experiments.

A correlation-based model order reduction approach for a diesel engine NOx and brake mean effective pressure dynamic model using machine learning

2020 ◽  
pp. 146808742093694
Author(s):  
Armin Norouzi ◽  
Masoud Aliramezani ◽  
Charles Robert Koch
Keyword(s):  
Support Vector Machine ◽  
Model Order Reduction ◽  
Order Reduction ◽  
High Order ◽  
Support Vector ◽  
Effective Pressure ◽  
Reduction Algorithm ◽  
Order Model ◽  
Model Order ◽  
Low Order

A correlation-based model order reduction algorithm is developed using support vector machine to model [Formula: see text] emission and break mean effective pressure of a medium-duty diesel engine. The support vector machine–based model order reduction algorithm is used to reduce the number of features of a 34-feature full-order model by evaluating the regression performance of the support vector machine–based model. Then, the support vector machine–based model order reduction algorithm is used to reduce the number of features of the full-order model. Two models for [Formula: see text] emission and break mean effective pressure are developed via model order reduction, one complex model with high accuracy, called high-order model, and the other with an acceptable accuracy and a simple structure, called low-order model. The high-order model has 29 features for [Formula: see text] and 20 features for break mean effective pressure, while the low-order model has nine features for [Formula: see text] and six features for break mean effective pressure. Then, the steady-state low-order model and high-order model are implemented in a nonlinear control-oriented model. To verify the accuracy of nonlinear control-oriented model, a fast response electrochemical [Formula: see text] sensor is used to experimentally study the engine transient [Formula: see text] emissions. The high-order model and low-order model support vector machine models of [Formula: see text] and break mean effective pressure are compared to a conventional artificial neural network with one hidden layer. The results illustrate that the developed support vector machine model has shorter training times (5–14 times faster) and higher accuracy especially for test data compared to the artificial neural network model. A control-oriented model is then developed to predict the dynamic behavior of the system. Finally, the performance of the low-order model and high-order model is evaluated for different rising and falling input transients at four different engine speeds. The transient test results validate the high accuracy of the high-order model and the acceptable accuracy of low-order model for both [Formula: see text] and break mean effective pressure. The high-order model is proposed as an accurate virtual plant while the low-order model is suitable for model-based controller design.

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