Research on the Simulation of Random Road Excitation in Time-Domain

2015 ◽  
Vol 738-739 ◽  
pp. 508-511 ◽  
Author(s):  
Yue Feng Zhu ◽  
Li Wang
Keyword(s):  
Dynamic Loads ◽  
Ar Model ◽  
Road Transportation ◽  
The Road ◽  
Pavement Roughness ◽  
Road Roughness ◽  
Moving Vehicles ◽  
Road Excitation ◽  
Increasing Demand ◽  
The Given

With the development of national economy and the increasing demand for the road transportation, the vehicles are widely used. The dynamic loads imposed by moving vehicles have variations due to the surface roughness and the larger dynamic loads can affect the pavement performance and life. In order to improve the accuracy of the reconstruction of the road roughness, the time series model—AR model was established based on the given standard pavement roughness PSD which can provide the theory conditions of vibration control and the interaction between vehicles and road.

scholarly journals METROLOGICAL SUPPORT OF GEODETIC WORKS IN THE ROAD ROUGHNESS MEASURING

2021 ◽  
Vol 6 (166) ◽  
pp. 130-133
Author(s):  
H. Sarkisian ◽  
V. Tymoshevskyi ◽  
S. Urdzik
Keyword(s):  
Metrological Support ◽  
Dynamic Load ◽  
Road Maintenance ◽  
Rigid Pavement ◽  
The Road ◽  
Pavement Roughness ◽  
Road Roughness ◽  
Accuracy Of Measurements ◽  
On The Road

Most of the transport and operational indicators that directly affect the road roughness depend on the roughness of coverage. Therefore, the control and timely monitoring of the road roughness is an extremely important issue that needs the attention of road maintenance services. At monitoring of the road roughness it is most expedient to use a technique of leveling of a covering. The method of leveling the coating provides more detailed information about the coating and allows you to determine the smallest deformations on the road coating, which may be at the first stage of their development, especially at that stage of their development, and show roughness and various parameters. One of the main tasks of measurements in the process of performing geodetic works is not only to obtain the measurement result, but also to assess its reliability. The required quality of instrumental measurement can not be achieved without adhering to the principles of unity and the required accuracy of measurements, so much attention should be paid to the metrological support of geodetic works. The purpose of this article is to analyze the metrological support of geodetic works in determining the pavement roughness and substantiation of the required accuracy of measuring the non-rigid pavement roughness. On the basis of dependences for determining the coefficient of dynamic load on pavement and the correlation between the pavement roughness and the coefficient of dynamic load and on the basis of experimental data, the necessary accuracy of measuring the non-rigid pavement roughness is substantiated. Based on the analysis, it was found that the accuracy of determining the height of the irregularities should not exceed 0.5 mm, for which it is necessary to use optical or electron-optical levels.

Road Flatness Detection Using Permutation Entropy (PE)

2014 ◽  
Vol 721 ◽  
pp. 420-423 ◽  
Author(s):  
Qing Chao Wang ◽  
Wan Qing Song ◽  
Jian Kai Liang
Keyword(s):  
Detection Method ◽  
Permutation Entropy ◽  
Data Array ◽  
The Road ◽  
Pavement Roughness ◽  
Road Roughness

Aimed at checking the signal’s nonlinearity and instability of road flatness, in order to get a more convenient and significant approach to verify the pavement smoothness, a road roughness detection method on the base of Permutation Entropy (PE) algorithm is put forward. This method firstly relevantly deals with the collecting road signals, then getting Permutation Entropy (PE), and reaches relevant drawing data array. By the use of Matlab drawing, the road roughness can be proved according to the PE. The experiment turns out that Permutation Entropy (PE) algorithm has an effective and convenient effect on checking road flatness, and it is more obvious to show pavement roughness compared the method of the Holder index.

Analysis of motorcycle vibration comfort based on rigid-flexible coupling model

2020 ◽  
Vol 51 (6) ◽  
pp. 110-115
Author(s):  
Yu Feng ◽  
Xie Jun
Keyword(s):  
Low Frequency ◽  
Coupling Model ◽  
Design Stage ◽  
Vibration Level ◽  
Subjective Impression ◽  
Flexible Coupling ◽  
The Road ◽  
Low Frequency Vibration ◽  
Road Roughness ◽  
Road Excitation

Based on the rigid-flexible coupling model, this article utilized ADAMS to establish a dynamics model of a motorcycle, in which the engine excitation and road excitation were determined. According to the ISO5349 and ISO2631 standards, the vibration of the motorcycle at 60 km/h was analyzed. The results showed that the high-frequency vibration of the engine accounted for the most vibration at the handle when driving on the B-class road at 60 km/h, and the vibration level was uncomfortable. In contrast, the low-frequency vibration of the road roughness was the main excitation of the cushion vibration, and the vibration level was relatively uncomfortable. These results were in accordance with the subjective impression on human observers, indicating that the vibration comfort analysis method based on the rigid-flexible coupling model was correct and effective to provide theoretical basis for the subsequent improvement and modification early in the design stage.

Mechanistic Roughness Model Based on Vehicle-Pavement Interaction

2000 ◽  
Vol 1699 (1) ◽  
pp. 114-120 ◽  
Author(s):  
Mofreh F. Saleh ◽  
Michael S. Mamlouk ◽  
Emmanuel B. Owusu-Antwi
Keyword(s):  
Vehicle Dynamics ◽  
Performance Model ◽  
Dynamic Force ◽  
The Road ◽  
Pavement Roughness ◽  
Roughness Model ◽  
Road Roughness ◽  
Dynamic Forces ◽  
Force Profile ◽  
Level Performance

A mechanistic roughness performance model that takes into account vehicle dynamics was developed for use in flexible pavement design and evaluation. The model was developed in the form of a relation between roughness and number of load repetitions, axle load, and asphalt layer thickness. The model is completely mechanistic and uses vehicle dynamics analysis to estimate the dynamic force profile and finite element structural analysis to estimate the change of pavement surface roughness for each load repetition. The model makes use of the fact that pavement roughness changes the magnitude of the vehicle dynamic forces applied on the pavement and that the dynamic forces change the road roughness. The developed mechanistic roughness performance model can be used to estimate the 80-kN (18-kip) equivalent single-axle load for mixed traffic. The model can also be used to design pavement so that it will last for a certain number of load repetitions before reaching a predetermined roughness level. Performance-based specifications can be developed using the methodology presented in this study. The model has been calibrated and verified with field data elsewhere.

scholarly journals Estimating Pavement Roughness by Fusing Color and Depth Data Obtained from an Inexpensive RGB-D Sensor

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1655 ◽  
Author(s):  
Ahmadreza Mahmoudzadeh ◽  
Amir Golroo ◽  
Mohammad Jahanshahi ◽  
Sayna Firoozi Yeganeh
Keyword(s):  
Surface Defects ◽  
Cost Effective ◽  
Pavement Management ◽  
Outdoor Environment ◽  
Primary Data ◽  
International Roughness Index ◽  
The Road ◽  
Pavement Roughness ◽  
Power Spectral ◽  
Road Roughness

Measuring pavement roughness and detecting pavement surface defects are two of the most important tasks in pavement management. While existing pavement roughness measurement approaches are expensive, the primary aim of this paper is to use a cost-effective and sufficiently accurate RGB-D sensor to estimate the pavement roughness in the outdoor environment. An algorithm is proposed to process the RGB-D data and autonomously quantify the road roughness. To this end, the RGB-D sensor is calibrated and primary data for estimating the pavement roughness are collected. The collected depth frames and RGB images are registered to create the 3D road surfaces. We found that there is a significant correlation between the estimated International Roughness Index (IRI) using the RGB-D sensor and the manual measured IRI using rod and level. By considering the Power Spectral Density (PSD) analysis and the repeatability of measurement, the results show that the proposed solution can accurately estimate the different pavement roughness.

A Study on Job Satisfaction among Tamil Nadu State Transport Corporation (TNSTC) Employees at Tiruvarur Branch

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 230-242
Author(s):  
M. Ganesan, K ◽  
K. Veerakumar ◽  
N. R Vembu ◽  
Dr. M. K Durgamani ◽  
Dr. Renuka
Keyword(s):  
Job Satisfaction ◽  
Job Stress ◽  
Tamil Nadu ◽  
Heavy Traffic ◽  
Road Transportation ◽  
The Road ◽  
Tamil Nadu State ◽  
On The Road ◽  
Day By Day ◽  
Labour Turnover

Job satisfaction is an important factor for employees working in formal and informal sector. The job is small or big, permanent or temporary, risky or non-risky, job satisfaction is important. It is the mental feeling which drives the employees to excel. Job satisfaction is a combination of psychological, physiological and environmental circumstances. A satisfied employee is a contented and happy human being. The labour turnover depends upon job satisfaction. Even highly paid employees quit the job when they are not satisfied with the job. Road transportation in Tamilnadu is growing day by day. Job stress in the road transportation is very high due to increase in number of vehicle playing on the road and heavy traffic. The drivers and conductors working in public transport corporation are suffering from high job stress. If drivers and conductors are not satisfied with their job which leads to mental stresses and affects the productivity and also creates accidents. In this present study the researchers made an attempt to study the level of job satisfaction among the drivers and conductors who are working in the Tamilnadu State Transport Corporation (TNSTC). The study reveals the expectations of drivers and conductors working in TNSTC with regards to the attributes like salary, promotion and fringe benefits etc., are satisfactory and not detrimental. 

scholarly journals Road Roughness Estimation Based on the Vehicle Frequency Response Function

Actuators ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 89
Author(s):  
Qingxia Zhang ◽  
Jilin Hou ◽  
Zhongdong Duan ◽  
Łukasz Jankowski ◽  
Xiaoyang Hu
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Gaussian White Noise ◽  
Estimation Method ◽  
Time Shift ◽  
Ride Quality ◽  
The Road ◽  
Road Roughness ◽  
Measured Response

Road roughness is an important factor in road network maintenance and ride quality. This paper proposes a road-roughness estimation method using the frequency response function (FRF) of a vehicle. First, based on the motion equation of the vehicle and the time shift property of the Fourier transform, the vehicle FRF with respect to the displacements of vehicle–road contact points, which describes the relationship between the measured response and road roughness, is deduced and simplified. The key to road roughness estimation is the vehicle FRF, which can be estimated directly using the measured response and the designed shape of the road based on the least-squares method. To eliminate the singular data in the estimated FRF, the shape function method was employed to improve the local curve of the FRF. Moreover, the road roughness can be estimated online by combining the estimated roughness in the overlapping time periods. Finally, a half-car model was used to numerically validate the proposed methods of road roughness estimation. Driving tests of a vehicle passing over a known-sized hump were designed to estimate the vehicle FRF, and the simulated vehicle accelerations were taken as the measured responses considering a 5% Gaussian white noise. Based on the directly estimated vehicle FRF and updated FRF, the road roughness estimation, which considers the influence of the sensors and quantity of measured data at different vehicle speeds, is discussed and compared. The results show that road roughness can be estimated using the proposed method with acceptable accuracy and robustness.

FPGA and ASIC implementation of the algorithm for traffic monitoring in urban areas

2011 ◽  
Vol 59 (2) ◽  
pp. 137-140 ◽  
Author(s):  
S. Szczepański ◽  
M. Wöjcikowski ◽  
B. Pankiewicz ◽  
M. KŁosowski ◽  
R. Żaglewski
Keyword(s):  
Urban Areas ◽  
Traffic Monitoring ◽  
Detection Algorithm ◽  
Frame Rate ◽  
Integrated Sensor ◽  
The Road ◽  
Moving Vehicles ◽  
Direction Of Movement ◽  
Account Due ◽  
Selection Of

FPGA and ASIC implementation of the algorithm for traffic monitoring in urban areas This paper describes the idea and the implementation of the image detection algorithm, that can be used in integrated sensor networks for environment and traffic monitoring in urban areas. The algorithm is dedicated to the extraction of moving vehicles from real-time camera images for the evaluation of traffic parameters, such as the number of vehicles, their direction of movement and their approximate speed. The authors, apart from the careful selection of particular steps of the algorithm towards hardware implementation, also proposed novel improvements, resulting in increasing the robustness and the efficiency. A single, stationary, monochrome camera is used, simple shadow and highlight elimination is performed. The occlusions are not taken into account, due to placing the camera at a location high above the road. The algorithm is designed and implemented in pipelined hardware, therefore high frame-rate efficiency has been achieved. The algorithm has been implemented and tested in FPGA and ASIC.

The Time Domain Simulation of Non-Stationary Road Roughness

2013 ◽  
Vol 423-426 ◽  
pp. 1238-1242
Author(s):  
Hao Wang ◽  
Xiao Mei Shi
Keyword(s):  
Power Spectrum ◽  
Time Domain ◽  
Ride Comfort ◽  
Time History ◽  
Random Excitation ◽  
Power Spectrum Density ◽  
The Road ◽  
Road Roughness ◽  
Spectrum Density ◽  
History Of

The input of road roughness, which affects the ride comfort and the handling stability of vehicle, is the main excitation for the running vehicle. The time history of the road roughness was researched with the random phases, based on the stationary power spectrum density of the road roughness determined by the standards. Through the inverse Fourier transform, the random phases can be used to get the road roughness in time domain, together with the amplitude. Then, the time domain simulation of the non-stationary random excitation when the vehicle ran at the changing speed, would also be studied based on the random phases. It is proved that the random road excitation for the vehicle with the changing speed is stationary modulated evolution random excitation, and its power spectrum density is the stationary modulated evolutionary power spectrum density. And the numerical results for the time history of the non-stationary random inputs were also provided. The time history of the non-stationary random road can be used to evaluate the ride comfort of the vehicle which is running at the changing speed.

Sign in / Sign up

Export Citation Format

Share Document