The functioning investigation of the network semi-active damping system for wheeled vehicle

2021 ◽  
pp. 21-28
Keyword(s):  
System Identification ◽  
Physical Model ◽  
Network Model ◽  
Active Damping ◽  
Central Processor ◽  
Active System ◽  
Physical Network ◽  
Wheeled Vehicle ◽  
Road Profile

The tasks related to the construction of a united semi-active system for damping vibrations of the supporting platform (chassis) of a wheeled vehicle (WV), taking into account the real road profile were considered. The influence estimation of the network on the functioning resulting quality of the entire united damping system is carried out. The modeling of the network united of the model of one wheelset, the possible law of control of the suspension, the central processor and the physical model of the CAN network by using the National Instruments equipment is performed. The results of the experiments, both purely mathematical and with a physical network model, showed the performance of the proposed solutions. Keywords CAN-tire; semi-active suspension system; identification; modeling

Network Model of a Thermo-Acoustic Heat Engine Assisted with Unsteady CFD and System Identification

2011 ◽  
Author(s):  
F. Selimefendigil ◽  
Theodore E. Simos ◽  
George Psihoyios ◽  
Ch. Tsitouras ◽  
Zacharias Anastassi
Keyword(s):  
System Identification ◽  
Network Model ◽  
Heat Engine

scholarly journals FULL CAR ACTIVE DAMPING SYSTEM FOR VIBRATION CONTROL

2020 ◽  
Vol 6 (4) ◽  
pp. 1-17
Author(s):  
G. Yakubu ◽  
G. Sani ◽  
S. B. Abdulkadir ◽  
A. A.Jimoh ◽  
M. Francis
Keyword(s):  
Mathematical Model ◽  
Linear Quadratic Regulator ◽  
Active Damping ◽  
Settling Time ◽  
Linear Quadratic ◽  
Body Acceleration ◽  
The Road ◽  
Road Profile ◽  
Lqr Controller ◽  
Mass Displacement

Full car passive and active damping system mathematical model was developed. Computer simulation using MATLAB was performed and analyzed. Two different road profile were used to check the performance of the passive and active damping using Linear Quadratic Regulator controller (LQR)Road profile 1 has three bumps with amplitude of 0.05m, 0.025 m and 0.05 m. Road profile 2 has a bump with amplitude of 0.05 m and a hole of -0.025 m. For all the road profiles, there were 100% amplitude reduction in Wheel displacement, Wheel deflection, Suspension travel and body displacement, and 97.5% amplitude reduction in body acceleration for active damping with LQR controller as compared to the road profile and 54.0% amplitude reduction in body acceleration as compared to the passive damping system. For the two road profiles, the settling time for all the observed parameters was less than two (2) seconds. The present work gave faster settling time for mass displacement, body acceleration and wheel displacement.

scholarly journals Contribution to image restoration using a neural network model

2002 ◽  
Vol Volume 1, 2002 ◽  
Author(s):  
Karim Achour ◽  
Nadia Zenati ◽  
Oualid Djekoune
Keyword(s):  
Neural Network ◽  
Image Restoration ◽  
Network Model ◽  
Neural Network Model ◽  
Hopfield Neural Network ◽  
Optimization Method ◽  
Nous Proposons ◽  
International Audience ◽  
High Level

International audience The reduction of the blur and the noise is an important task in image processing. Indeed, these two types of degradation are some undesirable components during some high level treatments. In this paper, we propose an optimization method based on neural network model for the regularized image restoration. We used in this application a modified Hopfield neural network. We propose two algorithms using the modified Hopfield neural network with two updating modes : the algorithm with a sequential updates and the algorithm with the n-simultaneous updates. The quality of the obtained result attests the efficiency of the proposed method when applied on several images degraded with blur and noise. La réduction du bruit et du flou est une tâche très importante en traitement d'images. En effet, ces deux types de dégradations sont des composantes indésirables lors des traitements de haut niveau. Dans cet article, nous proposons une méthode d'optimisation basée sur les réseaux de neurones pour résoudre le problème de restauration d'images floues-bruitées. Le réseau de neurones utilisé est le réseau de « Hopfield ». Nous proposons deux algorithmes utilisant deux modes de mise à jour: Un algorithme avec un mode de mise à jour séquentiel et un algorithme avec un mode de mise à jour n-simultanée. L'efficacité de la méthode mise en œuvre a été testée sur divers types d'images dégradées.

Healthier by Safe Persuasion

2012 ◽  
Vol 245 ◽  
pp. 9-14 ◽  
Author(s):  
Mihai Berteanu ◽  
Ruxandra Badea ◽  
Ileana Ciobanu ◽  
Luminita Violeta Dumitru ◽  
Alina Nela Iliescu ◽  
...  
Keyword(s):  
Chronic Condition ◽  
Inertial Sensors ◽  
Risk Prevention ◽  
Chronic Obstructive ◽  
Health State ◽  
Generation System ◽  
Active System ◽  
Obstructive Pulmonary Disease ◽  
Sensing System

We have three generations of persuasive technology devices used in health care, up to now. The IS-ACTIVE system –Inertial Sensing System for advanced Chronic Condition Monitoring and Risk Prevention is a third generation system, using IT, inertial sensors, sensors for physiological parameters and a feedback device in order to improve the physical activity and subsequently, the health state and the quality of life for people affected by chronic obstructive pulmonary disease and other respiratory and cardiovascular disabling medical conditions.

Health and Usage Monitoring Algorithm Based on Terrain Identification for Mechanical Components on an Army Ground Vehicle System

2008 ◽  
Vol 51 (2) ◽  
pp. 31-41 ◽  
Author(s):  
Richard Heine ◽  
Donald Barker
Keyword(s):  
Unit Cost ◽  
Monitoring Systems ◽  
Statistical Parameters ◽  
Ground Vehicle ◽  
Wheeled Vehicle ◽  
Vehicle System ◽  
Basic Set ◽  
Vehicle Systems ◽  
Monitoring Algorithm

The desire for enhanced functionality of Army vehicle systems has resulted in increasingly complex systems. This drive is in direct contention with another Army goal of improved reliability. Health and usage monitoring systems (HUMS) and remaining-life prognostics are being developed to address these conflicting goals. One of the major challenges of applying a HUMS to an Army wheeled vehicle system is that the development and per unit cost of the HUMS needs to be relatively low in comparison with typical high-cost applications such as aircraft. Simplified algorithms that derive terrain exposure from a basic set of sensors and estimate fatigue damage accumulated on components where loading comes primarily from terrain have been developed to meet this need. Various inputs and statistical parameters are evaluated for this model based on accuracy of terrain identification and quality of fatigue prediction on an example component. The generalized process and recommendations for application of this model to military ground vehicle systems are discussed.

Studying on the Fiber Diameter of Polypropylene (PP) Spunbonding Fabric by Means of Artificial Neural Network Model and Physical Model

2010 ◽  
Vol 426-427 ◽  
pp. 356-360
Author(s):  
Bo Zhao
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Physical Model ◽  
Network Model ◽  
Process Parameters ◽  
Neural Network Model ◽  
Artificial Neural Network Model ◽  
Fiber Diameter ◽  
Good Prediction ◽  
Artificial Neural

In this work, the artificial neural network model and physical model are established and utilized for predicting the fiber diameter of polypropylene(PP) spunbonding nonwovens from the process parameters. The artificial neural network model has good approximation capability and fast convergence rate, is used in this research. The results show the artificial neural network model can provide quantitative predictions of fiber diameter and yield more accurate and stable predictions than the physical model, which reveals that the artificial neural network model is based on the inherent principles, and it can yield reasonably good prediction results and provide insight into the relationship between process parameters and fiber diameter.

The Natural Vacuum Desalination Technology in Seawater Desalination

2014 ◽  
Vol 675-677 ◽  
pp. 851-855 ◽  
Author(s):  
Xiao Hua Liu ◽  
Xin Chun Zhang ◽  
Ya Qin Fang ◽  
Ming Ming Zhu
Keyword(s):  
Low Temperature ◽  
Water Column ◽  
Physical Model ◽  
Future Development ◽  
Atmospheric Pressure ◽  
High Water ◽  
Seawater Desalination ◽  
Different Types ◽  
Desalination Technology

Seawater desalination technology is an important way to solve the freshwater shortage problem. Natural vacuum desalination (NVD) technology generates very low pressure environment in the headspace of 10 meters high water column. The weight of the water column is balanced by atmospheric pressure, and low-temperature desalination proceeds in the headspace. NVD technology drives the desalination process without any mechanical pumping, and requires relatively inferior quality of device material and simple structures. In this paper, the basic theory of NVD technology is introduced and physical model is described. Research progresses of different types of NVD technologies are summarized, and the method of increasing freshwater production is pointed out. This paper also illustrates the outlook on future development of NVD technology.

scholarly journals Analysis on Topological Properties of Dalian Hazardous Materials Road Transportation Network

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Pengyun Chong ◽  
Bin Shuai ◽  
Shaowei Deng ◽  
Jianting Yang ◽  
Hui Yin
Keyword(s):  
Network Model ◽  
Transportation Network ◽  
Network Models ◽  
Node Degree ◽  
Power Law Distribution ◽  
Road Transportation ◽  
Service Network ◽  
Scale Free ◽  
Physical Network ◽  
Network Properties

To analyze the topological properties of hazardous materials road transportation network (HMRTN), this paper proposed two different ways to construct the cyberspace of HMRTN and constructed their complex network models, respectively. One was the physical network model of HMRTN based on the primal approach and the other was the service network model of HMRTN based on neighboring nodes. The two complex network models were built by using the case of Dalian HMRTN. The physical network model contained 154 nodes and 238 edges, and the statistical analysis results showed that (1) the cumulative node degree of physical network was subjected to exponential distribution, showing the network properties of random network and that (2) the HMRTN had small characteristic path length and large network clustering coefficient, which was a typical small-world network. The service network model contained 569 nodes and 1318 edges, and the statistical analysis results showed that (1) the cumulative node degree of service network was subjected to power-law distribution, showing the network properties of scale-free network and that (2) the relationship between nodes strength and their descending order ordinal and the relationship between nodes strength and cumulative nodes strength were both subjected to power-law distribution, also showing the network properties of scale-free network.

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