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A new formula of mechanism mobility based on virtual constraint loop

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Science China(Technological Sciences) 2011年第10期54卷 2768-2775页

作者： ZHANG YiTong LI YanWent WANG LiYa Mechanical Engineering Institute of Yanshan University Qinhuangdao 066004 China Foreign Languages Institute of Yanshan University Qinhuangdao 066004 China

Several important developing phases of the formulas for mobility calculation based on constraints are introduced. The shortcoming of the mobility formulas based on common constraints of loops of a mechanism is that virtual constraints must be calculated before determining the mobility of a mechanism with virtual constraints. In order to avoid the shortcoming, some new concepts including virtual loop, virtual-loop constraint and general-kinematic-pair constraint are used to analyze the relationship between mobility of links and constraint of kinematic pairs and a mobility formula based on common constraints of virtual loops is proposed. The formula is that the number of mobility of a mechanism is the sum of mobility of all links in the mecha-nism minus the sum of constraints of all kinematic pairs plus the sum of the common constraints of all virtual loops. The sum of over constraints of a mechanism is the sum of constraints of all virtual loops in the mechanism. This mobility formula expressed in terms of common constraints of virtual loops in a mechanism can avoid calculating virtual constraints. It is proved that the new formula is correct, simple and effective through the analysis of several different kinds of mechanisms.

关键词： 0mobility general kinematic pair virtual loop virtual-loop common constraint over constraint

Over-constraint and a Unified Mobility Method for General Spatial Mechanisms Part 1: Essential Principle

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Chinese Journal of Mechanical Engineering 2015年第5期28卷 869-877页

作者： ZENG Daxing LU Wenjuan HUANG Zhen School of Mechanical Engineering Yanshan University

Compared with the parallel mechanisms, the mobility analysis of the general multi-loop spatial mechanisms（GMSMs） is more difficult to obtain correct results. The reason is that its multi-loop is formed through several times of closings and there also exists motion coupling even strong coupling, where the over-constraints are concealed. However, the mobility analysis for this kind of mechanisms has been paid few attentions. A new systemic methodology for analyzing mobility is proposed for GMSMs also based on the screw theory. The key issue for mobility analysis is to recognize the over-constraint. Firstly, three theorems are given and point out： the reason and site of over-constraint occurrence, calculating the number of over-constraints by the screw theory, and how to analyze the over-constraints for a single-loop mechanism as well. Then, three closing forms for GMSMs are proposed including rigid closure, movable closure and dynamic closure, and for the three different forms the different analysis methods are also given. Especially, for the most difficult issue of GMSMs with the multi-loop Closure in many times and the inevitable motion coupling, two important methods are proposed：＂recognizing over-constraints by analyzing relative movement＂ and ＂recognizing over-constraints by virtual loop＂. The two methods are well used to solve the issue. Above-mentioned principles are not only systematic and effective but also unified. They provide a theoretical basis for the general multi-loop spatial mechanisms.

关键词： mobility analysis multi-loop over-constraint closing forms virtual loop

Model for Predicting Roadside Concentrations of Traffic Pollutants

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Tsinghua Science and Technology 2007年第2期12卷 178-183页

作者：杨忠振苗国强王璐 College of Transportation and Logistics Dalian Maritime University Dalian 116026 China

An analytical model is presented to estimate traffic pollutant concentrations based on an artificial neural network （ANN） approach. The model can analyze the highly nonlinear relationship between the traffic flow attributes, meteorological conditions, road spatial characteristics, and the traffic pollutant concentrations This study analyzes the multiple factors that affect the pollutant concentration and establishes the model structure using the ANN technique. Collected data for the pollutant concentrations as functions of vadant factors was used to train the ANN model. A method was developed to automatically measure the traffic flow attributes, such as traffic flow, vehicle speed, and flow composition from video data. The results indicate that the model can reliably forecast CO2 concentrations along the roads.

关键词： artificial neural network pollutant concentration traffic flow virtual loop