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Design of controlling system in multi-function durability testing device for vehicle vacuum booster with brake master cylinder (EI CONFERENCE) 会议论文
2012 International Conference on Mechanical and Electronic Engineering, ICMEE 2012, June 23, 2012 - June 24, 2012, Hefei, China
Hao X.; Zhang R.; Li X.; Wang M.
收藏  |  浏览/下载：31/0  |  提交时间：2013/03/25
The quality of vehicle vacuum booster with brake master cylinder is related to the safe of drivers and automobiles. The testing experiment must be executed strictly before leaving factory based on the national standards.The paper introduces the controlling system of multi-function durability testing device  which is designed for doing durable testing experiments and Anti-lock braking system (ABS) performance experiments. The structure and theory of device is presented. The controlling system is illuminated in detail. To test the dynamic property  this system was identified by a recursive BP neural network. According to the character of a great deal of sensors and actuators  the high precision  capabilities and reliability  the distributed control mode (DCS) including the computer and PLC by RS-485 bus is utilized. The four channels testing experiments are achieved at the same time. The test data is directly memorized into the computer. The results of general endurance and ABS endurance testing experiments are shown to demonstrate the excellent performance of the testing device. 2012 Springer-Verlag Berlin Heidelberg.  
Neural network based online traffic signal controller design with reinforcement training (EI CONFERENCE) 会议论文
14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011, October 5, 2011 - October 7, 2011, Washington, DC, United states
Dai Y.; Hu J.; Zhao D.; Zhu F.
收藏  |  浏览/下载：26/0  |  提交时间：2013/03/25
Traffic congestion leads to problems like delays  decreasing flow rate  and higher fuel consumption. Consequently  keeping traffic moving as efficiently as possible is not only important to economy but also important to environment. Traffic system is a large complex nonlinear stochastic system. Traditional mathematical methods have some limitations when they are applied in traffic control. Thus  computational intelligence (CI) technologies gain more and more attentions. Neural Networks (NNs) is a well developed CI technology with lots of promising applications in traffic signal control (TSC). In this paper  a neural network (NN) based signal controller is designed to control the traffic lights in an urban traffic road network. Scenarios of simulation are conducted under a microscopic traffic simulation software. Several criterions are collected. Results demonstrate that through online reinforcement training the controllers obtain better control effects than the widely used pre-time and actuated methods under various traffic conditions. 2011 IEEE.  
An advanced LEO satellite network model based on MPLS-TP (EI CONFERENCE) 会议论文
2010 International Conference on Advanced Intelligence and Awareness Internet, AIAI 2010, October 23, 2010 - October 25, 2010, Beijing, China
Yan X.; Zhang Y.; Zhou G.; Bai T.; Zhang Z.; Gu W.
收藏  |  浏览/下载：15/0  |  提交时间：2013/03/25
LEO (Low Earth Orbit) satellite networks are capable of providing broadband access to end users in any part of the world. With the characteristics of high-speed movement and rapid dynamic topology of LEO satellites  networking has always been one of the key issues in LEO satellite network. MPLS-TP (Multi-Protocol Label Switching-Transport Profile) is an excellent packet transport network (PTN) technology in terrestrial networks  which can support multi-service and have perfect function of QoS (Quality of Service)  OAM (Operation Administration Maintenance) and survivability. In this paper  the characteristics of LEO satellite network and functional architecture of MPLS-TP are introduced. Then an advanced LEO satellite network model based on MPLS-TP (ALSN-M) is proposed  which can guarantee a connection-oriented seamless data transmission. Furthermore topology and routing algorithms of proposed LEO satellite network model is analyzed. In the end  the paper describes how to setup and remove a LSP (Label Switched Path) and how to maintain an exiting LSP when a handover happens.  
The costs prediction of AOD furnace based on improved RBF neural network (EI CONFERENCE) 会议论文
2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China
Na T.; Zhang D.-J.; Hui L.
收藏  |  浏览/下载：9/0  |  提交时间：2013/03/25
Handwritten character recognition based on 13-point feature of skeleton and self-organizing competition network (EI CONFERENCE) 会议论文
2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010, May 11, 2010 - May 12, 2010, Changsha, China
Zhong C.; Ding Y.; Fu J.
收藏  |  浏览/下载：37/0  |  提交时间：2013/03/25
Application of master-slave multi-communication system in pilotless airborne mapping equipment (EI CONFERENCE) 会议论文
5th International Symposium on Instrumentation Science and Technology, September 15, 2009 - September 18, 2009, Shenyang, China
Zhang Y.; Chen J.; Wang W.
收藏  |  浏览/下载：22/0  |  提交时间：2013/03/25
This paper presents a master-slave multi-communication system designed with several micro-controllers used as master and slave controllers to set signal the lamp to realize point-to-point communication through the RS422 interface. By describing a typical example of this system and the blue print of hardware and the flowchart of software  the reliable work of the system has been proved. The circuits of system are very simple and practical  and they can be used to realize all the functions of a pilotless airborne mapping equipment. It also has a strong anti-jamming capability due to its balanced transfer scheme with single transmitter and multiple receivers. It is very efficient in protecting the integrity and correctness of transmitted and received signals  avoiding the collision of signals through the bus  satisfying the communication among several micro-controllers in a single system and forming a special communication network. 2009 SPIE.  
The application study on building materials with computer color quantification system (EI CONFERENCE) 会议论文
ICO20: Illumination, Radiation, and Color Technologies, August 21, 2005 - August 26, 2005, Changchun, China
Li Z.; Yu H.; Li H.; Zhao H.
收藏  |  浏览/下载：20/0  |  提交时间：2013/03/25
The first impression of any building to a person is its exterior and decoration  therefore  at the same time  and therefore the quality of decoration project shows the more important position in building project. A lot of projects produce quality problem because of the material color difference  how to grasp and control the color change of building materials  the color difference problem laying stone materials is also studied in this paper  which exists universally at the common project  and carry out color quantification  and the solution scheme has been given using this system.  and is often found at the high-grade decoration  it has the very important meaning. According to the color theory  a computer vision system used in color quantification measurement is established  the standard illuminant A is selected as the light source. In order to realize the standardization of color evaluation  the mutual conversion between RGB and XYZ color space is studied  which is realized by the BP network. According to the colorimetry theory  the computer program is compiled in order to establish the software system  and realize the color quantitative appraisement in whole color gamut. LCH model is used at quantifying the color of building materials  and L*a*V model is used at comparing the color change. If the wooden floor is selected and laid improperly during family fitment  it is easy to present "flower face". The color also arises greater discrepancy using the laths of same tree. We can give the laying scheme using the color quantification system  
Intelligent MRTD testing for thermal imaging system using ANN (EI CONFERENCE) 会议论文
ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China
Sun J.; Ma D.
收藏  |  浏览/下载：18/0  |  提交时间：2013/03/25
The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task  for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type  the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP  but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly  we use frame grabber to capture the 4-bar target image data. Then according to image gray scale  we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets  along with known target visibility  are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm  demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.  
An object recognition method based on fuzzy theory and BP networks (EI CONFERENCE) 会议论文
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
Chuan W.; Ming Z.; Dong Y.
收藏  |  浏览/下载：14/0  |  提交时间：2013/03/25
It is difficult to choose eigenvectors when neural network recognizes object. It is possible that the different object eigenvectors is similar or the same object eigenvectors is different under scaling  shifting  rotation if eigenvectors can not be chosen appropriately. In order to solve this problem  the image is edged  the membership function is reconstructed and a new threshold segmentation method based on fuzzy theory is proposed to get the binary image. Moment invariant of binary image is extracted and normalized. Some time moment invariant is too small to calculate effectively so logarithm of moment invariant is taken as input eigenvectors of BP network. The experimental results demonstrate that the proposed approach could recognize the object effectively  correctly and quickly.  
Abrupt sensor fault diagnosis based on wavelet network (EI CONFERENCE) 会议论文
2006 IEEE International Conference on Information Acquisition, ICIA 2006, August 20, 2006 - August 23, 2006, Weihai, Shandong, China
Zhang H.; Chen T.; Li W.
收藏  |  浏览/下载：11/0  |  提交时间：2013/03/25
The possible faults of a sensor may be classified as abrupt (sudden) faults and incipient (slowly developing) faults. This paper focuses on the abrupt faults of a sensor. Due to the limited number of scales  a single wavelet amplitude map has not enough scales to describe all details of the signal. The sampling grid in the scale direction is rather sparse  Some of the fault information will be leaked under such sparse grid. To make up for the deficiency of scalar orthogonal wavelet transform in the application of abrupt fault diagnosis  multiwavelet packets transform was introduced into the field of abrupt fault diagnosis. The distribution differences of the signal energy on decomposed multiwavelet scales of the signal before and after the fault occurring are extracted as the fault feature and used as the input of multi-dimensional wavelet network. A new model-free diagnostic method for isolating abrupt sensor faults is developed based on a proposed algorithm of multi-dimensional wavelet network constructing. The method has been proved to be quite effective in the detection of sensor abrupt fault. 2006 IEEE.  

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