Future mechatronics and automation

FUTURE MECHATRONICS AND AUTOMATION

Studies in Materials Science and

Mechanical Engineering

eISSN: 2333-6560

Volume 1

PROCEEDINGS OF THE 2014 IMSS INTERNATIONAL CONFERENCE ON FUTURE

MECHATRONICS AND AUTOMATION (ICMA 2014), BEIJING, 7–8 JULY 2014

Future Mechatronics and Automation

Editor

Guohui Yang

International Materials Science Society, Hong Kong, Kowloon, Hong Kong

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ISBN: 978-1-138-02648-3 (Hardback)

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Future Mechatronics and Automation – Yang (Ed.)

© 2015 Taylor & Francis Group, London, ISBN 978-1-138-02648-3

Table of contents

Preface IX

Organizing Committee XI

Section 1: Mechanical engineering

Analysis of measurement uncertainty for aircraft docking and assembly 3

Y.C. He, G.X. Li, B.Z. Wu & J.Z. Yang

The application of the China EDPF-NT + DCS in a power plant for an FGD project 7

L.J. Dong, W.P. Liang & Y.P. Wang

Research on the integrated test system of dynamical balance and the correction of optical axis

of the coordinator 11

P.T. Cong & H. Han

Comparison of different Sub-Grid Scale models for the nonreacting flow in a Lean Direct

Injection combustor 15

H. Dong & X.Y. Wen

In-vehicle information system embedded software developing approach based on QNX RTOS 21

H. Cheng & Z.Y. Liu

Research on steering angle tracking control approach for Steer-By-Wire system 27

M. Zhang & Z. Liu

Design and rendering of the 3D Lotus Pool by Moonlight 35

Y.-X. Hui & W.-G. Liu

Finite element analysis and optimization of an economical welding robot 41

S.W. Cui & J.J. Wei

Modal analysis on the instrument panel bracket of automotive 45

S.W. Cui & J.J. Wei

Preparing high aspect ratio sub-wavelength structures by X-ray lithography 49

Y.G. Li & S. Sugiyama

Optimization and combination of machinery units for processing fish balls 53

J.M. Liu, G.R. Sun, F.G. Du, X.R. Kong, K.J. Liu & X.S. Liu

Section 2: Mechatronics

Exploration on hospital strategy management based on niche theory 59

C. Zhu, G.W. Wang, X.F. Xiong & Y. Guo

Noise adaptive UKF method used for boost trajectory tracking 63

Y. Wang, H. Chen, H. Zhao & W. Wu

Geometric orbit determination of GEO satellites based on dynamics 69

Y.D. Wang, H. Zhao, H.Y. Chen & W.Y. Wu

The design of an intelligent hydropower station operation simulation model 73

T. Chen & X.C. Wu

The development of an intelligent portable fumigation treatment bed 79

D.-L. Zhao & Y.-X. Guo

V

The design of a controller with Smith predictor for networked control systems with long time delay 83

Y.G. Ma, J.R. Jia & J.Q. Bo

The behavioural identified technology of drivers based on mechanical vision 89

J.L. Tang, G.L. Zhuang, B.H. Su, S.F. Chen & X.Y. Li

Real-time fault detection and diagnosis of ASCS in AMT heavy-duty vehicles 95

Y.N. Zhao, H.O. Liu, W.S. Zhang & H.Y. Chen

WSN node localization technology research based on improved PSO 101

P.Y. Ren, L.R. Chen & J.S. Kong

An indoor control system based on LED visible light 107

W.Y. Yu, Z.Y. Chen, Y.Z. Zhao & C.Y. Hu

Experimental research on ultrasonic separation of two-dimensional normal mode 111

C.H. Hua & J.X. Ding

Adaptive fuzzy PID control for the quadrotor 115

D. Qi, J.-f. Feng, Y.-l. Li, J. Yang, F.-f. Xu & K. Ning

Design and implementation of cloud computing platform for mechatronics manufacturing 119

T.T. Liu, Q. Yue, T.K. Ji & X.Q. Wu

A fuzzy comprehensive assessment model and application of traffic grade on an emergency in a city 125

F. Wang, J. Gao, Z.-l. Xiong & Y. Jiang

The transplant process of Linux2.6.20 on the development board of K9iAT91RM9200 129

B.H. Jiang & J. Mei

Eliminating bridge offset voltage for AMR sensors 133

Y.J. Wang

Evaluation and influencing factors of urban land intensive use – a case study of Xianning City 137

X.H. Cui, C.S. Song & W.X. Zhai

Short-term wind power forecasting based on Elman neural networks 143

S.H. Zhang & X.P. Yang

Design of a multiple function intelligent car based on modular control 147

C. Tan, L.-Y. Wang, H.-M. Zhao & C. Su

Section 3: Intelligent robotics

Research on virtual human motion generation using KernelPCA method 153

X.Q. Hu, J.H. Liang, Q.P. Liu & Y.W. Fu

The research and realization of digital library landscape based on OpenGl 159

W.-G. Liu & Y.-X. Hui

A class of memory guaranteed cost control of T-S fuzzy system 165

Y.H. Wang, X.Q. He, Z.H. Wu & C.G. Wang

Application of improved BP neural network in fiber grating pressure measuring system 171

Q.G. Zhu, M. Yuan, C.F. Wang & Y.Y. Gao

Mobile robot vision location based on improved BP-SIFT algorithm 177

Q.G. Zhu, J. Wang, X.X. Xie & W.D. Chen

Direct adaptive fuzzy sliding mode control for a class of uncertain MIMO nonlinear systems 183

S.L. Wen & Y. Yan

Adjacent vertex distinguishing total coloring of Cartesian product graphs 191

Z.-Q. Chu & J.-B. Liu

Design of embedded graphical user interface of a graphics driver library based on STemWin 195

Y.M. Zhou, W.S. Liang & L. Qiu

Research and design of the controller for vision-based multi-rotor MAV 199

Y.-J. Wang, Z. Li, S.-b. Pan & X. Li

VI

Tow tension controller for robotic automated fiber placement based on fuzzy parameter

self-adjusting PID 205

J. Chen & Y.G. Duan

The research and design of an internal cooling control system for plastic film production

based on Cortex M3 211

H. Guo & S.-W. Yu

Author index 215

VII

Future Mechatronics and Automation – Yang (Ed.)

© 2015 Taylor & Francis Group, London, ISBN 978-1-138-02648-3

Preface

2014 IMSS International Conference on Future Mechatronics and Automation (ICMA 2014) was held on July

7–8, 2014 in Beijing, China. The conference was an international forum for the presentation of technological

advances and research results in the fields of Intelligent Robotics, Mechatronics, and Mechanical Engineering.

The conference brought together leading researchers, engineers and scientists in the domains of interest from

around the world. We warmly welcomed previous and prospective authors to submit their new research papers

to ICMA 2014, and share valuable experiences with scientists and scholars from around the world.

In the past twenty years, Intelligent Robotics, Mechatronics, and Mechanical Engineering have become

involved in many varied applications throughout the world, with multiple products and rapid market services.

They have has not only provided industries with new methods, new tools and new products, but also changed

the manner, philosophy and working environments of people in the manufacturing field.

The ICMA 2014 program consisted of invited sessions, technical workshops and discussions with eminent

speakers covering a wide range of topics. This rich program provided all attendees with the opportunity to meet

and interact with one another.

All the papers in the conference proceedings have undergone an intensive review process performed by the

international technical committee, and only accepted papers are included. This volume comprises the selected

papers from the subject areas of Intelligent Robotics, Mechatronics, and Mechanical Engineering.

We hope that the contents of this volume will prove useful for researchers and practitioners in developing and

applying new theories and technologies in Intelligent Robotics, Mechatronics, and Mechanical Engineering.

Finally we would like to acknowledge and give special appreciation to our keynote speakers for their valuable

contributions, our delegates for being with us and sharing their experiences, and our invitees for participating

in ICMA 2014. We would also like to extend our appreciation to the Steering Committee and the International

Conference Committee for the devotion of their precious time, advice and hard work to prepare for this conference.

IX

Future Mechatronics and Automation – Yang (Ed.)

© 2015 Taylor & Francis Group, London, ISBN 978-1-138-02648-3

Organizing Committee

HONORARY CHAIR

Tianharry Chang, IEEE SYS Brunei Darussalam Chapter Past Chair, Brunei Darussalam

GENERAL CHAIRS

Enke Wang, International Materials Science Society, Hong Kong

Mark Zhou, Hong Kong Education Society, Hong Kong

PUBLICATION CHAIR

Guohui Yang, International Materials Science Society, Hong Kong

ORGANIZING CHAIRS

Khine Soe Thaung, Society on Social Implications of Technology and Engineering, Maldives

Tamal Dasas, Society on Social Implications of Technology and Engineering, Maldives

PROGRAM CHAIR

Barry Tan, Wuhan University, China

INTERNATIONAL COMMITTEE

S. Sugiyama, Ritsumeikan University, Japan

Lijing Dong, North China Electric Power University, China

Hong Dong, Naval University of Engineering, China

J.M. Liu, Forestry College of Beihua University, China

Wangyang Yu, Jilin University, China

Duo Qi, Air Force Engineering University, China

Tiantian Liu, Cloud Computing Center, Chinese Academy of Sciences, China

Yi Jiang, Wuhan Polytechnic University, China

Binghua Jiang, China Three Gorges University, China

Yongjun Wang, Guilin University of Aerospace Technology, China

Zhengqing Chu, Anhui Xinhua University, China

Yanming Zhou, Lushan College of Guangxi University of Science and Technology, China

Hua Guo, Shandong University of Science and Technology, China

Xianqian Hu, National University of Defense Technology, China

XI

Section 1: Mechanical engineering

Future Mechatronics and Automation – Yang (Ed.)

© 2015 Taylor & Francis Group, London, ISBN 978-1-138-02648-3

Analysis of measurement uncertainty for aircraft docking and assembly

YuCheng He, GuoXi Li, BaoZhong Wu & JingZhao Yang

College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, China

ABSTRACT: For the difficulty of estimating measurement uncertainty during aircraft docking, the paper

proposes an evaluation method for measurement uncertainty based on a three-dimensional model; The author

uses VC++ and Visual Basic to do secondary development on Spatial Analyzer which is a measuring software

to develop a simulation software for measurement; A procedure was designed for measuring the position and

orientation of the aircraft components, and for simulating measurement procedures based on the Monte Carlo

Theory.This paper evaluates the results of the simulation, which indicates that the measuring procedure is feasible

and can provide guidance for the rapid deployment of measurement and docking for aircraft parts.

Keywords: Monte Carlo Theory, uncertainty, aircraft docking, measurement, position and orientation

1 INTRODUCTION

In the field of aircraft assembly, assembly work used to

be completed manually using rigid tooling. It has been

transformed into relying on a digital flexible assembly

system [1]. An important prerequisite for complet￾ing a digital assembly is that the measurement system

can accurately obtain the position difference between

two separate aircraft parts, The position difference is

then fed back to the motion control system. Laser

Tracker is widely used in the field of aircraft mea￾surement and assembly. Take “FARO Laser Tracker

X” for example: its measuring range can reach seventy

metres and its accuracy can reach 0.001. However, a

good measuring result includes not only the measur￾ing value, but also includes its confidence intervals

[2]. After considering uncertainty, the result is still

able to meet the precision of aircraft docking and

such a measurement result is credible. Currently, there

are four main methods of evaluating measurement

uncertainty: a statistical method, an analytical method,

an expert empirical method and a computer simula￾tion method [3]. In statistical methods, the workers

repeat measuring the workpiece many times and this

method can provide reliable assessment. However, air￾craft production is too complex and large and the

measuring environment too complicated for the sta￾tistical method to be suitable. The analytical method

needs to solve the sensitivity coefficient from error

sources to results, synthesizing the impacts of error

sources. In the process of aircraft measurement, error

sources are numerous and their transitive relationships

are complex. Therefore, the analytical method is not

appropriate. Expert empirical method relies on the

experience of empirical staff excessively, its standard￾ization is so low that it is not suitable for universal

application.

Figure 1. Main modules of measuring simulation platform.

The main idea of the computer simulation method is

that a constructing measurement system model, based

on the transitive relationship between error sources

and the measurement results, reproduces the important

sources of error in the measurement system’s model.

Finally, it is necessary to calculate the uncertainty

through simulation.

In the process of measuring aircrafts’ separate com￾ponents there are many factors affecting measurement

accuracy, these factors include not only errors of the

laser tracker itself, but also include the temperature

of the workshop, vibration, and deformation of the

workpiece. Since errors are distributed randomly, the

preferred choice of measuring an aircraft’s position

and orientation is the computer simulation method.

Based on the aforementioned information, the

author developes a computer simulation measuring

platform and its main modules are shown in Fig￾ure 1, At the same time, the author has designed a

3

Figure 2. The model of aircraft docking and assembly.

measurement plan for an aircraft docking model. This

model is shown in Figure 2 and the plan is tested with

Monte Carlo method, which indicate the uncertainty

of the results which highlight the significance of the

measurement results.

2 ANALYSIS OF MEASURING

UNCERTAINTY

2.1 Collecting measuring points

Before the simulation of measuring aircraft compo￾nents’position and orientation, it is necessary to obtain

the theoretical coordinate of optical target points. If

each point of coordination is obtained through the

basic operation of CATIA, a lot of time will be spent

and what is worse, operational faults will occur easily.

Therefore, the author did a secondary development on

CATIA based on VBA.

Through these commands:

ReDim InputObjectType(5)

InputObjectType(0) = "Face,Point"

We can set the feature being selected be face or point

and so on. Through these commands:

sel.SelectElement2(InputType, "User Select", True)

sel.Item(1).GetCoordinates Coo

We can obtain coordinates of mouse click [4].

Then save the points’ coordinates data to a text file by

the VB program. The operations in CATIA will be

simplified greatly if we depend on these methods.

2.2 Measuring process

The point groups extracted from CATIA were loaded

into spatial analyzer: a measuring software. The point

groups consist of ERS points, theoretical ERS points,

initial-position points, common points and target￾position points.

2.2.1 ERS points

The function of ERS (Enhanced Reference Points)

is to establish an assembly benchmark. The first

choice of ERS points are terrestrial reference points

or fixed points in an assembly plant. During the mea￾suring process, the first step is measuring the “ERS

points” and obtaining their coordinates. Secondly,

acquire the coordinates of corresponding “theoreti￾cal ERS points” in CATIA. Thirdly, fit “theoretical

ERS points” to “ERS points” and obtain the transform

matrix. Through these three steps, the relationship

between actual environment and virtual environment

is constructed.

2.2.2 Common points

An aircraft’s shape is complex and large, all the

measuring points cannot be measured by a single

instrument. So two or more instrument are needed to

accomplish the measuring task. However, the coor￾dinate system of each instrument is works indepen￾dently. In order to unify the laser trackers in the

same network, it is necessary to measure the com￾mon points, constructing a USMN (Unified Spatial

Metrology Network).

2.2.3 Initial-position points and target-position

points

“The initial-position points” refer to the measuring

points on the moving part before docking. “The target￾position points” refers to the same points, but the

difference is that separating parts have been docked

precisely.

Figure 3 shows the measuring procedure.

2.3 Simulation

According to the Monte Carlo Theory, when simula￾tion times tends to infinity, the uncertainty is closest

to real value, but SA basic operations support only one

time simulation. Therefore, the author did a secondary

development work on SA. Based on the interface pro￾vided by SA, every step of the SA operations was

converted into C++ code. The loop was exerted to

realize simulate for 10,000 times or more. After sim￾ulation, the expectation or standard deviation was

calculated, together with other relevant mathematical

characteristics. Before simulation in the SA, optical

interference checking is essential to guarantee that the

optical target point would not be blocked. Thereafter,

the points which could be measured by a laser tracker

were stored and these remaining points were loaded

into the SA, ignoring the CAD model. This saves a lot

of running time, especially if the simulation frequency

rises to 10,000.

2.4 Analysis of measuring result

Simulate the measuring procedure 60,000 times, col￾lect the data (including three moving parameters and

three rotating parameters) generated by the simulation,

4