Lecture Notes in Information Technology
Future Management Science and Engineering
Future Management Science and Engineering Volume 5
ISBN:978-1-61275-001-9 Lecture Notes in Information Technology Vol.5-6 ISSN:2070-1918, Electronically available at http://www.ier-institute.org/
INFORMATION ENGINEERING RESEARCH INSTITUTE
Lecture Notes in Information Technology Volume 5
Lecture Notes in Information Technology 2011 International Conference on Future Management Science and Engineering (ICFMSE 2011) August 4‐5, 2011, Bali Island, Indonesia
Edited by W. David
INFORMATION ENGINEERING RESEARCH INSTITUTE, USA iii
Copyright © 2011 Information Engineering Research Institute, USA All rights reserved. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the Information Engineering Research Institute. Information Engineering Research Institute 100 Continental Dr, Newark, DELAWARE 19713, Unite State, USA http://www.ier‐institute.org ISBN: 978‐1‐61275‐001‐9 Lecture Notes in Information Technology Vol.5‐6 ISSN: 2070‐1918 Distributed worldwide by Information Engineering Research Institute 100 Continental Dr, Newark, DELAWARE 19713, Unite State, USA E‐mail: admin@ier‐institute.org
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Message from the ICFMSE 2011 Chair 2011 International Conference on Future Management Science and Engineering (ICFMSE 2011) will be held on August 4‐5, 2011, Bali Island, Indonesia. In 1967 Stafford Beer characterized the field of management science as "the business use of operations research". However, in modern times the term management science may also be used to refer to the separate fields of organizational studies or corporate strategy. Management science (MS), is an interdisciplinary branch of applied mathematics devoted to optimal decision planning, with strong links with economics, business, engineering, and other sciences. It uses various scientific research‐based principles, strategies, and analytical methods including mathematical modeling, statistics and numerical algorithms to improve an organization's ability to enact rational and meaningful management decisions by arriving at optimal or near optimal solutions to complex decision problems. In short, management sciences help businesses to achieve their goals using the scientific methods of operational research. The management scientist's mandate is to use rational, systematic, science‐based techniques to inform and improve decisions of all kinds. Of course, the techniques of management science are not restricted to business applications but may be applied to military, medical, public administration, charitable groups, political groups or community groups. Management science is concerned with developing and applying models and concepts that may prove useful in helping to illuminate management issues and solve managerial problems, as well as designing and developing new and better models of organizational excellence. The application of these models within the corporate sector became known as Management science. Engineering is the discipline, art, skill and profession of acquiring and applying scientific, mathematical, economic, social, and practical knowledge, in order to design and build structures, machines, devices, systems, materials and processes that safely realize improvements to the lives of people. ICFMSE 2011 is a festival which binding numerous scholars in the circle of management science and engineering, we aim to keep an eye on actual productively, then raising the level of the project, ultimately impel social advancement. Three requirements are asked: 1. To open mind and grow together, creating a satisfactory meeting; 2. To construct a project with Chinese characteristics by the way of grabbing overseas experiences and absorbing global essence, in order to speedily establish a well society and accelerate the step of harmonious society; 3. To struggle more power of speaking, initiative and leadership. Wishing that every expert here will make great efforts to increase the innovative capability of China’s management science and engineering and contribute to the human development and world’s constitution. v
Special thanks should be given to the working staff of the association and participants of the conference, who contribute the success of the conference. ICFMSE 2011 shows the newest research results of management science and engineering, every participant need to consolidate their gains so as to lighten a new research direction of the future development. Two days is a short period, during which we communicate with each other, get to know each other and share the happiness with each other. We look forward to meeting you next year. W. David, Cambodia University, Cambodia
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ICFMSE 2011 Organizing Committee General Chairs Mark Zhou
Hong Kong Education Society, Hong Kong
Publication Chair W. David
Cambodia University,Cambodia
Organizing Chairs
Biswanath Vokkarane
Maldives College of Higher Education, Maldives (Contact:
[email protected]) Society on Social Implications of Technology and Engineering
Program Chair Tianbiao Zhang
Huazhong Normal University, China
Khine Soe Thaung
International Committee Yiyi Zhouzhou Garry Zhu Ying Zhang Dehuai Zeng David Wang Srinivas Aluru Tatsuya Akutsu Aijun An Qinyuan Zhou Mark Zhou Yiyi Zhouzhou Khine Soe Thaung Biswanath Vokkarane Tianbiao Zhang Garry Zhu Ying Zhang
Azerbaijan State Oil Academy, Azerbaijan (Contact:
[email protected]) Thompson Rivers University, Canada Wuhan Uniersity, China Shenzhen University, China IEEE Nanotechnology Council Cambodia Chapter Chair, Cambodia ACM NUS Singapore Chapter, Singapore ACM NUS Singapore Chapter, Singapore National University of Singapore, Singapore Jiangsu Teachers University of Technology, China Hong Kong Education Society, Hong Kong Azerbaijan State Oil Academy, Azerbaijan Maldives College of Higher Education, Maldives Society on Social Implications of Technology and Engineering Huazhong Normal University, China Thompson Rivers University, Canada Wuhan Uniersity, China
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ICFMSE 2011 Keynote Speech The Development of Youth Leadership in Extral‐curricular Activity
Speaker: Prof. Bin Wang, Central China Normal University, China Abstract: Leadership development has been an important theme in the field of leadership research. It aims at developing leadership skills by implementing a variety of activities and experiences for leaders, future leaders, and the ones with leadership potential. Positive youth development theory emphasized that adolescence is a critical time for leadership development. Based on youth leadership development literature, including the background, definitions, structure, assessment and developmental models and means, this paper selected 50 middle school students as subjects in which 25 were in experimental group and 25 were in comparison group and adopted the Pre‐test Post‐test control group design and multi‐factor experimental design to conduct an experimental study to find out the impact of outward bound on students’ leadership. Only the subjects of experimental group were exposed to a continuous 18‐week leadership outward bound intervention in extracurricular activity in which subjects met for 45 minutes a day once a week. The result has showed that outward bound have significant impact on students’ leadership development. Biography: Bin Wang was born in 1971. He received the B.S. degree in Sport Psychology from Wuhan Institute of Physical Education, Wuhan, Hubei, China, in 1993, the M.S. degree in General Psychology from Central China Normal University, Wuhan, Hubei, China, in 1996, and the Ph.D. degree in Applied Psychology from Beijing Sport University, Beijing, China, in 2002. Since 1996, he has been a Faculty Member in the Department of Sport and Physical Education, Central China Normal University, Wuhan, Hubei, China, where he is currently an professor and associate dean. He was a postdoctoral researcher in Organizational Behavior and Human Resource Management at the Institute of Psychology, Chinese academy of Sciences, Beijing, China, from 2002 to 2004, and a visiting scholar in Organizational Behavior at the Cornell University, United States, from 2006 to 2007. His research interests include Sport Psychology and Sport administration. He has authored or coauthored more than 90 journal papers and 40 international conference papers. Dr. Wang’s research has been supported by the Program for New Century Excellent Talents in University, National Natural Science Foundation of China, National Social Science Foundation of China, China Ministry of Education, China Sport General Administration and Chinese postdoctoral science foundation. Currently, Dr. Wang is a member of Program for New Century Excellent Talents in University, one of Executive Board members of Asican Council of Exercise and Sport Science, Committee Member of Sports Psychology and Sports Management, Chinese Society of Sports Science, Psychological Expert in National Swimming team, Director of Hubei Society of Psychology and Vice‐President of Sports Psychology Committee in P.R of China. ix
Table of Contents Volume 5 Effective IT Governance - Aligning the COBIT and ITIL Frameworks into a IT Academic Curricula Vanco Cabukovski, Vase Tusevski ·························································································································· 1 A Study of Process Optimization Using Computational Intelligence Approaches Chao-Ton Su,C. Alec Chang ·································································································································· 6 Management of Highly Dynamic Processes Based on Monotonic Reasoning Assistance Klaus P. Jantke, Christoph Vogler, Oksana Arnold, Hans-Rainer Beick ······························································ 10 A Study on Blocks of Knowledge Creation Zhang Xiangyang ·················································································································································· 19 Key Technologies for Decision-making of Emergency Command in Chemical Industrial Region CHEN Chen, ZHANG Xin Mei ····························································································································· 25 Design and Implementation of ETL Strategy in Tele-Communication Based on the Tool of Teradata Data Warehouse Zhang Qinhe , Li Min············································································································································ 31 Introductory Design, Description and Analysis of the Material Flow at an Intelligent Manufacturing Cell D. R. Delgado Sobrino, P. Košťál, A. Mudriková,K. Velíšek, M. Vlášek······························································· 37 Research on Teaching Resources Sharing Mechanism of Higher Education Park He Yongqiang, Li Yajuan ······································································································································ 42 Research on the Evolution of Immigration Risks in Water and Hydroelectric Projects Hou Jiangang, Zheng Tongtong ···························································································································· 47 A Retrieval Strategy for Texture Image Based on Micro-Feature Chun-Hua Qian, He-Qun Qiang ··························································································································· 52 Constructing Methods of Buffer Operators Based on the Weighted Mean Function Yang Shan,Wei Yong ·············································································································································· 60 The Impact of Culture on Electronic Marketplaces: A Preliminary Analysis from the Sellers’ Perspective Kevin K.W. Ho,Eric W.K. See-To ·························································································································· 66 Internet-Future Business Management Platform Focus Fang Xiang ··························································································································································· 70 Construction Automation: A Technology Perspective Tariq Shehab ························································································································································· 75 Comparison of Three HVAC Systems in Commercial Buildings from a Life Cycle Perspective Shuo Chen, Guomin Zhang ··································································································································· 82 Study on the Relationship between Job Analysis and Teachers’ Teaching Yun SU, Shengdou YIN, Hongyan BEN················································································································· 88 A Study on the Development Strategy of Ice and Snow Sports Tour Si GanDan ···························································································································································· 92 Customer Relationship Management Adoption of E-tourism Corporations Lijia Wen, Huaping Gong ····································································································································· 96
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Apply of the New Multimedia Educational Technologies in Open and Distance Education Yong-Min Liu, Wu-Yi Lu, Zhu-Fang Kuang ,Ai-Bin Chen ·················································································· 101 Dynamic Modelling, Simulation and Control of Doubly Fed Induction Generator Variable Speed Wind Turbine under Fault Seyed Zeinolabedin Moussavi , Reza Atapour ···································································································· 107 The Application Case of E-Commerce in an Agricultural Small Medium Enterprise in Beijing Jing Mu ······························································································································································· 116 Mobile Phone Screen System Research in Jails Han Qing,Xuanlin Ye ,Ren Shan,Min Jie,Haisheng Wang ·················································································· 121 The Influences of Accounting Informatization on Audit and Strategies Cheng Ping,Wu Yue············································································································································· 125 Teaching Design and Practice of OPNET Network Simulation Training JiaoLi Shi ···························································································································································· 130 Design of Service-oriented Business Training System Based on Customer Satisfaction Degree Yang Ding-quan,Le Lijun ···································································································································· 135 Research on Teaching Quality Assessment Based on Support Vector Machine Wang Tao, Wu Lin-li ··········································································································································· 141 Analysis of College Sports Consumption and the Sports Industry in China Long Wang, Yan-xia ZHANG ······························································································································ 147 The Relationship Research on the Physical Fitness and the Development of Sports Industry Yan-xia ZHANG , Long WANG ··························································································································· 152 Analysis and Discussion of Building and Sanitary Ceramics Product Sales Channels Hong Huang ······················································································································································· 156 Red Tides Prediction Using Fuzzy InferenceMethod Sun Park,Yeonwoo Lee,MyeongSoo Choi,cand Seong Ro Lee ··········································································· 161 Practice and Exploration of Bilingual Teaching in Electromagnetism Classes Qianzhao Lei······················································································································································· 165 Neural Network Modeling of Surface Quality in Magnetic Field Assisted Rotary EDM Hamid Baseri, Reza Teimouri ····························································································································· 170 Studies on the Pattern of Short-term Fluctuations in China's Business Cycles Lin Haitao, Chao Xueqin,Fu Zhankui ················································································································ 175 An Study on the Employment of College Students——Based on Social Network Analysis Liao Junhua ························································································································································ 181 Analysis of Contemporary College Student Cadres Training Liao Junhua ························································································································································ 185 Acoustic Analysis on Monosyllabic Tone of Yushu Dialect in Tibetan Li Liang, Ding Lijuan,Ma Li······························································································································· 189 On Sequential P Systems with Proteins Chun Lu, Xiao-jie Chen, Xiao-long Shi ·············································································································· 196 Analysis on Heterogeneous Characteristics of XBRL Taxonomies Based on Ontology LI Ji-mei, ZHAO Hui-zhou, DU Mei-jie ············································································································· 202 The Researches on Relationship of Positive Psychological Capital and Value Orientation of Career Choice about University Students in China LI-Li, CHU-Li rong············································································································································· 209 Advances in Water Resources Security Pre-warning Qu Qiang, Chang Mingqi, Xu Lei, Wang Yue, Lv Meizhao, Lu Shaohua ··························································· 216 xii
Game Analysis of Bargaining Power in International Iron Ore Trade Gong Jianxia······················································································································································· 223 Generation Management in Grid-Connected Renewable Systems with NaS Battery Storage Rodolfo Dufo-López, José L. Bernal-Agustín ····································································································· 229 Electric Vehicles: Why and How José L. Bernal-Agustín, Rodolfo Dufo-López, Juan M. Lujano-rojas································································· 235 Guidelines to Build an Intelligent Predictive Monitoring System for Synchronous Compensators Robson Florêncio Félix, Erik Leandro Bonaldi, Levy Ely de Oliveira, Luiz Eduardo Borges da Silva, Germano Lambert-Torres·················································································· 241 Study on Improving Resource Sharing in Higher Education Park by Grid Technology He Yongqiang ······················································································································································ 247 Distance Education Practices in China YUAN Ping, SUN Bo Cheng ······························································································································· 253 Hybrid Models for Performability Evaluation in Power Systems Mariana Dumitrescu ··········································································································································· 258 A Software for Computing Electric Power Systems Fuzzy Safety Mariana Dumitrescu ··········································································································································· 265 China Should Give Priority to the Development of Renewable Energy in Rural Areas Jia Quanxing······················································································································································· 272 The Legal Status of Solar Energy in Some European Countries and Iran Mehdi Mostofi, Noushin Ahanrobay ··················································································································· 276 The Designing Angle and Application Research of Intelligent Clothing Liu Chunyu, Sun Jing ·········································································································································· 281 Sustainable Toilet for a Developing Nation Jay N. Meegoda, H. N. Hsieh, P. Rodriguez,J. Jawidzik····················································································· 286 The Need of Experiencing Cognitive Psychology Principles for Students of (Business) Informatics Trimmel Michael ················································································································································· 292 Knowledge Cycle and Changes of Knowledge Based Organisation Functions Nicolescu Ovidiu, Nicolescu Ciprian·················································································································· 296 Author Index ··························································································································································· 302
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Author Index
A A. Mudriková ························································ 37 Ai-Bin Chen ························································ 101
C C. Alec Chang ························································· 6 Cand Seong Ro Lee ············································· 161 Chang Mingqi······················································ 216 Chao Xueqin························································ 175 Chao-Ton Su ···························································· 6 CHEN Chen ·························································· 25 Cheng Ping ·························································· 125 Christoph Vogler···················································· 10 CHU-Li rong ······················································· 209 Chun Lu ······························································· 196 Chun-Hua Qian ····················································· 52 D D. R. Delgado Sobrino ·········································· 37 Ding Lijuan ························································· 189 DU Mei-jie ·························································· 202
L Le Lijun ······························································· 135 Levy Ely de Oliveira ··········································· 241 LI Ji-mei ······························································ 202 Li Liang ······························································· 189 Li Min ···································································· 31 Li Yajuan ······························································· 42 Liao Junhua ··············································· 181、185 Lijia Wen ······························································· 96 LI-Li ···································································· 209 Lin Haitao ···························································· 175 Liu Chunyu ·························································· 281 Long Wang ·························································· 147 Long WANG························································ 152 Lu Shaohua ·························································· 216 Luiz Eduardo Borges da Silva ····························· 241 Lv Meizhao ························································· 216 M M. Vlášek ······························································ 37 Ma Li ··································································· 189 Mariana Dumitrescu ·································· 258、265 Mehdi Mostofi ····················································· 276 Min Jie ································································· 121 MyeongSoo Choi················································· 161
E Eric W.K. See-To ··················································· 66 Erik Leandro Bonaldi ·········································· 241 F Fang Xiang ···························································· 70 Fu Zhankui ·························································· 175
N Nicolescu Ciprian ················································ 296 Nicolescu Ovidiu ················································· 296 Noushin Ahanrobay ············································· 276
G Germano Lambert-Torres ···································· 241 Gong Jianxia························································ 223 Guomin Zhang ······················································ 82
O Oksana Arnold ······················································· 10
H H. N. Hsieh ·························································· 286 Haisheng Wang···················································· 121 Hamid Baseri ······················································· 170 Han Qing ····························································· 121 Hans-Rainer Beick ················································ 10 He Yongqiang ·············································· 42、247 He-Qun Qiang ······················································· 52 Hong Huang ························································ 156 Hongyan BEN ······················································· 88 Hou Jiangang ························································· 47 Huaping Gong ······················································· 96
P P. Košťál ································································ 37 P. Rodriguez ························································ 286 Q Qianzhao Lei ······················································· 165 Qu Qiang ····························································· 216 R Ren Shan ····························································· 121 Reza Atapour ······················································· 107 Reza Teimouri ····················································· 170 Robson Florêncio Félix ······································· 241 Rodolfo Dufo-López ································· 229、235
J J. Jawidzik ··························································· 286 Jay N. Meegoda ··················································· 286 Jia Quanxing························································ 272 JiaoLi Shi ···························································· 130 Jing Mu································································ 116 José L. Bernal-Agustín ······························ 229、235 Juan M. Lujano-rojas··········································· 235
S Seyed Zeinolabedin Moussavi····························· 107 Shengdou YIN ······················································· 88 Shuo Chen ····························································· 82 Si GanDan ····························································· 92 SUN Bo Cheng ···················································· 253 Sun Jing ······························································· 281 Sun Park ······························································ 161
K K. Velíšek ······························································ 37 Kevin K.W. Ho ······················································ 66 Klaus P. Jantke ······················································ 10
T Tariq Shehab ·························································· 75 Trimmel Michael ················································· 292 302
Author Index
V Vanco Cabukovski ··················································· 1 Vase Tusevski ·························································· 1
W Wang Tao ····························································· 141 Wang Yue ···························································· 216 Wei Yong ······························································· 60 Wu Lin-li ····························································· 141 Wu Yue ································································ 125 Wu-Yi Lu····························································· 101
Y Yang Ding-quan··················································· 135 Yang Shan······························································ 60 Yan-xia ZHANG ······································· 147、152 Yeonwoo Lee ······················································· 161 Yong-Min Liu ······················································ 101 YUAN Ping ························································· 253 Yun SU ·································································· 88 Z Zhang Qinhe ·························································· 31 Zhang Xiangyang ·················································· 19 ZHANG Xin Mei ·················································· 25 ZHAO Hui-zhou ·················································· 202 Zheng Tongtong ···················································· 47 Zhu-Fang Kuang ················································· 101
X Xiao-jie Chen ······················································ 196 Xiao-long Shi ······················································ 196 Xu Lei·································································· 216 Xuanlin Ye ··························································· 121
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2011 International Conference on Future Management Science and Engineering Lecture Notes in Information Technology, Vol.5-6
Guidelines to Build an Intelligent Predictive Monitoring System for Synchronous Compensators Robson Florêncio Félix1, a, Erik Leandro Bonaldi2,b, Levy Ely de Oliveira2,b, Luiz Eduardo Borges da Silva2,b, Germano Lambert-Torres2,b 1
CHESF – San Francisco Power System Co. - Rua Delmiro Gouveia, 333 - Recife - PE - Brazil 2
NEPEN – Northeast Research Center - Av. Tancredo Neves 5655 – Aracaju - SE- Brazil
a
[email protected] b{erik.bonaldi, levy.oliveira, leborgess, germanoltorres}@gmail.com
Keywords:Data mining, Intelligent system, Monitoring system, Power system operation, Synchronous compensator, Predictive maintenance.
Abstract.This paper describes a project which envisages the development of equipment for diagnostic and predictive monitoring of operational requirements of synchronous compensators. A system of extracting features has been developed using intelligent data mining techniques to relate possible elements that contribute to premature degradation of such equipment. Rough set techniques have been used which attempts through sets of upper and lower approximation to determine the most appropriate frontier for the classification process. The developed system classifies with success the state operating system in "normal operation", "alert" or "failed". The prototype system is in operation in a CHESF Power System Co. synchronous compensator. 1.
Introduction
The generating capacity of both real power and reactive power of power electrical systems represents a crucial point in the operation of the system. The economic implications of this operation are enormous and the assurance that the components responsible for such an operation must be obtained to operate correctly at any cost. Usually, with a continuous work, both the generators and the synchronous compensators, feeding electric system loads, are subjected to stresses, that can cause failures and loss of its generation capacity, resulting in uncertainty about its actual nominal capacity [1]. Therefore, a careful and rigorous evaluation of the reduction of operational capacity will produce, sure, a substantial increase of reliability of the equipment, a visible reduction of costs in respect of the correct treatment involving preventive properly performed and the possibility to prevent unscheduled downtime of such equipment. Unscheduled interruptions in the operation of synchronous compensators should be avoided due to the great importance of such equipment for power transmission systems and the value associated with the remuneration of the availability of these assets. To this effect to be achieved, a series of maintenance procedures was developed over the past forty years. Initially only the procedures involving corrective maintenance were used. That is, if the equipment had failed began a repair procedure involving, of course, interruption in the availability of the equipment in question. As time passes and the accumulation of knowledge involving the operation of the equipment were developed preventive maintenance procedures that trigger the process of maintenance before the failure happen, based on the history of each specific piece of equipment under supervision. This procedure, although it produces a satisfactory result with regard to the reduction of non-scheduled interruption of equipment, often in pre-programmed maintenance unnecessary, because the equipment that has 978-1-61275-001-9/10/$25.00 ©2011 IERI
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suffered the intervention is in perfect working order, even having been run by a number of hours the average of the same type of equipment would be indicating the proximity of a failure. Recently, with the advancement of acquisition digital systems and signal processing, another maintenance strategy was developed. This new technique, called Predictive Maintenance, has as primary objective the development of a diagnostic process equipment under supervision, so that the indication for a maintenance intervention only if take when the operating state of the equipment were to present a major deterioration in condition, stating to the level of deterioration in which the same meets and showing an estimate of how long it can continue to operate without a widespread panic will happen. This maintenance strategy, although much more rational, implies sophisticated systems of management of the variables involved in the operation of the equipment in question [1, 2]. In the case of electric synchronous compensators, the condition of isolation represents an important point of failure and concern. Other important points to strengthen the diagnosis in a predictive analytics that can also be listed would be: bearings, unwanted vibrations, partial discharges, alignment, balancing, etc.[3]. This project envisages the development of equipment for surveillance and predictive diagnosis of synchronous compensator operating conditions for CHESF – San Francisco Power Company, located in Northeast of Brazil. This project applies predictive techniques for the diagnosis of the State of large synchronous compensators using digital processing techniques of the information contained in the electrical variables involved in the operation of the compensator. It is basically a device for manipulating magnetic fields, it is possible to infer that any operational conditions of the equipment, somehow, will influence the behavior of the magnetic field, reflecting noticeably in tensions and currents supplied by him. Through the information contained in voltages and currents, extracted after an appropriate signal processing, it is possible to obtain an assessment of the operational state of synchronous compensator. For the analysis and diagnosis should be used Rough Set Theory [4, 5]. The system, after the evaluation of the operational conditions, should send for a supervisory centre a sign "normal operation", "alert" or "failed", thus helping in the decision-making process of the maintainer to intervene in the equipment. All system information are sent via network Eternet. 2. Description of the Methodology In the case of synchronous compensators, two approaches could be listed in order to guide the deployment of the evaluation methodology of operational condition of the equipment. The first concerns A smart data mining in the database involving the system of supervision and maintenance of the plant in which the equipment is inserted, to use the existing historic data to perform the type of problems and their possible causes. The second approach is based on a data acquisition system developed adequately connected to pay to do a sampling of some important variables involving the operation of the equipment. In this project, the condition of compensator isolation represents an important point of failure and concern. Other important points to strengthen the diagnosis in a predictive analytics that can also be listed are: bearings, unwanted vibrations, partial discharges, alignment, balancing, etc. Equipment for monitoring and predictive diagnosis of compensating operating conditions has been developed based on the digital processing of the information contained in the electrical variables involving the operation of the equipment. The system, based on information obtained specifically for electrical voltages and currents, is able to infer about the operational conditions of the equipment, because the pattern involving the behavior of variables monitored presents some degree of correlation with the deteriorating operational conditions. Through the information contained in the signals collected, extracted after an adequate digital signal processing, it is possible to obtain an assessment of the state supervised equipment operating. The system consists primarily of current and voltage transducers with proper passage, bandwidth recently made available on the international market at reasonable prices, a signal conditioning circuit 242
to match the signal measured by data acquisition circuit, a circuit analog/digital conversion speed and resolution, a DSP type microprocessor for processing and storage of electrical variables and measures of an intelligent program data consolidation, evaluation and diagnosis of operational condition of the equipment. Two techniques have been used in this equipment. The first detects, through a specific pre-processing of signals obtained by transducers, the most important features of the signal. The second analyzes the characteristic of equipment degradation based on artificial intelligence algorithms that correlate to the data of the equipment throughout its operational life, making a diagnosis of equipment operating conditions, suggesting interventions and showing an estimate of time for which they have to be made. 3. Implementation of the Diagnostic Program The goal of the system is to obtain a diagnostic program able to assess the patterns of failures and features extracted from the current and voltage signals acquired synchronous compensator. To this end, it was developed a parsing algorithm that used the trend curves of the patterns and characteristics extracted, along with levels of alarm, to evaluate the condition of the equipment being monitored. The implemented algorithm and structures were integrated into the system, allowing addition of acquisition and processing of acquired signals its presentation and validation according to severity assessment criteria. These criteria, determined by the alarm levels, are then presented in the form of three possible conditions: "normal operation", "alert" or "failed". The internal structures, organization and methodology of the program are described in the following sections. 4. The Diagnostic Program The diagnostic program is able to get current and voltage signals of an acquisition device and extracting patterns and characteristics of these signals. Then the system analyzes and interprets the values of these signals, taking into consideration the equipment being analyzed, with the purpose of estimating the condition of synchronous compensator in analysis. Figure 1 presents an overview of the diagnostic program. It is important to note that the diagnostic program is based on processing of three types of information: trend curves, alarm levels and compensator data construction and operation.
Fig. 1. Overview of the Diagnostic Program. 243
Alarm levels associated with each one of the patterns and characteristics extracted represent the knowledge of an expert or an experience-based knowledge, acquired through the analysis of history. Synchronous compensator data reported to the system consist of constructive data and basic operation data. Finally, the trend curves are a representation of the patterns and characteristics extracted through extraction algorithm. The core of the algorithm processes the information available and determines the condition of the compensator by means of a diagnosis represented by one of the three possible operation states. In cases where there is no alarm level preset, the diagnostic program classifies as "no review" and in cases where there is no sample of a particular pattern or parameter, it was classified as "component" or "without" parameter. 5. Trend Curves The trend curves represent one of the most important structures of the diagnostic program. In addition to serve as a resource of analysis for the operator (which verifies the behavior of each visual shape pattern), also serves as a foundation of analysis for the diagnostic program. The diagnosis through predictive maintenance techniques is extremely dependent on the so-called comparative analysis. Whereas the operation of the machine suffers few amendments during its useful life, it is possible to understand that changes in the characteristics and patterns are monitored and indications of the emergence of seeding machine failures. Comparing the current situation of machine with values from the same machine in a period where his condition was known to be good, may reveal deviations in your condition. Thus, each trend curve is associated with a specific pattern or characteristic, and presents the amplitudes of this pattern associated with a time marker. Therefore, the basis of every trend curve is the so-called time series. In Statistics, a time series is a collection of observations taken sequentially over time. Unlike some linear regression models, time series in the order of the data is fundamental. A very important characteristic of this data type is that neighboring observations are dependent and the interest is to analyze and model this dependency. Through the analysis of time series of statistical standards and the latest figures provided by it, the program is able to identify an anomaly and then determine the severity of a failure or deviation in the operation of synchronous compensator. 6. Data from Synchronous Compensator Both for the calculation of patterns and characteristics as to the assessment of the condition of synchronous compensator, technical parameters, construction and operation are the extreme importance. Used throughout the system, these data are organized in fields where each field of this structure represents the different technical characteristics of the compensator in analysis. All parameters are stored in the database, and a human machine interface allows the operator to insert and change these data. 7.
Alarm Levels
Alarm levels are reference values provided to the system by the user. They are associated with a particular pattern or characteristics, and they are determined by an expert or some process based on analysis of historical failures of equipment. Without these levels, the diagnostic system is only able to identify variations in the amplitude of the failure, but is not able to assess the severity of the failure. In this predictive maintenance system, the employed diagnostic methodology is based on severity. These severity charters inform to the system what the expected values for each of the monitored parameters. The figures provided by the charters of severity may vary according to the equipment, operation scheme and constructive characteristics of the machine. There are several factors that 244
influence the quality of a charter of severity, as its capacity of generalization (adapt to different machines and conditions), accuracy (inform with good confidence the actual equipment condition), among others. On the developed system, alarm levels are the structure used to represent a charter of severity. These levels are reference values provided to the system that indicate the boundaries of alarm and failed. When the magnitude of a particular pattern exceeds the level of "normal" means that the equipment is developing a fault and the same should be monitored. Already when the amplitude exceeds the level of "alarm" means that the flaw is in an advanced stage, where a break is imminent and a maintenance action is recommended. Figure 2 illustrates how the application of alarm levels under trend curves is an effective approach of fault diagnosis. Notice 4 special points in the trend curve. In the point A, this part of the trend curve is in the normal area. Note that the amplitude values change but inside the normal region. In the point B, the system leaves the normal region and passes to the attention region. In the point C, the system is compromised. The failure has usually an exponential evolution. In the point D, the system leaves the attention region and passes to the emergency region.
Fig. 2. Trend curve and alarm levels.
In the developed system, the alarms levels can be stored in three different ways: • Absolute: the user specifies an absolute value, that is compared with the absolute value of the magnitude of the failure; • Percentage: the magnitude of the failure is compared with its own reference, in the form of a percentage (e.g. attention if 20% above the reference); • Difference in dB: like percentage, just that using a logarithmic scale, the decibel scale. Finally, the core of the diagnostic algorithm processes each of the patterns and features extracted from their respective levels of alarm. The general condition of each measurement technique or synchronous compensator as a whole is obtained through an analysis of the worst case, where the most severe condition is propagated to higher levels until the general condition of the equipment. Figure 3 illustrates the propagation system from the worst case. In the case, the state of "failed" has always priority if compared to the state "alert" or "normal" and so on. As seen in the Figure 3, if there is a pattern of CSA analysis in "normal" condition, a default in the analysis VSA in condition "attention" and a default in the parsing EVPA provided "emergency", the final state of synchronous compensator is considered as "failed".
245
Fig. 3. Illustrative pictorial example of a diagnostic process.
8. Conclusions This paper describes a system to predictive maintenance of synchronous compensators. A diagnostic program was developed and implemented in CHESF Power System Co.. This program is able to analyze patterns and features extracted from the synchronous compensator and diagnose its condition based on alarm levels provided to the expert. The diagnostic program was developed using classes and structures of extraction and processing algorithm. Tables and extracted pattern characteristics were established and storage. Classes and structures that represent the trend curves of the patterns and extracted characteristics extracted were also developed and implemented. The system is currently in operation in the CHESF power system substation, in the Brazil Northeast region with good results. References [1] E.L Bonaldi - Failure Predictive Diagnostic in Three-Phase Induction Motors with MCSA and Rough Set Theory. Ph.D. Thesis, Itajuba Federal School of Engineering, Itajuba – Brazil, 2006, in Portuguese. [2] S. M. A. Cruz e A. J. M. Cardoso, “Diagnosis of the Multiple Induction Motor Faults Using Extended Park’s vector Approach” in International Journal of Comadem, pp 19-25, 2001. [3] M. H. Benbouzid, “A Review of Induction Motors Signature Analysis as a Medium for Faults Detection”, IEEE Transactions on Industrial Eletronics, vol. 47, pp. 984-993, Oct. 2000. [4] Z. Pawlak – “Rough Sets”, Int. J. Information and Computer Science, Vol.11, pp.341-356, 1982. [5] S. Rissino, and G. Lambert-Torres- “Rough Set Theory – Fundamental Concepts, Principals, Data Extraction, and Applications”, In: Ponce, J., Karahoca, A. (eds.) Data Mining and Knowledge in Real Life Applications., pp. 35-58, ISBN 978-3-902613-53-0, In-Tech Press, 2009.
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