MAINTENANCE ORIENTED DISTRIBUTED COOPERATIVE DECISION SUPPORTED SYSTEM FOR HYDROPOWER PLANT
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Abstract:
Condition-based maintenance (CBM) is a systematic project, and the information coming from equipments condition, water and market must be all taken into account. In order to reduce the equipment downtime and the maintenance cost, the maintenance strategy in hydropower plants has to be progressively changed from time-based maintenance (TBM) to CBM. It is very important issues that how to achieve the harmony among the operator, expert and the computer, maintenance oriented distributed cooperative decision supported system (MoDCDSS) for hydropower plants is presented in this paper. The principle and the method of distributed cooperative diagnosis decision making are discussed, which adopt three technologies, such as computer supported cooperative work (CSCW), agent and virtual reality (VR). The systematic goal, framework and function are particularly introduced, and the implementation method of hardware and software is proposed. The MoDCDSS has been already put into operation in Gezhouba hydropower plants, the result shows good.Keywords:
Downtime
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With the developing of industry, maintenance has become an important factor that influences survival and development of business. As an interdisciplinary activity, maintenance management needs technical support from computer decision support system when using that knowledge. There are numerous pieces of equipment in a power plant, but the maintenance requirements are different for different equipment. Making condition based maintenance in a power plant is a systemic and integrative maintenance management activity which needs a special maintenance decision support system. As a main developing direction of decision support system, intelligent decision support system has got a comprehensive and successful application in many domains. According to the characteristic of operation and maintenance in a power plant, an intelligent maintenance decision support system is designed in this paper where the system goal, function, framework and platform are particularly introduced.
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Maintenance resource is a main part of maintenance support system.However,how to forecast the maintenance resources demand scientifically and reasonably is a hot and austere task.According to the practical needs of equipment maintenance support,based on analyzing the operation process of maintenance support system,a simulation flow chart is established by UML.Based on the requirement analysis of the software and the function module and database design,the development of the simulation system is realized by using VB language and Access database.At last,a case is applied to the software,which validates that the simulation system can forecast the demand of maintenance resource exactly and speedily.It can provide scientific information for maintenance support of equipment.
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Equipment maintainability support is the most important influencing factor which affects weapon battle ability. Guided by the theory of visualization of equipment support management, this paper discusses the research content and construction goals of maintenance support visualization management expert system based on equipment maintenance support of weapon design, manufacture, storage and use dept. Based on analysis of equipment maintenance support, maintenance support scenario establishment approach is discussed in paper. The overall framework model of the system is brought forward. Its hardware, software and architecture are analyzed. At last service-oriented software development method is used to develop equipment maintenance expert system. Decision-makers can establish rational maintenance scenario according to evaluation result and arrange maintenance tasks. Weapon equipment development department and army can optimize maintainability support scheme based on evaluation result and maintain equipment.
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Equipment maintenance is one of the essential tasks for manufacturing industries. There have been a number of information systems developed to cope with equipment malfunctions. Most fault diagnosis systems are applications of expert systems which have two drawbacks with regard to knowledge acquisition. One is the lack of knowledge continuity; the other is the limited source of knowledge being incapable of combining knowledge of entire workforce. In this study, we propose an equipment maintenance decision support system architecture with a flexible knowledge maintenance methodology. A case implementation to a sewage management company with multiple distributed plants is introduced to show that the proposed approach helps more efficient utilization of experience-based knowledge in maintaining equipments.
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As the growing of individual demand and the requirement of environmental protection, the species of modern rail traffic equipment are increasing. System integration and coupling complexity require the maintenance personnel's knowledge, which also increases the economic burden of the enterprise. This study proposes a new 3D visualization and collaborative maintenance method for the product maintenance of rail traffic equipment manufacturing enterprises, which enables maintenance staff and experts to complete the collaborative operation or guiding behavior by integrating the information models of maintenance process and maintenance schedules based on human-computer interaction, information visualization and sharing methods. This technical scheme will establish a good platform that avoids the disadvantage of the traditional maintenance process guidance way. This work can improve the efficiency of maintenance work and reduce the waste of resources in the maintenance process.
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For prevention of failure and extension of maintenance interval, many Asian power companies have continuously tried to apply Condition Based Maintenance system to their plants. However, only few companies succeed to change their maintenance system from fixed time based to equipment condition based, although there are many brand new ITs, such as high speed computing system, huge storage device, and advanced development software tools. This paper describes the reasons why they failed to change and proposes the solutions to construct maintenance management system based on equipment condition. The solutions were also applied practically to power plant in Korea.
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With the developing of industry, maintenance has become an important factor that influences survival and development of the business. There are numerous pieces of equipment in a power plant, but the maintenance requirement is different for respective equipment, so making condition based maintenance in a power plant is a systemic and integrative activity in maintenance management. As an interdisciplinary activity, a special maintenance decision support system is necessary to aid operating and maintenance personnel use that knowledge right and well. As a hotspot of Distributed Artificial Intelligence research, agent technology is one of the strongest tools for constituting large-scale distributed and open computer-based systems. This paper briefly introduces decision support system and agent technology, and presents an architecture of multiagent based maintenance decision support system used for power plant equipment, and describes its architecture, function and decision making process in detail.
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It is an inexorable trend to replace the traditional periodical maintenance with condition based maintenance (CBM) progressively, but the main difficulty that many power transmission and transformation enterprises will face with is how to rationally choose the equipments to develop the CBM in large complicated power grids and how to successfully realize the transition from current situation mode of equipment maintenance to CBM. Considering the factors such as technical support needed by CBM and the personal performance and so on, and on the basis of existing technological condition and management level, a thinking of whether power equipments can be brought into CBM or not is put forward according to the experts decision on known information and using fuzzy comprehensive evaluation.
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