陈坚红,吴文健,万安平,王异成,李鸿坤,盛德仁
CHEN Jianhong,WU Wenjian,WAN Anping,WANG Yicheng,Li Hongkun,SHENG Deren

• 1:浙江大学热工与动力系统研究所
• 2:国网浙江省电力公司电力科学研究院

摘要(Abstract)：

针对当前燃气轮机关键部件维护及维修管理中由人工统计计算维修间隔,造成费时耗力、准确性低的问题,提出燃气轮机视情维修决策模型,结合燃气轮机已经运行时段的历史运行数据和待预测时段的实际运行计划,对部件维修周期进行预测。提出等效服务系数的概念,根据2个时段的等效服务系数,建立4种预测模型,并利用ASP.NET技术,实现了基于B/S架构的燃气轮机视情维修决策系统。该系统可在线自动计算燃气轮机相关部件的使用寿命,并决策计算维修周期,为科学制定维修计划和进行备件信息管理工作奠定基础。该决策系统已应用于工程实际,取得了良好的效果。
Aiming at time-consuming, labor-intensive and low-accurate manual statistical calculation in key part maintenance and maintenance management of gas turbines, this paper proposes a condition-based maintenance decision-making model for gas turbine which predicts component maintenance cycle in combination with historical operation data of gas turbine in the past running period and actual operation plans in the predictive period. The concept of equivalent service factor is proposed. Based on whether the equivalent service factors of two periods are equal, four decision-making models are established, and by using ASP.NET technology, a condition-based maintenance decision-making system based on B/S structure for gas turbine is developed. The system can calculate service life of relevant components of gas turbine automatically online and determine and calculate maintenance cycle to lay a foundation for making scientific and feasible maintenance plan and conducting information management of spare parts. Finally, the decision-making system is put into engineering practice, from which favorable application effect was achieved.

关键词(KeyWords)： 燃气轮机;PI实时数据库;等效服务系数;视情维修;寿命预测
gas turbine;PI real-time database;equivalent service factor;condition-based maintenance;life prediction

Abstract:

Keywords:

基金项目(Foundation):

作者(Author): 陈坚红,吴文健,万安平,王异成,李鸿坤,盛德仁
CHEN Jianhong,WU Wenjian,WAN Anping,WANG Yicheng,Li Hongkun,SHENG Deren

DOI: 10.19585/j.zjdl.2014.10.014

参考文献(References)：

• [1]冯葵清,金晶.建设燃气—蒸汽联合循环电站改善环境质量[J].中国电力,1999,32(2):13-16.
• [2]VERMA A K,SRIVIDYA A,RAMESH P G.A Systemic Approach To Integrated E-Maintenance of Large Engi neering Plants[J].International Journal of Automation&Computing,2010(02):173-179.
• [3]NIU G,YANG B S,PECHT M.Development of Anoptimized Condition-Based Maintenance System By Data Fusion and Reliability Centered Maintenance[J].Reliability Engineering and System Safety,2010,7(95):786-796.
• [4]TIAN Z,JIN T,WU B,et al.Condition Based Maintenance Optimization for Wind Power Generation Systems Under Continuous Monitoring[J].Renewable Energy,2011,36(5):1502-1509.
• [5]殷豪,孟安波,彭显刚.大型燃气轮机检修策略的研究[J].电站系统工程,2009(04):36-38.
• [6]龚文强,王庆韧.基于EOH分析的燃机检修策略优化[J].中国电力,2011,44(8):40-42.
• [7]刘昱.联合循环机组辅助决策系统的设计与实现[D].浙江大学,2007.
• [8]李蔚,盛德仁,陈坚红,等.电厂实时监控信息系统的设计与应用[J].中国电机工程学报,2003(12):218-221.
• [9]洪慧,杨卫国,林中达.PI数据库及其在电厂SIS中的应用[J].电力自动化设备,2005,24(11):69-72.
• [10]BALEVIC D,BURGER R,FORRY D.Heavy-duty gas turbine operating and maintenance considerations[R].GER-3620,General Electric,2004.
• [11]方明霞.PI数据库在浙江电网的应用现状与展望[J].浙江电力,2010(4):51-54.
• [12]蒙永苹,许勇,王俊永,等.基于PI数据库的实时动态监测系统(WAMS)的建设与应用[J].电力设备,2007,8(7):36-40.