基于AHP-RBR的燃气轮机压气机故障诊断方法研究Study on Gas Turbine Compressor Fault Diagnosis Method Based on AHP-RBR
彭道刚,姬传晟,涂煊,戚尔江
PENG Daogang,JI Chuansheng,TU Xuan,QI Erjiang
摘要(Abstract):
燃气轮机压气机在高转速的工作环境下运行经常会发生故障,严重时会造成燃气轮机非计划停机。为了诊断压气机的故障类型,提出基于AHP(层次分析法)的RBR(规则推理)故障诊断方法。该方法针对规则推理模型不能确定各故障征兆参数对压气机故障类型影响权重的问题,采用了层次分析法对各故障征兆参数进行分析,利用专家知识、经验和压气机故障案例分析,综合确定相对客观的各故障征兆参数权重,有效提高了规则推理故障诊断方法的准确性。仿真结果表明:与RBR模型相比,AHP-RBR模型准确率更高,可为燃气轮机压气机的故障诊断提供方法参考。
Gas turbine compressor failure often occurs in high-speed operation. In severe cases, it may cause an unplanned shutdown of the gas turbine. To diagnose the type of compressor malfunctions, an RBR(rulebased reasoning) fault diagnosis method based on AHP(analytic hierarchy process) is proposed. As the RBR model cannot determine the influence weight of each fault symptom parameter on the compressor fault type,the AHP is adopted to analyze the weight of each fault symptom parameter. By use of expertise, experience and compressor failure case analysis, the relatively objective weight of each failure symptom parameter is determined, and the accuracy of the rule-based reasoning fault diagnosis method is improved. The simulation results show that AHP-RBR, in contrast to RBR, is of higher accuracy and can provide a reference for fault diagnosis of the gas turbine compressor.
关键词(KeyWords):
层次分析法;规则推理;压气机;故障诊断
analytic hierarchy process;rule reasoning;compressor;fault diagnosis
基金项目(Foundation): 国家科技重大专项(2017-V-0011-0063);; 上海市“科技创新行动计划”地方院校能力建设专项项目(19020500700)
作者(Author):
彭道刚,姬传晟,涂煊,戚尔江
PENG Daogang,JI Chuansheng,TU Xuan,QI Erjiang
DOI: 10.19585/j.zjdl.202104015
参考文献(References):
- [1]蒋洪德,任静,李雪英,等.重型燃气轮机现状与发展趋势[J].中国电机工程学报,2014,34(29):5096-5102.
- [2]杜景琦,赵明,殷捷,等.电厂发电设备故障诊断方法综述[J].云南电力技术,2018,46(5):88-96.
- [3]黄郑,周建新,李家伟,等.基于改进型强跟踪卡尔曼滤波的燃气轮机机组气路故障诊断研究[J].热能动力工程,2017,32(5):50-56.
- [4]崔建国,刘瑶,于明月,等.基于深度学习与信息融合的燃气轮机故障诊断[J].机械设计与制造,2019(12):28-31.
- [5]王文祥,安维峥,王维民,等.基于模糊综合评判与故障树法的燃气轮机故障诊断[J].船舶工程,2013,35(增刊1):52-55.
- [6]尚文,王维民,齐鹏逸,等.基于条件规则与故障树法的燃气轮机故障诊断[J].机电工程,2013,30(7):798-801.
- [7]谷思宇,李刚.GE LM2500+SAC型燃气轮机压气机积垢判据的确定[J].油气储运,2016,35(7):763-767.
- [8]赖安卿,谭燕,李世林.压气机叶片边缘磨损对其性能的影响研究[J].计算机仿真,2020,37(5):20-24.
- [9]王伟影,王健丰,崔宝,等.基于时间序列模型的燃气轮机气路性能退化预测[J].热能动力工程,2016,31(1):50-55.
- [10]苏三买,孙占恒,吕烨,等.压气机失速与喘振动态模型与仿真[J].推进技术,2016,37(5):960-965.
- [11]韩朝兵,朱泓逻,黄伟栋,等.压气机离线水洗后燃气轮机性能衰退分析研究[J].动力工程学报,2019,39(8):626-623.
- [12]李世尧,李振林,王颖,等.部件性能退化对燃气轮机运行状态的影响[J].油气储运,2019,38(8):911-918.
- [13]陈仁贵,陶月.燃气轮机进气系统结霜分析及对策[J].热能动力工程,2005,20(6):647-649.
- [14]方国民.9E燃机压气机防喘设备及其故障检修[J].浙江电力,2012,31(11):82-84.
- [15]汪旸,徐彪,周超凡,等.基于层次分析法的输电断面综合监控方法[J].中国电力,2019,52(4):89-95.
- [16]王岭,王晓华,吴进新.层次分析法和灰色关联法在发电厂设备运行状态评估中的综合应用[J].浙江电力,2019,38(2):110-114.
- [17]徐敏,陈全,张锦文,等.基于规则推理的继电保护动作行为评价的新方法研究[J].郑州大学学报(工学版),2014,35(1):116-119.
- [18]唐磊,陈启卷,王卫玉,等.基于征兆驱动和专家推理的水电机组轴承状态分析[J].水电能源科学,2018,36(5):137-141.