水电机组状态检修中若干关键技术研究
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摘要
状态检修能最大限度地延长检修间隔,降低水电厂的运行成本,保证安全生产,为国民经济的持续发展保驾护航,水电厂的检修体制逐步由计划检修向状态检修过渡。然而由于水电机组是一个涉及到水力、电气和机械的复杂系统,人们对其故障机理、诊断策略、监测诊断系统数据通道、机组寿命评估体系、检修决策支持系统等的研究力度不足。水电机组状态检修围绕降低机组设备维护成本,提高设备利用率和检修的预见性,它不仅涉及到电力设备各个专业、多学科的技术问题,还涉及到一系列的管理科学上的问题。目前我国还没实现完全意义上的状态检修系统,因此对状态检修的若干关键技术的研究还是有着十分重大的现实意义。结合课题组多年来关于水电机组性能试验和在线监测故障诊断的课题,对水电机组故障机理、诊断方法、监测诊断系统数据通道、信号提取识别及预测展开研究,为最终实现水电厂状态检修提供一定的技术支撑。
故障机理的研究是开展故障诊断的基础,水电机组故障机理的研究力度不足以让人们辨识故障类型,开展状态检修。通过理论分析、数值模拟和真机测试相结合的方法,对天荒坪电站异常抬机、三峡左岸电站6 号机组小开度异常振动、水轮机转轮裂纹机理展开研究。研究表明:天荒坪电站抬机现象的主要原因是密封环泄漏量的变化导致轴向力发生变化,而引起泄漏量变化的可能原因是密封部位的堵塞或者损坏; “负流量”不可能是三峡小开度异常振动的原因,分析了“水体共振”是一种可能的原因; 作用在叶片上的静应力和动应力达到叶片材料的疲劳极限,并累计损伤造成的微裂纹和裂纹的扩展,是造成叶片振动疲劳断裂的原因之一,其中动应力值较大是引起转轮叶片产生疲劳裂纹的主要原因。
故障诊断方法关系到状态检修系统中对机组当前性能的合理评价,当前诊断方法不是很完善,传统方法或多或少在某些方面存在一些局限性。尝试引入CBR (Case Based Reasoning)诊断方法到水电机组故障诊断领域,降低了知识获取的难度; 对水电机组轴系模型进行一定改进,将轴系仿真结果作为故障诊断知识库,可缓解知识库瓶颈问题,通过对油膜力数据库插值获取油膜力,降低时间复杂度; 给出一种基于多方法诊断联盟的诊断策略,提高诊断精度。
According to condition based maintenance can mostly prolong the maintenance intervals and reduce operation cost, it can ensures safety operating of hydropower plants and the successive development of national economy. Nowadays, maintenance model is transferring from plan maintenance to condition based maintenance step by step. Since hydropower generator unit is a very complicated system that involving hydraulic, electrical and mechanical factors, such as the fault mechanism, diagnosis methods, data channel, evaluation principle of life and maintenance decision supporting system are not fully researched. Condition based maintenance system focuses on such fields as reducing units’maintenance cost, improving devices’operating efficiency and maintenance predictive. Since it is a difficult engineering includes electricity fields and management fields, there is no actual condition based maintenance system in real life. In line with performance test and monitoring diagnosis project that research team responded for, such key technologies for condition based maintenance as: fault mechanism, diagnosis methods, data channels, signal extracting, symptom identification and trend-based forecasting. All of these research can do some good for the eventually implementation of condition based maintenance.
Fault reasons analysis is essential for fault diagnosis. It does some research on the extraordinary runner hang-up in Tian Huangping Hydropower Station, the abnormal vibration of Three Gorges Hydropower Station left bank #6 generator unit under 4% guide vane opening and the mechanism of turbine runner crack. By means of theoretical analysis, numerical simulation and prototype test. Research results indicate: the main cause of hang-up is the variety of leakage discharge of sealing ring, which results in the change of axial force of shaft, and the jam or damage of seal parts may lead to the leakage discharge variation; “negative discharge”can not be the cause of abnormal vibration under small opening and possible reason of “fluid structure resonance”is also analyzed; when static and dynamic stress acted on runner blade reach fatigue limitation, accumulated fatigue damage may leads to the micro crack or extend of crack, is responsible for runner blade fracture, and excessive dynamic stress is the main cause.
And traditional diagnosis methods are not adequately. CBR (Case Based Reasoning) is introduced into hydropower generator sets fault diagnosis, and it lowers the difficulty of
knowledge acquisition; also shafting model of hydropower generator units is modified to relief the bottleneck of knowledge repository by implementing shafting simulation results as the fault diagnosis knowledge database. Since oil film force acquisition by interpolating the oil film force database, time complexity is reduced. A diagnosis strategy based on multi method diagnosis league is also introduced to improve the diagnosis accuracy. Equipments’operating conditions can be obtained through axis orbit and conventional identification algorithm of axis orbit is low accuracy or too complex. A new method of axis orbit automatic identification base on moment invariant is proposed. It acquires the axis orbit shape parameters to help operation personnel to deeper diagnosis by ways of optimization method. Since signal extract algorithm is critical to determine whether symptom reflects current operating conditions and signal trend-based forecasting algorithm effects the decision of future operating conditions, local weak signal is extracted based on harmonic wavelet and prediction in line with maximal Lyapunov exponent is introduced into hydro-generator unit fields Data channels are also analyzed: a hybrid network transmission model of B/S (Browser/Server) and C/S (Client/Server) is used to consist of distributed monitoring and diagnosis system; memory database is adopted to decrease the times of operation of hard disk and improve the real–time performance; a new intelligent data store algorithm is brought forward to reduce the data size that stored in database and also assures sufficient data to analyze; Matlab Web Server is the first time introduced into hydro-generator sets faults diagnosis to implement distributed remote monitoring and diagnosis system.
故障机理的研究是开展故障诊断的基础,水电机组故障机理的研究力度不足以让人们辨识故障类型,开展状态检修。通过理论分析、数值模拟和真机测试相结合的方法,对天荒坪电站异常抬机、三峡左岸电站6 号机组小开度异常振动、水轮机转轮裂纹机理展开研究。研究表明:天荒坪电站抬机现象的主要原因是密封环泄漏量的变化导致轴向力发生变化,而引起泄漏量变化的可能原因是密封部位的堵塞或者损坏; “负流量”不可能是三峡小开度异常振动的原因,分析了“水体共振”是一种可能的原因; 作用在叶片上的静应力和动应力达到叶片材料的疲劳极限,并累计损伤造成的微裂纹和裂纹的扩展,是造成叶片振动疲劳断裂的原因之一,其中动应力值较大是引起转轮叶片产生疲劳裂纹的主要原因。
故障诊断方法关系到状态检修系统中对机组当前性能的合理评价,当前诊断方法不是很完善,传统方法或多或少在某些方面存在一些局限性。尝试引入CBR (Case Based Reasoning)诊断方法到水电机组故障诊断领域,降低了知识获取的难度; 对水电机组轴系模型进行一定改进,将轴系仿真结果作为故障诊断知识库,可缓解知识库瓶颈问题,通过对油膜力数据库插值获取油膜力,降低时间复杂度; 给出一种基于多方法诊断联盟的诊断策略,提高诊断精度。
According to condition based maintenance can mostly prolong the maintenance intervals and reduce operation cost, it can ensures safety operating of hydropower plants and the successive development of national economy. Nowadays, maintenance model is transferring from plan maintenance to condition based maintenance step by step. Since hydropower generator unit is a very complicated system that involving hydraulic, electrical and mechanical factors, such as the fault mechanism, diagnosis methods, data channel, evaluation principle of life and maintenance decision supporting system are not fully researched. Condition based maintenance system focuses on such fields as reducing units’maintenance cost, improving devices’operating efficiency and maintenance predictive. Since it is a difficult engineering includes electricity fields and management fields, there is no actual condition based maintenance system in real life. In line with performance test and monitoring diagnosis project that research team responded for, such key technologies for condition based maintenance as: fault mechanism, diagnosis methods, data channels, signal extracting, symptom identification and trend-based forecasting. All of these research can do some good for the eventually implementation of condition based maintenance.
Fault reasons analysis is essential for fault diagnosis. It does some research on the extraordinary runner hang-up in Tian Huangping Hydropower Station, the abnormal vibration of Three Gorges Hydropower Station left bank #6 generator unit under 4% guide vane opening and the mechanism of turbine runner crack. By means of theoretical analysis, numerical simulation and prototype test. Research results indicate: the main cause of hang-up is the variety of leakage discharge of sealing ring, which results in the change of axial force of shaft, and the jam or damage of seal parts may lead to the leakage discharge variation; “negative discharge”can not be the cause of abnormal vibration under small opening and possible reason of “fluid structure resonance”is also analyzed; when static and dynamic stress acted on runner blade reach fatigue limitation, accumulated fatigue damage may leads to the micro crack or extend of crack, is responsible for runner blade fracture, and excessive dynamic stress is the main cause.
And traditional diagnosis methods are not adequately. CBR (Case Based Reasoning) is introduced into hydropower generator sets fault diagnosis, and it lowers the difficulty of
knowledge acquisition; also shafting model of hydropower generator units is modified to relief the bottleneck of knowledge repository by implementing shafting simulation results as the fault diagnosis knowledge database. Since oil film force acquisition by interpolating the oil film force database, time complexity is reduced. A diagnosis strategy based on multi method diagnosis league is also introduced to improve the diagnosis accuracy. Equipments’operating conditions can be obtained through axis orbit and conventional identification algorithm of axis orbit is low accuracy or too complex. A new method of axis orbit automatic identification base on moment invariant is proposed. It acquires the axis orbit shape parameters to help operation personnel to deeper diagnosis by ways of optimization method. Since signal extract algorithm is critical to determine whether symptom reflects current operating conditions and signal trend-based forecasting algorithm effects the decision of future operating conditions, local weak signal is extracted based on harmonic wavelet and prediction in line with maximal Lyapunov exponent is introduced into hydro-generator unit fields Data channels are also analyzed: a hybrid network transmission model of B/S (Browser/Server) and C/S (Client/Server) is used to consist of distributed monitoring and diagnosis system; memory database is adopted to decrease the times of operation of hard disk and improve the real–time performance; a new intelligent data store algorithm is brought forward to reduce the data size that stored in database and also assures sufficient data to analyze; Matlab Web Server is the first time introduced into hydro-generator sets faults diagnosis to implement distributed remote monitoring and diagnosis system.
引文
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