摘要
针对大型汽轮发电机组的状态监测与故障诊断问题，为了克服单一故障诊断方法的局限性，对现有大型设备故障诊断方法作了全面的分析和比较之后，提出并探讨了多种故障诊断技术集成的混合智能诊断方法。该方法根据设备故障诊断过程的不同阶段和具体任务，综合利用了模糊数学、模糊模式识别、模糊人工神经网络、基于规则的诊断专家系统等多种故障诊断原理，并且已经分别在电站热力系统的故障诊断和机组振动故障诊断中实际应用。
In order to improve the ability of condition monitoring and fault diagnostic system, a hybrid intelligent diagnostic method for condition monitoring and fault diagnosis of large steam turbine generator sets is proposed. This method integrates different intelligent diagnostic techniques, includes signal analysis, fuzzy logic, fuzzy pattern recognition, fuzzy neural network and knowledge based systems. It has been used to monitor, analyze and diagnose the condition of thermal system and vibration faults of machinery in power plants.
出处
《清华大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
1999年第3期75-78,共4页
Journal of Tsinghua University(Science and Technology)
基金
国家攀登计划
关键词
状态监测
故障诊断
专家系统
汽轮发电机组
large power plants
condition monitoring
fault diagnosis
fuzzy logic
pattern recognition
artificial neural network
expert systems
