摘要
针对机组状态监测技术无法实时、有效地获取机组健康状况信息的问题,根据系统构成与行为关系模型及专家通过人工试验掌握机组健康状况的思路,提出了基于宏试验的机组健康状况在线监测方法。将机组正常运行中经历的工况当成试验,与人工试验统称为宏试验;在机组全状态监测的基础上,实时自动地识别宏试验、记录试验数据及计算试验性能指标;通过运行状态异常检测及性能降低与越限检测实时评估机组健康状况,实现机组健康状况在线监测。该方法已成功应用于葛洲坝电站,实际运行证明了该方法的实用性与有效性。
In view of the inability of the condition monitoring technique of the hydroelectric generating sets to effectively obtain health condition information in real time, an online monitoring approach to the health condition of hydroelectric generating sets based on macro tests is proposed according to the model for the relationship between system composition and behavior and with the help of thought used to grasp the health condition of hydroelectric generating sets by experts through artificial tests. The operating conditions of hydroelectric generating sets in normal running are regarded as tests, which are spoken of as macro tests along with artificial tests. On the basis of complete state monitoring for hydroelectric generating sets, the identification of macro tests, the record of test data, and the calculation of performance indices of macro tests are automatically completed in real time. Through the detection of operating state abnormalities, degraded performance or detection ultra vires, online monitoring for the health condition of hydroelectric generating sets can be realized. This approach has been successfully applied in Gezhouba Hydropower Station, whose practicality and effectiveness are proved by actual operations.
出处
《电力系统自动化》
EI
CSCD
北大核心
2012年第8期71-76,共6页
Automation of Electric Power Systems
关键词
水电机组
在线监测
异常检测
宏试验
性能评估
健康状况
hydroelectric generating set
online monitoring
failure detection
macro test
performance evaluation
health condition
