文章摘要
潘罗平,安学利,周叶.基于大数据的多维度水电机组健康评估与诊断[J].水利学报,2018,49(9):1178-1186
基于大数据的多维度水电机组健康评估与诊断
Multi-dimension health assessment and diagnosis of hydropower unit based on big data
投稿时间:2018-07-17  
DOI:10.13243/j.cnki.slxb.20180658
中文关键词: 健康样本  水电机组  智能评估  运行分区  安全高效
英文关键词: health samples  hydropower unit  intelligent assessment  running zone  safe and efficient
基金项目:中国水科院基本科研业务费项目(HM0145B222018)
作者单位E-mail
潘罗平 中国水利水电科学研究院 水力机电研究所, 北京 100038  
安学利 中国水利水电科学研究院 水力机电研究所, 北京 100038 an_xueli@163.com 
周叶 中国水利水电科学研究院 水力机电研究所, 北京 100038  
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中文摘要:
      考虑到当前水电机组安全高效运行领域存在的健康状态评估不准确、故障样本少、故障知识不健全和大型机组安全高效运行准则缺乏等问题,本文通过分析提炼水电机组试验、在线监测及运行维护等海量健康数据,提出了表征机组运行状态的特征参数,揭示了各特征参数与机组运行工况参数之间的耦合关系,最终建立了基于健康样本的多维度水电机组健康评估和性能退化预测理论方法。此外,本研究还提出了大型机组安全稳定运行分区准则。基于所建模型和准则,建立了大型水电机组远程状态监测与诊断系统平台。为保障水电机组安全、稳定和高效运行提供了重要技术支撑。
英文摘要:
      At present, there are some problems in the safe and efficient operation of hydropower units, such as inaccurate health assessment, fewer fault samples,inadequate fault knowledge, lack of safe and efficient operation guidelines for large units, etc. The healthy data of hydropower unit test, on-line monitoring and operation and maintenance are analyzed. The characteristic parameters that represent the running status of the unit are proposed. The coupling relationship between characteristic parameters and the unit operating condition parameters is revealed. The multi-dimensional health assessment and performance degradation prediction theory of hydropower unit based on healthy samples is established. The zoning guideline for safe and stable operation of large-scale units is proposed. Based on the established model and criteria, a remote hydropower unit monitoring and diagnosis system platform is established. It provides important technical support for ensuring the safe,stable and efficient operation of hydropower unit.
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