摘要
热电联产机组作为综合能源系统的重要组成部分之一,不仅承担着电能和热能的生产与传输等环节,也为系统消纳可再生能源提供了基础。风机和磨煤机作为热电联产机组的重要辅机设备,对热电联产机组的正常运行发挥着重要作用。介绍了故障预警技术背景,并对风机和磨煤机的故障类型进行了总结,随后基于人工智能算法将故障预警技术分为机器学习、深度学习和组合模型3种技术路线展开叙述。分析总结了各个技术的发展趋势和核心问题。最后对当前故障预警技术在综合能源系统中的发展应用进行了展望。
As an important component of an integrated energy system,a CHP unit not only provides electric and thermal power,but also lays a foundation for renewable energy consumption.The fan and coal mill are significant devices for a cogeneration unit and play vital roles in its operation.In the research on fault diagnosis technologies,faults in fans and coal mills are summarized,and subsequently,based on artificial intelligence algorithms,the fault diagnosis technologies are categorized into three technical approaches:machine learning,deep learning,and hybrid models.The development trends and core issues of each technology are analysed.Finally,the prospects of fault diagnosis technologies applying in integrated energy systems are discussed.
作者
邓振宇
汪茹康
徐钢
云昆
王颖
DENG Zhenyu;WANG Rukang;XU Gang;YUN Kun;WANG Ying(School of Energy,Power and Mechanical Engineering,North China Electric Power University,Beijing 102206,China;North Engineering Design and Research Company Limited,Shijiazhuang 050011,China)
出处
《综合智慧能源》
CAS
2024年第8期67-76,共10页
Integrated Intelligent Energy
基金
国家自然科学基金项目(51821004)。