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燃气轮机气路故障诊断技术综述与展望
引用本文:田书耘,万震天,谢岳生.燃气轮机气路故障诊断技术综述与展望[J].能源研究与信息,2022,38(1):23-28.
作者姓名:田书耘  万震天  谢岳生
作者单位:上海发电设备成套设计研究院有限责任公司,上海 200240
摘    要:气路故障是燃气轮机的主要故障形式,对燃气轮机安全性和经济性影响重大,因此研究气路故障诊断方法至关重要。总结了国内外燃气轮机气路故障诊断技术研究的发展现状,并对各种研究方法进行了归类,分别讨论了基于模型、基于数据和基于知识方法进行故障诊断的优势、进展、适用范围及3种方法互相结合的可能性,重点介绍了近年来新兴的深度学习和融合诊断方法,最后探讨了该领域值得进一步研究的问题和可能的发展方向。

关 键 词:燃气轮机  气路故障诊断  深度学习  融合诊断
收稿时间:2020/5/7 0:00:00

Review and outlook of gas path fault diagnosis technology in the gas turbine
TIAN Shuyun,WAN Zhentian,XIE Yuesheng.Review and outlook of gas path fault diagnosis technology in the gas turbine[J].Energy Research and Information,2022,38(1):23-28.
Authors:TIAN Shuyun  WAN Zhentian  XIE Yuesheng
Affiliation:Shanghai Power Equipment Research Institute Co., Ltd., Shanghai 200240, China
Abstract:Gas path fault is the main fault mode in the gas turbine, which has a significant impact on its safety and economy. Therefore, it is important to study diagnosis methods for gas path fault. The development status of gas path fault diagnosis technology in the gas turbine was summarized at home and abroad, and various research methods were classified. The advantages, progress and application of three fault diagnosis methods based on models, data, and knowledge as well as their combination were discussed. The emerging deep learning and fusion diagnosis methods were highlighted. The problems and possible development directions in this field were discussed finally as the future research directions.
Keywords:gas turbine  gas path fault diagnosis  deep learning  fusion diagnosis
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