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旋转机械健康状态评估方法研究现状与展望

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旋转机械是机械装备的重要组成部分,其内部结构复杂度高,关键零部件与子系统之间耦合度强,长期在复杂工况下运行易发生故障。一旦发生故障,会导致整机性能下降,甚至造成重大经济损失或人员伤亡。因此,旋转机械健康状态评估研究已成为现代国防与工业装备发展中的重点之一。从旋转机械的健康管理与智能运维需求出发,首先,论述了健康状态评估在机械设备智能运维中的地位和作用;其次,介绍了健康状态评估技术的概念、状态等级的划分以及评估指标;再次,阐述了基于知识经验、模型驱动和数据驱动的典型评估方法;进而,综述了近年来国内外学者在泵、轴承、齿轮箱和航空发动机等典型旋转机械健康状态评估方面的研究成果;最后,基于健康状态评估方法研究面临的技术挑战和发展趋势,对旋转机械健康状态评估方法的发展方向进行了探讨和展望。
Research status and prospect of health status assessment methods for rotating machinery
Rotating machinery is an important component of mechanical equipment,with complex in-ternal structural complexity and strong coupling degree between its key components and subsystems.It is prone to easy failure under long-term complex working conditions.Once the failure occurs,it can lead to the decline overall performance of the machine,and even cause significant economic losses or personal injury.Therefore,the research on the health status assessment of rotating machinery has be-come one of the key points in the development of modern national defense and industrial equipment.Based on the requirements of health management and intelligent maintenance of rotating machinery,the status and role of health status assessment in intelligent operation and maintenance of mechanical equipment are firstly discussed.Secondly,the concept of health status assessment technology,the clas-sification of status levels,and assessment indicators are introduced.Thirdly,typical assessment methods based on knowledge and experience,model-driven,and data-driven methods are illustrated.Fourth,the research achievements in the evaluation of health status of typical rotating machinery in re-cent years are reviewed,such as pumps,bearings,gearboxes,and aircraft engines.Finally,based on technical challenges and development trends faced by research on health status assessment methods,the development direction of health status assessment methods for rotating machinery is discussed and prospected.

rotating machineryhealth status assessmentfault identificationremaining life predictionassessment method

苏红、朱勇、刘金华、高强

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江苏大学国家水泵及系统工程技术研究中心,江苏镇江 212013

共青科技职业学院国际航运研究院,江西九江 332020

旋转机械 健康状态评估 故障识别 剩余寿命预测 评估方法

中国博士后科学基金面上项目江苏省高等学校自然科学研究项目

2022M72370222KJB460002

2024

排灌机械工程学报
中国农业机械学会排灌机械分会,江苏大学流体机械工程技术研究中心

排灌机械工程学报

CSTPCD北大核心
影响因子:1.055
ISSN:1674-8530
年,卷(期):2024.42(3)
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