航天推进技术研究院主办
[1]姚尚鹏,黄红,赵佳敏,等.涡轮泵典型故障仿真与辨识系统设计[J].火箭推进,2023,49(03):96-104.
YAO Shangpeng,HUANG Hong,ZHAO Jiamin,et al.Typical fault simulation and identification system design for turbopump[J].Journal of Rocket Propulsion,2023,49(03):96-104.
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YAO Shangpeng,HUANG Hong,ZHAO Jiamin,et al.Typical fault simulation and identification system design for turbopump[J].Journal of Rocket Propulsion,2023,49(03):96-104.
涡轮泵典型故障仿真与辨识系统设计
《火箭推进》[ISSN:1672-9374/CN:CN 61-1436/V]
卷:
49
期数:
2023年03期
页码:
96-104
栏目:
目次
出版日期:
2023-06-25
- Title:
- Typical fault simulation and identification system design for turbopump
- 文章编号:
- 1672-9374(2023)03-0096-09
- 分类号:
- V434.21
- 文献标志码:
- A
- 摘要:
- 涡轮泵是液体火箭发动机的关键部件,工作环境恶劣,故障率较高。特别是复杂高温、高压燃料冲击的转子系统,极易发生不平衡、不对中和叶片掉块故障。迫切需要探究涡轮泵转子常见的故障机理,阐明故障特征,建立典型故障的辨识系统。通过分析故障力模型,分别建立了考虑转子不平衡、不对中和叶片掉块的动力学模型,确定涡轮泵转子振动特征,明确转子时域、频域信号以及轴心轨迹。进一步搭建基于Matlab GUI平台的涡轮泵典型故障仿真与辨识系统,并对测试数据开展处理。研究表明,不平衡故障时域波形为正弦曲线,1倍频占优,椭圆形轴心轨迹; 不对中故障时域波形由2组不同的正弦曲线组成,2倍频占优,“内8”形轴心轨迹; 叶片掉块时域波形存在突变现象,1倍频占优,轴心轨迹在掉块发生前稳定,掉块发生后较为杂乱。结果表明,信号频域特征是故障辨识的关键,辅以时域特征,能准确辨识出3种典型故障,该系统能够为涡轮泵转子故障辨识设计提供技术支撑。
- Abstract:
- Turbine pump is a key component of liquid rocket engine, with harsh working environment and high failure rate. Especially, the rotor system with complex high temperature and high pressure fuel impact is highly prone to unbalance, misalignment and blade drop block failures. It is urgent to explore the common fault mechanism of turbopump rotor, clarify the fault characteristics and establish the identification system of typical failures. In this paper, by analyzing the failure force model, the dynamics models considering the rotor unbalance, misalignment and blade dropout are established respectively, to determine the vibration characteristics of the turbine pump rotor and clarify the rotor time domain and frequency domain signals as well as the axial trajectory. Further, a typical fault simulation and identification system of turbine pump based on Matlab GUI platform is built and the test data are processed. The research shows that the time domain waveform of the unbalanced fault is a sine curve with 1 frequency dominance and elliptical axis trajectory; the time domain waveform of the misalignment fault is composed of two different sets of sine curves with 2 frequency dominance and "inner 8" shaped axis trajectory; the time domain waveform of the blade block drop has abrupt changes with 1 frequency dominance, and the axis trajectory is stable before the block drop occurs but more chaotic after the block drop occurs. The above research results show that the signal frequency domain characteristics are crucial to fault identification. Supplemented by time domain characteristics, three typical faults can be accurately identified, and the system can provide technical support for the fault identification design of turbine pump rotor.
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备注/Memo
收稿日期:2022-06-07; 修回日期:2022-07-11
基金项目:国家自然科学基金项目(12102348)
作者简介:姚尚鹏(1999—),男,硕士,研究领域为液体火箭发动机故障诊断及健康管理。
更新日期/Last Update:
1900-01-01