液体火箭发动机涡轮泵多维度传感器优化布置

马珮羽; 杨宝锋; 陈晖; 翟智; 王晨希; 马猛; 陈雪峰

doi:10.7652/xjtuxb202409008

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液体火箭发动机涡轮泵多维度传感器优化布置

—————————————————————— | 更新时间：2025-07-28

- 液体火箭发动机涡轮泵多维度传感器优化布置
- Multidimensional Sensor Optimization Placement for Turbopump in Liquid Rocket Engines
- 西安交通大学学报 2024年58卷第9期页码：72-82
- 作者机构：
  
  1. 西安交通大学机械工程学院,西安,710049
  2. 西安航天动力研究所,西安,710100
- 作者简介：
  
  : 2023-12-27。作者简介: 马珮羽(1999—),女,硕士生
  翟智(通信作者),女,副研究员,博士生导师。基金项目: 国家自然科学基金资助项目(52205124)。
- 基金信息：
  
  : 2023-12-27。作者简介: 马珮羽(1999—),女,硕士生;翟智(通信作者),女,副研究员,博士生导师。基金项目: 国家自然科学基金资助项目(52205124)。
- DOI：10.7652/xjtuxb202409008
  中图分类号： TH212;TH213.3
- 纸质出版：2024
- 稿件说明：
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马珮羽, 杨宝锋, 陈晖, 等. 液体火箭发动机涡轮泵多维度传感器优化布置[J]. 西安交通大学学报, 2024,58(9):72-82.

MA Peiyu, YANG Baofeng, CHEN Hui, et al. Multidimensional Sensor Optimization Placement for Turbopump in Liquid Rocket Engines[J]. 2024, 58(9): 72-82.
马珮羽, 杨宝锋, 陈晖, 等. 液体火箭发动机涡轮泵多维度传感器优化布置[J]. 西安交通大学学报, 2024,58(9):72-82. DOI： 10.7652/xjtuxb202409008.

MA Peiyu, YANG Baofeng, CHEN Hui, et al. Multidimensional Sensor Optimization Placement for Turbopump in Liquid Rocket Engines[J]. 2024, 58(9): 72-82. DOI： 10.7652/xjtuxb202409008.

摘要

针对液体火箭发动机涡轮泵健康监测时存在的结构重要模态信息遗漏、故障敏感信息提取不全等问题

提出了一种涡轮泵传感器多维度优化布置方法

并采用故障模拟实验台进行了实验验证。首先

建立了涡轮泵待优化区域的有限元模型并开展了结构约束模态分析以及轴承故障仿真瞬态动力学分析; 其次

基于离散人工蜂群算法及瞬态分析结果得出传感器布置候选点集; 再次

综合传感器多维度评估方法得出最终的传感器布置方法; 最后

通过实验对比分析了传感器布置方法与传统方法的综合指标。计算结果表明:相对于有效独立法

布置测点优化后

传感器监测信号的模态振型符合率提高了20.1%

对轴承故障检测的准确率提高了27.5%

验证了多维度优化布置方法具有良好的故障诊断综合性能。

Abstract

A method of multidimensional optimization placement of turbopump sensors is proposed to address the issues of missing structurally important modal information and incomplete extraction of fault-sensitive information during the health monitoring of liquid rocket engine turbopumps. Experimental verification is conducted using a fault simulation test bench. Firstly

a finite element model of the turbopump's optimization area is established to conduct structural constrained modal analysis and transient dynamic analysis of bearing faults. Subsequently

candidate points for sensor placement are indentified based on the discrete artificial bee colony algorithm and transient analysis results. The final sensor placement method is determined through a comprehensive multidimensional evaluation method of sensors. Finally

the comprehensive indicators between the proposed sensor placement method and the traditional method are experimentally compared. The calculation results show that

compared with effective independence

after optimizing the placement of measurement points

sensor monitoring signal modal shape compliance increased by 20.1%

and the accuracy of bearing fault detection increased by 27.5%. This verifies that the multidimensional optimization placement method has good comprehensive performance in fault diagnosis.

关键词

Keywords

references

谢光军. 液体火箭发动机涡轮泵实时故障检测技术及系统研究 [D]. 长沙: 国防科学技术大学, 2006.

夏鲁瑞. 液体火箭发动机涡轮泵健康监控关键技术及系统研究 [D]. 长沙: 国防科学技术大学, 2010.

杨硕. 基于支持向量机的涡轮泵故障检测算法研究 [D]. 成都: 电子科技大学, 2015.

伊廷华, 张旭东, 李宏男. 基于协同爬猴群算法的传感器优化布置方法研究 [J]. 计算力学学报, 2014, 31(6): 681-686.

YI Tinghua, ZHANG Xudong, LI Hongnan. Collaborative-climb monkey algorithm for optimal sensor placement [J]. Chinese Journal of Computational Mechanics, 2014, 31(6): 681-686.

KAMMER D C. Sensor placement for on-orbit modal identification and correlation of large space structures [J]. Journal of Guidance, Control, and Dynamics, 1991, 14(2): 251-259.

CARNE T G, DOHRMANN C R. A modal test design strategy for model correlation [J]. Proceedings of SPIE-the International Society for Optical Engineering, 1994, 2460: 927.

DOWNEY A, HU Chao, LAFLAMME S. Optimal sensor placement within a hybrid dense sensor network using an adaptive genetic algorithm with learning gene pool [J]. Structural Health Monitoring, 2018, 17(3): 450-460.

DOWNEY A, HU Chao, LAFLAMME S. Optimal sensor placement within a hybrid dense sensor network using an adaptive genetic algorithm with learning genepool [J]. Structural Health Monitoring, 2018, 17(3): 450-460.

SEYEDPOOR S M. A two stage method for structural damage detection using a modal strain energy based index and particle swarm optimization [J]. International Journal of Non-Linear Mechanics, 2012, 47(1): 1-8.

赵建华, 张陵, 孙清. 利用粒子群算法的传感器优化布置及结构损伤识别研究 [J]. 西安交通大学学报, 2015, 49(1): 79-85.

ZHAO Jianhua, ZHANG Ling, SUN Qing. Optimal placement of sensors for structural damage identification using improved particle swarm optimization [J]. Journal of Xi'an Jiaotong University, 2015, 49(1): 79-85.

YI Tinghua, LI Hongnan, ZHANG Xudong. Health monitoring sensor placement optimization for Canton Tower using immune monkey algorithm [J]. Structural Control and Health Monitoring, 2015, 22(1): 123-138.

YI Tinghua, LI Hongnan, WANG Chuanwei. Multiaxial sensor placement optimization in structural health monitoring using distributed wolf algorithm [J]. Structural Control and Health Monitoring, 2016, 23(4): 719-734.

LI Shiqi, ZHANG Heng, LIU Shiping, et al. Optimal sensor placement using FRFs-based clustering method [J]. Journal of Sound and Vibration, 2016, 385: 69-80.

YOGANATHAN D, KONDEPUDI S, KALLURI B, et al. Optimal sensor placement strategy for office buildings using clustering algorithms [J]. Energy and Buildings, 2018, 158:1206-1225.

张恒, 李世其, 刘世平, 等. 一种聚类优化的传感器布置方法研究 [J]. 振动与冲击, 2017, 36(14): 61-65.

ZHANG Heng, LI Shiqi, LIU Shiping, et al. Optimal sensor placement by using clustering method [J]. Journal of Vibration and Shock, 2017, 36(14): 61-65.

SUN Hao, BÜYÜKÖZTÜRK O. Optimal sensor placement in structural health monitoring using discrete optimization [J]. Smart Materials and Structures, 2015, 24(12): 125034.

YI Tinghua, LI Hongnan, ZHANG Xudong. Sensor placement on Canton Tower for health monitoring using asynchronous-climb monkey algorithm [J]. Smart Materials and Structures, 2012, 21(12): 125023.

刘艳, 刘贵杰, 刘波. 传感器优化布置研究现状与展望 [J]. 传感器与微系统, 2010, 29(11): 4-6.

LIU Yan, LIU Guijie, LIU Bo. Research status and prospect on optimal placement of sensor [J]. Transducer and Microsystem Technologies, 2010, 29(11): 4-6.

KARABOGA D. An idea based on honey bee swarm for numerical optimization: technical report TR06 [R/OL].(2005-01-01)[2023-12-01]. http: //mf.erciyes.edu.tr/abc/pub/tro6_2005.pdf.

CHEN Benlan. Analysis of shock calculation based on Newmark integral method [C]//Journal of Physics: Conference Series. Bristol, United Kingdom: IOP Publishing, 2021: 012056.

杨金亮. 基于智能算法的传感器布设多目标优化方法研究 [D]. 哈尔滨: 哈尔滨工业大学, 2021.

杨宝锋, 金路, 王晓锋, 等. 两条流体力传递途径下涡轮泵壳体振动特性 [J]. 火箭推进, 2023, 49(1): 72-79.

YANG Baofeng, JIN Lu, WANG Xiaofeng, et al. Vibration characteristics of the turbopump casing under two different fluid force transmission paths [J]. Journal of Rocket Propulsion, 2023, 49(1): 72-79.

刘士杰, 梁国柱. 航天飞机主发动机高压燃料涡轮泵的故障模式 [J]. 航空动力学报, 2015, 30(3): 611-626.

LIU Shijie, LIANG Guozhu. Failure modes of space shuttle main engine high-pressure fuel turbopump [J]. Journal of Aerospace Power, 2015, 30(3): 611-626.

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